Reading/ Writing

• How to Read a Paper by S. Keshav, ACM SIGCOMM Computer Communication Review archive Volume 37 Issue 3, July 2007, PDF

• Timothy Roscoe, "Writing reviews for systems conferences", PDF
• George M. Whtesides, "Whitesides' Group: Writing a Paper", PDF
• "Writing Technical Articles", URL

• NeuroPhone
• EyePhone
• CenseMe
• SenSys2010 Keynote Bigger
• Honk-OK-Please

MOBILITY VISIONS There have been many vision papers in computer science that include aspects of mobile computing. The following four papers have had the most significant impact on the research community. The first two topics below, ubiquitous and pervasive computing, were initially distinct terms deriving from research programs at Xerox PARC and IBM, respectively. However, over time they have evolved to include an expanded set of ideas, and now the research community considers them to be synonymous. These programs make the case for the benefits and opportunity that embedded computing can bring to work practices via wireless coordination. The third topic, autonomous computing, argues that we need self-managed computer systems to handle complexity; a problem that has become particularly acute now that billions of mobile devices are in use throughout the world. And the fourth topic, sentient computing, argues for designing computer systems that are capable of monitoring and responding to real-time data sensed from the physical world.

• The Computer for the 21st Century by Mark Weiser. Scientific American (Sept. 1991), pp. 94-10. DOI=10.1145/329124.329126.
  • The World Is Not A Desktop (ACM DL: Free for Members) by Mark Weiser. Interactions, vol.1, issue 1 (Jan. 1994), pp. 7-8. DOI=10.1145/174800.174801.

• Pervasive Computing: Vision and Challenges. M. Satyanarayanan. IEEE Personal Communications, vol.8, issue 4 (Aug. 2001), pp.10-17. DOI=10.1109/98.943998.

• The Vision of Autonomic Computing. Jeffrey O. Kephart and David M. Chase. IEEE Computer, vol. 36, issue 1 (Jan. 2003), pp. 41-50. DOI=10.1109/MC.2003.1160055.

• Sentient Computing. Andy Hopper. Philosophical Transactions of the Royal Society of London, vol. 358 (Aug. 2000), pp. 2349-2358. DOI=10.1098/rsta.2000.0652.

The following two articles provide a summary of the research challenges in mobile computing in 1995, and then later in 2011, almost 15 years apart, in a fast changing field. Reading these two articles together will provide a perspective view of mobile computing achievements and the remaining open issues in this exciting field:

• Fundamental Challenges in Mobile Computing
M. Satyanarayanan. Proceedings of the Annual ACM Symposium on Principles of Distributed Computing (PODC), ACM, 1996. DOI=10.1145/248052.248053.
  • Mobile Computing: The Next Decade (ACM DL: Free for Members). 
M. Satyanarayanan. 2010. Proceedings of the ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond (MCS), ACM, 2010. DOI=10.1145/1810931.1810936.

Context-aware computing enables a computer to modify its behavior based on its local context such as location, time of day, who is nearby, and state of motion. As a result, computer applications can provide an improved user experience by customizing their behavior to better support a user task. This kind of adaptation is particularly useful when designing mobile applications that will be placed in continuously changing contexts. There are two key components required for creating context-awareness: first, the ability to capture a wide-variety of sensor data (both hardware sensors and software sensors); and second, to infer activities based on that data. The following articles provide an overview of the research in this area:

• [Survey] A Survey of Context-Aware Mobile Computing Research. 
G. Chen and D. Kotz. 2000. Tech. Rep. TR2000-381, Department of Computer Science, Dartmouth College (Nov. 2000). 
Summary: An overview of the key concepts and projects, exploring context-aware computing from 1994-2000. As the publication date is 2000, it is missing more recent work, but the core concepts and original projects are worth the read.

• [System] Context-Aware Computing Applications. 
Bill Schilit, Norman Adams, and Roy Want. First Annual Workshop on Mobile Computing Systems and Applications (WMCSA), IEEE, 1994. DOI=10.1109/WMCSA.1994.16. 
Summary: Describes the context-aware applications designed and built using the ParcTab System (the first mobile context-aware computer system). Four categories of context-aware applications are presented: proximate selection, automatic contextual reconfiguration, contextual information and commands, and context-triggered actions.

• [Experience] Inferring Activities from Interactions with Objects. 
M. Philipose, K.P. Fishkin, M. Perkowitz, D.J. Patterson, D. Fox, H. Kautz, and D. Hahnel. IEEE Pervasive Computing, vol. 3, issue 4 (2004), pp. 50-57. DOI=10.1109/MPRV.2004.7. Also available at CiteSeer. 
Summary: Applies context-awareness to systems that help elders maintain an independent lifestyle; that is, a support mechanism sometimes referred to as assisted living. Monitoring the activities of daily living (ADL) is one way to ensure that elders are coping with everyday tasks and not entering into a decline. This article describes mobile computing techniques that automate this process using radio-frequency-identification technology, data mining, and a probabilistic inference engine.

• [Theory] A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications (ACM DL: Free for Members). 
Anind K. Dey, Daniel Salber, and Gregory D. Abowd. Journal Human-Computer Interaction, vol.16, issue 2 (2001), pp. 97-166. DOI=10.1207/S15327051HCI16234_02. 
Summary: Anchor article of a special issue on context-aware computing. It presents a conceptual framework that separates the acquisition and representation of context from its delivery and effect, as employed by a context-aware application. The authors describe the design of the Context Toolkit, which instantiates this conceptual framework, and supports the rapid development of a rich space of context-aware applications.

• [General] SeeMon: Scalable and Energy-Efficient Context Monitoring Framework for Sensor-Rich Mobile Environments (ACM DL: Free for Members). 
S. Kang, J. Lee, H. Jang, H. Lee, Y. Lee, S. Park, T. Park, and J. Song. Proceedings of the ACM International Conference on Mobile Systems, Applications, and Services, ACM, 2008. DOI=10.1145/1378600.1378630. 
Summary: This article describes SeeMon, a scalable and energy-efficient context monitoring-framework for sensor-rich, resource-limited mobile environments. The system runs on a personal mobile device, such as a smart phone, performing context-monitoring operations involving multiple sensors and applications. A key feature of the design is low-power operation.

• [General] Determining Transportation Mode on Mobile Phones. 
Sasank Reddy, Jeff Burke, Deborah Estrin, Mark Hansen, and Mani Srivastava. 
IEEE International Symposium on Wearable Computers (ISWC), IEEE, 2008. DOI=10.1109/ISWC.2008.4911579. Also available at http://research.cens.ucla.edu/people/estrin/resources/conferences/2008sep-Reddy-Burke-Determining_Transportation.pdf. 
Summary: a study showing that a modern mobile phone with GPS and an accelerometer can be used to discern whether an individual is stationary, walking, running, biking, or in motorized transport, with an accuracy greater than 90%

Mobile routing in the context of ad-hoc networks has received lots of attention from the research community. Below, we include a few representative articles in this area, such as the key original ones that defined a new ad-hoc protocol, and a survey that compares them. We also provide a reference for the theoretic analysis of the capacity of such a network, and an article that examines the critical model required to make a simulation accurate. An excellent quite comprehensive list of ad hoc routing protocols along with their references can also be found on Wikipedia at the link included:

• [Survey] Topology Control and Routing In Ad Hoc Networks: A Survey (ACM DL: Free for Members). 
Rajmohan Rajaraman. ACM SIGACT News, vol. 33, issue 2 (June 2002). DOI=10.1145/564585.564602.
Summary: This article first surveys research work on topology control for various objectives, including network connectivity, energy efficiency, throughput, and robustness to mobility. It then reviews a number of routing protocols, ranging from flat routing, such as DSR, AODV, and TORA, to hierarchical routing to geographical routing.

• [System] Dynamic Source Routing (DSR) in Ad Hoc Wireless Networks. 
David B. Johnson and David A. Maltz. Mobile Computing, vol. 353 (1996), pp.153-181. 
Summary: This is a seminal article on routing in ad hoc networks. It is the first to propose the idea of reactive routing (i.e., finding a route to a node only when there is traffic sent to that node). Due to its simplicity, DSR routing has become one of the most popular ad-hoc routing protocols.

• [System] Ad hoc On-Demand Distance Vector Routing. 
Charles E. Perkins and Elizabeth M. Royer. Proceedings of the IEEE Workshop on Mobile Computing Systems and Applications (WMCSA), IEEE,1999. DOI= 10.1109/MCSA.1999.74928. 
Also available at http://www.cs.ucsb.edu/~ebelding/txt/wmcsa99.pdf. 
Summary: AODV is another popular routing protocol. It is a reactive routing protocol like DSR, but is different than DSR in that it uses a routing table instead of source routes to reduce overhead in data traffic. It also includes more aggressive route invalidation to eliminate invalid routes.

• [System] A Highly Adaptive Distributed Routing Algorithm for Mobile Wireless Networks. 
V.D. Park and M.S. Corson. Proceedings Annual Joint Conference of the IEEE Computer and Communications Societies (INFCOM), IEEE, 1997. DOI=10.1109/INFCOM.1997.631180. 
Summary: Describes the TORA protocol, or Time Ordered Routing Algorithm, and is another example of a flat routing strategy that is also link-reversible. TORA is very adaptable and stable in the presence of network partitions.

• [Experience] Experimental Evaluation of Wireless Simulation Assumptions (ACM DL: Free for Members). 
Calvin Newport, David Kotz, Yougu Yuan, Robert S. Gray, Jason Liu, and Chip Elliott.Proceedings of the ACM International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), ACM, 2004. DOI=10.1145/1023663.1023679. 
Summary: This article reexamines the assumptions made about mobility in wireless networks in order to model them. By comparing analytical and simulation results, the authors try to find the tipping point at which a simulation model can be simplified but can still capture the realism of a deployment.

• [Theory] The Capacity of Wireless Networks. 
P. Gupta and P.R. Kumar. IEEE Transactions on Information Theory, vol. 46, issue 2 (March 2002), pp. 388-404. DOI=10.1109/18.825799. 
Also available at http://www.mit.edu/~6.454/www_fall_2000/everest/guptakumar.pdf. 
Summary: This is a seminal article on capacity analysis of multihop wireless networks. It shows that in a network of n identical nodes, each of which is communicating with another node, the throughput per node is 1/sqrt(n.logn), assuming random node placement and communication pattern, and 1/sqrt(n), assuming optimal node placement and communication pattern.

With the advent of small form-factor devices capable of sensing, processing, and communication, it became possible to conceive of large numbers of small battery-operated wirelessly-connected sensor nodes, which could enable more fine-grain observation of physical phenomena, and man-made structures, than previously possible. An important challenge in networked sensing is managing the energy cost of communication This challenge inspired a whole field devoted to exploring energy-aware network architectures and algorithms, as well as novel applications of sensor networks.

• [System] Directed Diffusion for Wireless Sensor Networking (ACM DL: Free for Members). 
Chalermek Intanagonwiwat, Ramesh Govindan, Deborah Estrin, John Heidemann, and Fabio Silva. ACM/IEEE Transactions on Networking, vol.11, issue 1 (Feb. 2003), pp. 2-16. DOI=10.1109/TNET.2002.808417. 
Summary: An early article in the field, which discusses the trade-offs that sensor networks present, and argues for novel “data-centric” methods for data dissemination that enable aggregation within the network to minimize energy cost.

• [System] The Emergence of a Networking Primitive In Wireless Sensor Networks (ACM DL: Free for Members). 
Philip Levis, Eric Brewer, David Culler, David Gay, Samuel Madden, Neil Patel, Joe Polastre, Scott Shenker, Robert Szewczyk, and Alec Woo. Communications of the ACM, vol. 51, issue 7 (July 2008), pp. 99-106. DOI=10.1145/1364782.1364804. 
Summary: This article describes an important milestone in the evolution of the field: the emergence of a useful novel primitive for code dissemination or for routing, low 
overhead network-wide reliable dissemination. Using ideas from gossiping and epidemic propagation, Trickle scales well to large networks propagating updates and ensures fast network-wide consistency.

• [Experience] The Hitchhiker's Guide to Successful Wireless Sensor Network Deployments(ACM DL: Free for Members). 
Guillermo Barrenetxea, Francois Ingelrest, Gunnar Schaefer, and Martin Vetterli. Proceedings of the ACM Conference on Embedded Network Sensor Systems (SenSys), ACM, 2008, pp.43-56. DOI=10.1145/1460412.1460418. 
Summary: Very early on, many groups attempted to deploy real applications of sensor networks. This article discusses the experiences of one such deployment, SensorScope, and nicely crystallizes what worked and what didn’t, providing a guide for other deployments.

• [Theory] Near-Optimal Sensor Placements: Maximizing Information While Minimizing Communication Cost (ACM DL: Free for Members). 
Andreas Krause, Carlos Guestrin, Anupam Gupta, and Jon Kleinberg. Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN), 2006. DOI=10.1145/1127777.1127782. 
Summary: Networked sensing inspired lots of interesting theoretical investigations, of which this article is a nice example; it describes the methods to achieve a sensor placement that guarantees high-quality information extraction while ensuring low communication cost.

• [General] IP Is Dead, Long Live IP for Wireless Sensor Networks (ACM DL: Free for Members). 
Jonathan W. Hui and David E. Culler. Proceedings of the ACM Conference on Embedded Network Sensor Systems (SenSys), ACM, 2008. DOI=10.1145/1460412.1460415. 
Summary: An open question in the field was whether it is possible to extend the IP stack out to sensor nodes; early work in the field was built on a specialized stack. This article answers that open question affirmatively, describing an IPv6 stack for sensor nodes.

• [General] The Tenet Architecture for Tiered Sensor Networks (ACM DL: Free for Members). 
Jeongyeup Paek, Ben Greenstein, Omprakash Gnawali, Ki-Young Jang, August Joki, Marcos Vieira, John Hicks, Deborah Estrin, Ramesh Govindan, and Eddie Kohler. ACM Transactions on Sensor Networks, vol. 6, issue 4, (July 2010), 44 pp. DOI=10.1145/1777406.1777413. 
Summary: Many articles in the field also explore high-level programming abstractions and middleware for sensor networks. This article describes an approach that architecturally constrains the placement of functionality in the network to ensure reusable components, and a data-flow application programming language and associated run-time system.

Vehicular networks have emerged from the strong desire to communicate on the move. Car manufacturers all over the world are developing industry standards and prototypes for vehicular networks. The design of vehicular networks involves theoretical, network, system, and security issues.

• [Survey (security issues)] Challenges in Securing Vehicular Networks. 
ABryan Parno and Adrian Perrig. Proceedings of the Workshop on Hot Topics in Networks(HotNets-IV), 2005. 
Summary: This article outlines the research challenges for securing vehicular networks, and then gives an overview of attack models and examples of attacks. The authors present important security primitives, such as location authentication for the origin of a message, anonymization services, and secure aggregation.

• [Survey] Routing in Vehicular Ad Hoc Networks: A Survey. 
Fan Li and Yu Wang. IEEE Vehicular Technology Magazine, vol. 2, issue 2 (June 2007), 
pp.12-22. DOI=10.1109/MVT.2007.912927. 
Summary: This article discusses the research challenges for routing in vehicular ad hoc networks (VANET), and surveys several recent routing protocols, such as position-based routing, cluster routing, broadcast routing, geocast routing; it also describes a few mobility models for VANET.

• [System] Modulation Rate Adaptation in Urban and Vehicular Environments: Cross-Layer Implementation and Experimental Evaluation (ACM DL: Free for Members). 
J. Camp and E. Knightly. Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom), ACM, 2008. DOI=10.1145/1409944.1409981. 
Summary: This article conducts an in-depth study of various rate adaptation schemes in vehicular networks and proposes to select the data-rate based on a combination of RSSI and channel coherence time. It demonstrates its effectiveness using a real implementation.

• [Experience] A Measurement Study of Vehicular Internet Access Using In Situ Wi-Fi Networks(ACM DL: Free for Members). 
V. Bychkovsky, B. Hull, A. Miu, H. Balakrishnan, and S. Madden. Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom). ACM, 2006. DOI=10.1145/1161089.1161097. 
Summary: This article analyzes the measurements carried out for 290 drive hours using a few cars in and around the Boston metropolitan area, and one car from Seattle. The authors find that grassroots Wi-Fi networks are feasible for a range of vehicular network applications, especially those that can tolerate intermittent connectivity.

• [Theory] Relays, Base Stations,and Meshes: Enhancing Mobile Networks with Infrastruture(ACM DL: Free for Members). 
N. Banerjee, M.D. Corner, D. Towsley, and B.N. Levine. Proceedings of the ACM International Conference on Mobile Computing and Networking (MobiCom), AcM, 2008. DOI=10.1145/1409944.1409955. 
Summary: This article analyzes the benefit of adding relays, mesh nodes, and base stations 
to a mobile network. It concludes that adding a small amount of infrastructure to the network 
is vastly superior to adding even a large number of mobile nodes capable of routing to one another.

In this section we single out projects that capture results, perform user evaluations, and record experiences from real-world deployments and user trials. These projects are notable for the design considerations that need to be taken into account for use in the real world, making them more complicated than if deployed in a lab environment or as a theoretical study. As such, these articles inform researchers about real issues that should be taken into account when designing a system for everyday use.

• [Experience] Experiences of Developing and Deploying a Context-Aware Tourist Guide: The GUIDE project (ACM DL: Free for Members). 
K. Cheverst, N. Davies, K. Mitchell, and A. Friday. Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom), 2000. DOI=10.1145/345910.345916. 
Summary: This article describes the GUIDE system, a handheld, context-aware tourist guide. A number of distinct research directions contributing to the overall system are described, including investigating a cell-based wireless communications technology, designing and populating an information model to represent the city tourist attractions, building a prototype, and then trialing and evaluating the system.

• [Experience] An Overview of the PARCTAB Ubiquitous Computing Experiment. 
R. Want, B.N. Schilit, N.I. Adams, R. Gold, D. Goldberg, K. Petersen, J.R. Ellis, and M. Weiser.IEEE Personal Communications, vol. 2, issue 6 (1995), pp. 28-43. DOI=10.1109/98.475986. 
Also available at http://sandbox.parc.com/want/papers/parctab-pcs-dec95.pdf. 
Summary: This article describes the ParcTab project, an original testbed for ubiquitous computing. It covers the ubiquitous computing philosophy, the ParcTab system, user interface issues for small devices and deployment experiences for a wide range of mobile applications. The system and deployment presented provide concepts and experiences that helped shape many mobile computing systems that followed it.

• [Experience] Elderly Persons' Perception and Acceptance of Using Wireless Sensor Networks to Assist Healthcare. 
R. Steele, A. Lo, C. Secombe, and Y. K. Wong. International Journal of Medical Informatics, vol. 78, issue 12 (2009), pp. 788-801. 
Summary: This article describes end-user perceptions and acceptance in relation to the utilization of wireless sensor networks to assist healthcare for older adults. As such, it considers the factors perceived by end-users in real- world deployments. The two factors identified to be most important were cost and the complexity of user interaction with the system. Other factors include the desire for using sensors only during emergencies, rejection of the idea of sensors used for social purposes such as reminders, and concerns over the social implications of being seen to “wear a device.”

• [Experience] EasyLiving: Technologies for Intelligent Environments. 
B. Brumitt, B. Meyers, J. Krumm, A. Kern, and S. Shafer. Handheld and Ubiquitous Computing, pp. 97-119, Springer, 2000. DOI=10.1007/3-540-39959-3_2. 
Summary: This article describes the system required to bring together many diverse I/O devices into a single coherent user experience. It covers each of the components required, including middleware, world modeling, perception, and service description.

• [Experience] Diversity in Smartphone Usage (ACM DL: Free for Members). 
Diversity in Smartphone Usage. H. Falaki, R. Mahajan, S. Kandula, D. Lymberopoulos, R. Govindan, and D. Estrin. 2010. Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys), 2010. DOI=10.1145/1814433.1814453. 
Summary: This article compares the differences in smartphone usage by examining detailed traces of 255 users. Intentional user activities were considered, including interactions with the device and its applications. Among all aspects of use studied, users differed by one or more orders of magnitude. The article also demonstrates the value in adapting to user behavior in the context of a mechanism to predict future smartphone energy consumption.

• [Experience] Experience with Adaptive Mobile Applications in Odyssey (ACM DL: Free for Members). 
B. D. Noble and M. Satyanarayanan. Mobile Networks and Applications, vol. 4, no. 4 (1999). DOI=10.1023/A:1019159101405. 
Summary: This article presents experiences with application-aware adaptation in the context of Odyssey, a platform for mobile data access. Three applications modified to run on Odyssey are described: a video player, a Web browser, and a speech recognition system. The article indicates that it is relatively simple to incorporate applications into Odyssey, and that application source code is not always essential. The work also exposes important areas of future work. Specifically, it reveals the difficulty of balancing agility with stability in adaptation, and emphasizes the need for controlled exposure of internal Odyssey state to users.

SHORT RANGE WIRELESS: RFID, NFC, BLUETOOTH, BANs, and PANs Wireless technologies that only operate over a short range have many applications for mobile computing. "Short range" implies they need to be proximate to respond. An example is Radio Frequency IDentification (RFID), which is designed to identify an object or person in front of a reader, perhaps for access control or inventory management. For these purposes, the proximity constraint is necessary for the information that is determined to have value by a reader (e.g., detecting RFID badges 1m away is useful for access control to a door, but detecting badges 500m away is not). Near-Field Communication (NFC) is a standard that is a subset of RFID technology with added features to allow both reader-to-tag communication and reader-to-reader communication. As a result, it can also be used to facilitate high-bandwidth wireless connections between laptop and mobile computers by sharing a secret channel key across a proximate link (e.g., physically secure). Once the key has been transferred securely, it can be used to set up an additional Bluetooth, or WiFi radio channel. The Bluetooth radio standard was developed by the Bluetooth SIG to enable a short-range Personal Area Network (PAN) that can wirelessly connect all of a person's computing devices (e.g., laptop to phone, mouse, PDA, GPS). This standard has also been adopted by cellular handset developers to support hands-free operation; this is now a requirement in many countries for using cell phones while driving. Another use of short-range radio has been to wirelessly connect medical sensors (placed on the human body) to a small wearable computing hub that can buffer data and then communicate it to a remote hospital server using cellular radio technology. Often, Bluetooth, or Zigbee, is used for the proximate link, but near-field communication has also been adapted for this purpose. Such a network is called a Body Area Network (BAN) or Body Sensor Network (BSN).

• [Overview] An Introduction to RFID Technology. 
Roy Want. IEEE Pervasive Computing, vol. 5, issue 1 (Jan.-March 2006), pp. 25-33. DOI=10.1109/MPRV.2006.2. 
Summary: This article introduces the principles behind RFID, applications of the technology beyond identification, to include sensing, the standards across the various frequency domains (LF, HF, UHF), and the remaining engineering challenges that need to be resolved.

• [Overview] NFC Technical Overview. 
Ian Keen. 2009. 
Summary: A presentation overview of the goals and intended applications of NFC, how it relates to other wireless technologies, the standards it embraces, the protocol architecture, NDEF message types, and current work in progress.

• [Overview] An Overview of the Bluetooth Wireless Technology. 
B. Chatschik. IEEE Communications Magazine, vol. 39, issue12 (Dec. 2001), pp. 86-94. DOI=10.1109/35.968817. Also available at CiteSeer. 
Summary: A high-level description of the Bluetooth protocol architecture and its components. Bluetooth is presented in the context of its beginnings in the Bluetooh SIG (May 1998) and its relationship with other standards such as LANs and WANs. Since the article was written, many new protocol profiles have been added to support new classes of the device; however, the description here underlies each one of them.

• [Overview] Body Sensor Networks. 
G. Yang. Springer, 2006. 
Summary: A book providing a comprehensive overview of body sensor networks based on the pioneering work carried out in this area at Imperial College London. The sections address the key challenges: improved sensor design, bio-compatibility, energy supply and demand, system security and reliability, context-awareness, and integrated therapeutic systems.

• [Overview] Personal Area Networks: Near-Field Intrabody Communication. 
T.G. Zimmerman. IBM Systems Journal, vol. 35, issue 3/4 (1996), pp. 609-612. DOI=10.1147/sj.353.0609. 
Also available at http://dspace.mit.edu/bitstream/handle/1721.1/29101/34289663.pdf. 
Summary: A Master's thesis presenting an intriguing piece of research that shows the potential for building a body area network (BAN) using near-field electrostatic communication to exchange digital information between electronic devices on and near the human body. Because there are no free-space propagated electromagnetic waves, the sensed data also remains on a person, which is desirable for security and medical applications.

Wireless LANs are one of the most widely used network technologies. However, understanding its performance and predicting its behavior under various conditions pose significant research challenges. These challenges motivate researchers to develop models to predict behavior under different usage scenarios, design techniques to optimize WLAN performance, diagnose problems when things go wrong, and measure/analyze how well WLANs work in reality. (See also the section on measurement, below.)

• [System] Architecture and Techniques for Diagnosing Faults in IEEE 802.11 Infrastructure Networks (ACM DL: Free for Members). 
Atul Adya, Paramvir Bahl, Ranveer Chandra, and Lili Qiu. Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom), 2004. DOI=10.1145/1023720.1023724. 
Summary: The first article on diagnosing problems in WLAN networks. It points out several common faults in enterprise networks, such as rogue access points, lack of connectivity, performance problems, and authentication. It describes ways to identify and diagnose the first three problems.

• [System] Jigsaw: Solving the Puzzle of Enterprise 802.11 Analysis (ACM DL: Free for Members). 
Yu-Chung Cheng, John Bellardo, Péter BenköB, Alex C. Snoeren, Geoffrey M. Voelker, and Stefan Savage. Proceedings of the Conference on Applications, Technologies, Architectures, and Protocolsor Computer Communications (SIGCOMM), 2006. DOI=10.1145/1159913.1159920. 
Summary: Jigsaw is a wireless diagnostic tool deployed in a large 802.11 network at UCSD. It uses multiple system monitors to collect traces of the wireless traffic, and then to unify the results. The output is a visualization of system activity across all layers of the stack (physical, link, network, and transport). The authors evaluate their approach using 150 radio monitors deployed throughout a large building on campus, and show how such a tool can be used to diagnose networking problems; see also the “Wit” tool described in the Measurement section below.

• [Experience] Self-Management in Chaotic Wireless Deployments (ACM DL: Free for Members).
Aditya Akella, Glenn Judd, Srinivas Seshan, and Peter Steenkiste. J. Wireless Networks, vol. 13, Issue 6 (Dec. 2007). DOI=10.1007/s11276-006-9852-4. 
Summary: This article observes that Wi-Fi deployments are usually unplanned and unmanaged. It analyzes wireless data on a large scale using data measured from several cities, and finds that Wi-Fi density is high, and the access points are not configured to minimize interference. It points out the need for self-managed Wi-Fi networks that are able to reconfigure, even when deployed in a chaotic fashion.

• [Theory] Performance Analysis of the IEEE 802.11 Distributed Coordination Function. 
G. Bianchi. IEEE Journal on Selected Areas in Communications, vol. 8 (March 2000), pp. 535-547. DOI=10.1109/49.840210. 
Summary: This is one of the first models that accurately predicts throughput in the IEEE 802.11 distributed coordination function when every node is within communication range of each other. Many other articles have built on this work, so be sure to search for papers that cite Bianchi.

• [Theory] A General Model of Wireless Interference (ACM DL: Free for Members). 
Lili Qiu, Yin Zhang, Feng Wang, Mi Kyung Han, and Ratul Mahajan. Proceedings of the Annual ACM International Conference on Mobile Computing and Networking (MobiCom), ACM, 2007. DOI=10.1145/1287853.1287874. 
Summary: This article develops a general model to estimate the throughput and goodput between arbitrary pairs of nodes in the presence of interference from other nodes in a wireless network. It is based on measurement from the underlying network itself. Its distinct features include a model for interference among an arbitrary number of senders (instead of assuming pairwise interference), a model for both broadcast and unicast transmissions, and for unsaturated and heterogeneous traffic, hidden terminals, and multihop transmissions.

Although largely developed in the communication's industry, cellular networks are a key component of any mobile system that requires metropolitan- or national-scale connectivity. Analog (1G) was the base technology of the first cell phones. The first digital systems were called 2nd generation (2G), primarily GSM & Cellular Data Packet Data (CDPD), which operated with low bandwidth (9.6kbps). They were of limited value for mobile computing compared to what was available over a wireless LAN at that time (10Mbps). However, as the various standards have progressed from 2G to 2.5G (GPRS at 48Kbps), to 3G, which provides 384Kbps moving and 2Mbps stationary, and now 4G (long-term evolution (LTE), with the eventual goal of 100Mbps for mobile operation and 1Gbps for stationary), these data rates are now comparable to those available on today's WLANs. Thus, mobile applications that had only been imagined in the early days of mobile systems will soon be possible almost anywhere. The following references provide an overview of cellular technology developments, along with their strengths and weaknesses:

• [Overview] Fundamentals of Cellular Network Planning and Optimization: 2G/2.5G/3G…Evolution to 4G. 
Ajay R. Mishra. Wiley Press, 2004. 
Summary: A good overview of 2G (GSM) in Part I, pp.19-106; 2.5G (GPRS and EDGE) in Part II, pp. 107-146; and 3G in Part III, pp. 147-216. However, 4G is best covered by the Motorola reference, below, describing LTE.

• [Overview] Third Generation (3G) Basics: CDMA-2000 & 3GPP W-CDMA. 
Tim Masson. Wireless Technology Seminar, Feb. 2001. 
Summary: This presentation provides an overview of third-generation (3G) wireless technologies, CDMA2000 and 3GPP, and W-CDMA. It discusses the market drivers behind third-generation cellular communication, the implementation of the technologies, and explains the challenges associated with each one. A comparison highlighting the differences and similarities is presented.

• [Overview] Long-Term Evolution (LTE): A Technical Overview. 
Motorola Inc. 2007, www.motorola.com. 
Summary: LTE is the latest protocol standard for cellular communication, sometimes called 4th generation (4G). It has aggressive performance objectives that rely on physical layer technologies, such as orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) antenna systems. The main goals of LTE are to minimize the system and user equipment (UE) complexity, allow flexible spectrum deployment in existing or new frequency bands, and to enable co-existence with other 3GPP radio access technologies (RATs). LTE is backed by most 3GPP and 3GPP2 service providers.

• [System] MAR: A Commuter Router Infrastructure for the Mobile Internet (ACM DL: Free for Members). 
Pablo Rodriguez, Rajiv Chakravorty, Julian Chesterfield, Ian Pratt and Suman Banerjee.Proceedings of the International Conference on Mobile Systems, Applications, and Services(MobiSys), 2004. DOI=10.1145/990064.990091. 
Summary: MAR is a mobile access router infrastructure that makes use of a variety of handsets, wireless service providers, and wireless channels to exploit the benefits of wireless diversity. A mobile computer can use MAR to select the equipment that can provide the best data throughput at any given time. The research demonstrates the potential improvement in mobile application performance using this system.

• [System] Augmenting Mobile 3G Using WiFi (ACM DL: Free for Members). 
Aruna Balasubramanian, Ratul Mahajan, and Arun Venkataramani. Proceedings of the ACM International Conference on Mobile Systems and Applications, ACM, 2010. DOI=10.1145/1814433.1814456. 
Summary: This article describes a system, called Wiffler, that exploits the current availability of 3G (87%) and WiFi (11%) for mobile devices in a city. Wiffler switches between these radios to reduce 3G traffic where possible, thus reducing costs and aggregate channel utilization. However, if VOIP or other time-sensitive protocols (or applications) are in use, or WiFi becomes unavailable, it rapidly switches back to 3G.

Localization, is the ability of a mobile or stationary device to ascertain its own position; this is a crucial capability for ubiquitous computing as well as mobile and wireless systems. It enables context-aware applications on handheld and portable devices, and is also critical metadata that provides context for data gathered by wireless devices. Location is easily obtained outdoors using GPS, although this may incur a significant energy cost. Work in this area has explored indoor localization systems, or methods to localize nodes and objects when GPS may be unavailable or too expensive to use.

• [System] The Active Badge Location System (ACM DL: Free for Members). 
Roy Want, Andy Hopper, Veronica Falcao, and Jon Gibbons. ACM Transactions on Information Systems, vol. 10, issue 1, (Jan.1993), pp. 91-102. DOI=10.1145/128756.128759. 
Summary: An early article in the field, and one that first demonstrated some of the benefits of ubiquitous computing. The Active Badge project was based on a network of infrared sensors embedded in the environment, and infrared (beaconing) badges on people and mobile objects in order to localize them.

• [System] The Cricket Location-Support System (ACM DL: Free for Members). 
N.B. Priyantha, Anit Chakraborty, and Hari Balakrishnan. 2000. Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom), ACM, 2000. DOI=10.1145/345910.345917. 
Summary: A system based on infrastructural beacons containing a periodic RF signal synchronized with an ultrasonic pulse. A mobile device can determine its distance to the beacon by measuring the time difference between the RF and ultrasonic pulse arriving at its receiver. Triangulating from several beacons provides the mobile device with a relative location.

• [System] The Anatomy of a Context-Aware Application (ACM DL: Free for Members). 
A. Harter, Andy Hopper, Pete Steggles, Andy Ward, and Paul Webster. Proceedings of the Annual ACM/IEEE International Conference on Mobile Computing and Networking. ACM/IEEE, 1999. DOI=10.1145/313451.313476. 
Summary: Badges called BATs generate an ultrasonic pulse after receiving an RF packet from the infrastructure. Several coordinated infrastructural receivers can then measure the relative time when each receiver recorded the pulse, and then calculate their distance to its origin, and through triangulation locate the badge. The system was designed and deployed, and measured location in 3D to about 3cm.

• [System] RADAR: An In-Building RF-Based User Location and Tracking System. 
P. Bahl and V.N. Padmanabhan. Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), IEEE, 2000. DOI=10.1109/INFCOM.2000.832252. 
Also available at http://research.microsoft.com/en-us/um/people/padmanab/papers/
infocom2000.pdf. 
Summary: RADAR builds on a deployment of Wi-Fi access points, without additional infrastructure, to determine the indoor location of a mobile device. This is an attractive location capability with no additional cost; this article describes an implementation using RF-signal strength indication (RSSI) measured from several Wi-Fi access points in order to approximate a location. Although many related solutions have since been proposed, most improving on RADAR; this article remains seminal.

• [System] Place Lab: Device Positioning Using Radio Beacons in the Wild. 
Anthony LaMarca, Yatin Chawathe, Sunny Consolvo, Jeffrey Hightower, Ian Smith, James Scott, Tim Sohn, James Howard, Jeff Huges, Fred Potter, Jason Tabert, Polly Powledge, Gaetano Borriello and Bill Schilit. Pervasive Computing, LNCS 3468, Springer, 2005. 
Summary: Cheap, approximate, positioning can be obtained by listening to WiFi beacons in the wild. This article describes an approach to position estimation using a city-wide (or even national) database of WiFi access points, which later inspired commercial ventures.

• [Theory] Locating the Nodes: Cooperative Localization In Wireless Sensor Networks. 
N. Patwari, J.N. Ash, S. Kyperountas, A.Q. Hero, III, R.L. Moses, and N.S. Correal. Signal Processing Magazine, vol.22, issue 4 (July 2005), pp. 54-69. DOI=10.1109/MSP.2005.1458287. 
Also available at CiteSeer. 
Summary: In sensor networks, nodes may cooperatively localize each other in a peer-to-peer fashion. This survey article discusses the theory and practice underlying this class of localization problem.

• [General] Surroundsense: Mobile Phone Localization via Ambience Fingerprinting (ACM DL: Free for Members). 
Martin Azizyan, Ionut Constandache, and Romit Roy Choudhury. Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom), ACM, 2009. DOI=10.1145/1614320.1614350. 
Summary: Beyond physical location, determining logical location (e.g., the room you are in) is often an important capability for mobile devices; this article explores a method of using fingerprints of ambient sound and light information to achieve this capability.

For some classes of wireless networks, especially sensor networks, data acquisition can be improved by placing synchronized clocks at every node in the network. Often, time synchronization is achieved by explicit message exchanges to communication clock offsets between neighboring nodes, and then algorithmically adjusting those offsets over time to compensate for clock drifts. The following articles describe important additional time synchronization techniques in some detail.

• [System] Fine-Grained Network Time Synchronization Using Reference Broadcasts (ACM DL: Free for Members). 
Jeremy Elson, Lewis Girod, and Deborah Estrin. Proceedings of the Symposium on Operating Systems Design and Implementation (OSDI), ACM, 2002. DOI=10.1145/844128.844143. 
Summary: One of the earliest articles in the field, this work relies on the fact that wireless messages are broadcast in order to perform time synchronization "post-facto"facto (e.g., after an event has occurred).

• [System] The Flooding Time Synchronization Protocol (ACM DL: Free for Members). 
Miklos Maroti, Branislav Kusy, Gyula Simon, and Akos Ledeczi. Proceedings of the International Conference on Embedded Networked Sensor Systems (SenSys), ACM, 2004. DOI=10.1145/1031495.1031501. 
Summary: This work came up with a comprehensive solution to the network-wide time synchronization problem, using ingenious, low-level message time stamping to avoid errors that often bedevil many synchronization protocols.

• [System] Recovering Temporal Integrity with Data Driven Time Synchronization (ACM DL: Free for Members). 
Martin Lukac, Paul Davis, Robert Clayton, and Deborah Estrin. Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN), IEEE, 2009. 
Summary: This work takes a qualitatively different approach, using the events seen in the data itself to adjust timestamps at different nodes.

One of the HCI challenges for mobile computing is providing users with the ability to have an effective mobile user experience while using a small handheld computer such as a smart phone. The scope of this topic is very large, but here we limit it to mobile input, and provide a set of references that cover the research behind stylus and soft keyboard solutions for text input on a mobile handset (smart phone or PDA):

• [System] Touch-Typing with a Stylus (ACM DL: Free for Members). 
David Goldberg and Cate Richardson. Proceedings of the INTERACT '93 and CHI '93 Conference on Human Factors in Computing Systems (INTERCHI), ACM, 1993. DOI=10.1145/169059.169093. 
Summary: This article is about a system called “Unistrokes,” in which every character is written with a single pen stroke, and lifting the pen indicates the character is ready for recogntion. Unistrokes preceded and inspired Palm Pilot's Graffiti, leading to a protracted IP battle between Xerox and Palm. It has a lot of good ideas and rationales for its design. The Unistrokes Alphabet is more efficient, but harder to remember than Graffiti. Graffiti is much more similar to the Latin alphabet, while remaining single stroke (mostly) per letter.

• [System] Shorthand Writing on Stylus Keyboard (ACM DL: Free for Members). 
S. Zhai and P-O. Kristensson. Proceedings of the SIGCHI Conference on Human Factors in Computing (CHI ), ACM, 2003. DOI=10.1145/642611.642630. 
Summary: This is the first article to start the paradigm of using gesture strokes on a keyboard as a way to enter complete words. The article has a sequel by the same authors: SHARK2: a large vocabulary shorthand writing system for pen-based computers, 2004, which presents the fundamentals of algorithms to implement a gesture keyboard, which is now commercialized on many smart phones.

• [Experience] Letterwise: Prefix-Based Disambiguation for Mobile Text Input (ACM DL: Free for Members). 
I. Scott MacKenzie, Hedy Kober, Derek Smith, Terry Jones, and Eugene Skepner. Proceedings of the Annual ACM Symposium on User Interface Software and Technology (UIST). ACM, 2001. DOI=10.1145/502348.502365. 
Summary: A LetterWise centered perspective, this article analyses and compares three approaches to numeric keypad text input: Multitap, Dictionary-based disambiguation (T9, iTap, Zi), and prefix N-gram based disambiguation (LetterWise).

• [Theory] Language Modeling for Soft Keyboards (ACM DL: Free for Members). 
Joshua Goodman, Gina Venolia, Keith Steury, and Chauncey Parker. Proceedings of the International Conference on Intelligent User Interfaces (IUI), 2002, American Association for Artificial Intelligence. DOI=10.1145/502716.502753. 
Summary: This article was the first to introduce formal descriptions of touchscreen keyboard error correction based on the n-gram model, borrowing concepts and methods from speech recognition.

• [General/Theory] Performance optimization of virtual keyboards. 
S. Zhai, M. Hunter and B. A. Smith. Human-Computer Interaction, vol. 17, issue 2/3 (2002), 
pp. 89-129. 
Also available at CiteSeer. 
Summary: This article is the most complete and rigorous treatment of soft keyboard optimization, a topic that produced many papers. However, to date, keyboard optimization has not been adopted by the phone market.

One of the constraints that distinguishes mobile systems from desktop, or server, systems is their reliance on battery technology. This means that energy is limited for a mobile computer, and needs to be used sparingly. As a result, low-power operation has always been a core research area for mobile computing and encompasses the design of hardware, wireless protocols, architecture, operating systems, and user interaction mechanisms. As the world has become more concerned about total energy usage and the green movement has gained momentum, many of the techniques developed for mobile computing are now also being applied to desktop and server systems in order to save energy in both the home and corporate environments. The following articles provide some insight into the creative ways the energy footprint of mobile systems has been reduced by redesigning applications, languages, and devices and by building hybrid wireless technologies and employing energy-scavenging techniques.

• [System (application)] Energy-Aware Adaptation for Mobile Applications (ACM DL: Free for Members). 
Jason Flinn and M. Satyanarayanan. ACM SIGOPS Operating Systems Review, vol. 33, issue 5 (Dec. 1999), pp. 48-63. DOI=10.1145/319344.319155. 
Summary: This article demonstrates that creating a relationship between mobile applications and the mobile operating system can be used to save system power. It describes how applications can be redesigned to be energy-aware, and, in times of abundant energy, give the best user experience–but when it is scarce, put a premium on energy-saving at the cost of a reduced user experience. For example, in the case of a media player, by rendering video at a reduced resolution during playback.

• [System (language)] Eon: A Language and Runtime System for Perpetual Systems (ACM DL: Free for Members). 
Jacob Sorber, Alexander Kostadinov, Matthew Garber, Matthew Brennan, Mark D. Corner, and Emery D. Berger. Proceedings of the International ACM Conference on Embedded Networked Sensor Systems (SenSys), ACM, 2007. DOI=10.1145/1322263.1322279. 
Summary: This article introduces Eon, a programming language and runtime system designed to support the development of perpetual systems. Eon is the first energy-aware programming language, using a declarative coordination language that lets programmers compose programs from components written in C or nesC. Paths through the program (“flows”) may be annotated with different energy states. Eon's automatic energy management then dynamically adapts these states to current and predicted energy levels.

• [System (device)] The Infopad Multimedia Terminal: A Portable Device for Wireless Information Access. 
T. E. Turman, T. Pering, R. Doering, and R.W. Brodersen. IEEE Transactions on Computers, vol. 47, issue 10 (1998),1073-1087,1998. DOI=10.1109/12.729791. 
Summary: InfoPad is an early exploration into a tablet-based, mobile thin-client connected wirelessly to services that could send and receive multimedia content. It was unique in that its custom hardware enabled communication, but the tablet did not support local computation—it was carried out on remote servers. This architecture saved energy, while giving the appearance of unlimited processing performance and storage capacity, at the expense of communication energy costs. The trade-off between processing vs communication power consumption is discussed.

• [System] Wake on Wireless: An Event-Driven Energy Saving Strategy for Battery Operated Devices (ACM DL: Free for Members). 
Eugene Shih, Parmvil Bahl, and Michael Sinclair. Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom), 2002, ACM. DOI=10.1145/570645.570666. 
Summary: The first article to characterize the power saving achieved when using a small low-power radio to wake up a higher-bandwidth, more powerful, radio (e.g., cellular or WiFi) in a mobile device. Wake-on-Wireless is often cited as WoW.

• [System (optimize-wireless)] CoolSpots: Reducing the Power Consumption of Wireless Mobile Devices Using Multiple Radio Interfaces (ACM DL: Free for Members). 
Trevor Pering, Yuvraj Agarwal, Rajesh Gupta, and Roy Want. Proceedings of the International Conference on Mobile Systems, Applications and Services (MobiSys), 2006, ACM. DOI=10.1145/1134680.1134704. 
Summary: The CoolSpot system reduces energy in wireless communication by trading off the different characteristics of Bluetooth and WiFi communication. When both Bluetooth and WiFi are available to a mobile device (a CoolSpot), IP-based communication is switched between a Bluetooth and WiFi channel, depending on the bandwidth needs, while at the same time powering down the unused channel. The results show that by choosing a suitable switching policy for typical network usage, a saving of up to 50% of the energy consumption can be achieved.

• [System (energy-scavenger)] A Wirelessly Powered Platform for Sensing and Computation. 
Joshua R. Smith, Alanson P. Sample, Pauline S. Powledge, Sumit Roy, and Alexander Mamishev. Ubiquitous Computing, LNCS 4206, Springer, Berlin, 2006, pp. 495-506. DOI=10.1007/11853565_29. 
Summary: The ultimate design for a low-power mobile device that scavenges enough ambient energy to execute local applications. This work describes a WISP (WIreless Sensing and Processing) device that harvests energy from an EPCGlobal RFID reader to power a small microcontroller. The processor can then read sensors, perform calculations, and return the result using standard EPCGlobal communication packets.

• [System (protocol)] X-MAC: A Short Preamble MAC Protocol for Duty-Cycled Wireless Sensor Networks (ACM DL: Free for Members). 
M. Buettner, G.V.Yee, E. Anderson, and Richard Han. Proceedings of the International Conference on Embedded Networked Sensor Systems, 2006, ACM. DOI=10.1145/1182807.1182838.

Security and privacy pose unique challenges in mobile computing, because device mobility and personalized usage make it possible to infer personal information from the system's location, or usage patterns. In this section we highlight a few of the many interesting articles in this field, providing examples of security attacks that highlight some of the risks. This article provides an overview of privacy challenges in mobile and ubiquitous computing.

• [Overview] Privacy by Design—Principles of Privacy-Aware Ubiquitous Sytems. 
Marc Langheinrich. Ubiquitous Computing (UbiComp), LNCS 2201, Springer, 2001. DOI=10.1007/3-540-45427-6_23. 
Also available at CiteSeer. 
Summary: This article provides a solid foundation for thinking about privacy in ubiquitous computing systems.

• [System] 802.11 User Fingerprintin (ACM DL: Free for Members). 
Jeffrey Pang, Benjamin Greenstein, Ramakrishna Gummadi, Srinivasan Seshan, and David Wetherall. Proceedings of the International Conference on Mobile Computing and Networking(MobiCom), ACM, 2007. DOI=10.1145/1287853.1287866. 
Summary: The authors demonstrate methods for identifying individual users by observing 802.11 traffic, even if the 802.11 payloads are encrypted, by recognizing various sources of information in the 802.11 frame headers (such as the SSIDs listed in beacon requests).

• [System] Anonymous Usage of Location-Based Services through Spatial and Temporal Cloaking (ACM DL: Free for Members). 
Marco Gruteser and Dirk Grunwald. Proceedings of the International Conference on Mobile Systems, Applications and Services (MobiSys), ACM, 2003. DOI=10.1145/1066116.1189037. 
Summary: One of the original articles providing methods for location anonymity; it provides a solid foundation for the topic. Many new methods have since been proposed, which can be found by tracing the citations of this article forward.

• [Evaluation] Behavioral Detection of Malware on Mobile Handsets (ACM DL: Free for Members). 
A. Bose, X. Hu, K.G. Shin, and T. Park. Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys), ACM, 2008. DOI=10.1145/1378600.1378626. 
Summary: This article proposes a novel behavioral detection framework for mobile worms, viruses, and Trojans based on classifiers that demonstrate more than 96% accuracy. The techniques employed have low overhead for computation time and resources, and are therefore very suitable for use with mobile computers.

• [General] Cracking the Bluetooth PIN (ACM DL: Free for Members). 
Yaniv Shaked and Avishai Wool. Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys), ACM, 2005. DOI=10.1145/1067170.1067176. 
Summary: This article describes a passive attack on Bluetooth to find the PIN used during the pairing process. The authors show that a 4-digit PIN can be cracked in less 0.06 sec on a 3GHz Pentium IV computer. The research shows that the underlying SAFER algorithm, which is based on a 128-bit key, is quite secure, but its realization as a 4-digit human readable PIN makes it vulnerable.

This section includes research that spans disconnected operation, weak connectivity, and conflict resolution. Note this is different from delay tolerant networks (DTNs), as, in this scenario, computers are sometimes directly plugged into a high-bandwidth network connections, but in other situations a computer may intermittently have no connection at all. The articles below describe how mobile systems can usefully continue their work despite these varying conditions:

• [Overview] Replicated Data Management for Mobile Computing. 
Douglas B. Terry. A Morgan & Claypool Synthesis Lecture, 2008. DOI=10.2200/S00132ED1V01Y200807MPC005. 
Summary: A general summary of the area and state-of-the-art techniques developed into systems; also listed in the Book section below.

• [System] Disconnected Operation in the Coda File System. 
James J. Kistler and Mahadev Satyanarayanan. Transactions on Computer Systems, vol. 10, issue 1,(Feb. 1992). DOI=10.1145/146941.146942. 
Summary:This article demonstrates the feasibility of building a file system that provides access to remote files even when disconnected; the Coda file system is described along with measurements to support usability and efficiency. The key idea behind the research is that caching data, which has traditionally been used to enhance performance, can also be exploited to improve availability.

• [System] Bayou: Replicated Database Services for World-Wide Applications (ACM DL: Free for Members). 
K. Petersen, M. J. Spreitzer, D. B.Terry, and M. M.Theimer. Proceedings of the ACM SIGOPS European Workshop: Systems Support for Worldwide Applications (EW 7), ACM, 1996, DOI=10.1145/504450.504497. 
Summary: Bayou is a system and architecture that addresses the database storage needs of mobile applications. In addition to discussing its scalability, availability, extensibility, and adaptability, this article presents Bayou's mechanisms for permitting the replicas of a database to vary dynamically without global coordination. It achieves this through weak consistency replication among autonomous devices, and strict adherence to the tenet that no operation should involve more than two machines.

• [System/Theory] Improving Mobile Dmatabase Access Over Wide-Area Networks Without Degrading Consistency (ACM DL: Free for Members). 
Niraj Tolia, Mahadev Satyanarayanan, and Adam Wolbach. Proceedings of the International Conference on Mobile Systems, Applications and Services (MobiSys), ACM, 2007. DOI=10.1145/1247660.1247672. 
Summary: This article shows how a relational database can be accessed without loss of consistency in a weakly connected mobile environment. A system, called Cedar, as described, enables mobile database access with good performance over low-bandwidth networks. The design, implementation, and validation of Cedar is presented, along with the principle that even a stale client replica can be used to reduce data transmission volume from a database server. For read-write workloads, experiments show that Cedar improves throughput by 39% to 224%, while reducing response time by between 28% and 79%.

• [Experience] Exploiting Weak Connectivity for Mobile File Access (ACM DL: Free for Members).
Lily B. Mummert, Maria Ebling, Mahadev Satyanarayanan. Proceedings of the ACM Symposium on Operating System Principles (SOSP), ACM, 1995. DOI=10.1145/224056.224068. 
Summary: This article describes how the Coda file system has evolved to exploit weak connectivity in the form of intermittent, low-bandwidth, and sometimes expensive plans by a service provider. This has been the environment for mobile computing for many years, although recently with 3G, and now 4G, this is improving. The key ideas presented here to enable mobile file access are cache validation, update propagation, and cache handling.

Wireless mesh networks are becoming a new attractive communication paradigm. Many cities have deployed, or are planning to deploy, them to provide Internet access to homes and businesses. In order to compete with wire-line access technology, routing in wireless mesh network should provide high throughput and reliable performance. This goal has inspired lots of research into developing effective routing protocols for wireless mesh networks. We also include an article on routing using Mobile IP that is representative of the key ideas described in several articles on this subject.

• [Survey] A Survey on Wireless Mesh Networks. 
Ian F. Akyildiz, Xudong Wang, and Weilin Wang. IEEE Communications Magazine, vol. 43, 
issue 9 (Sept. 2005), pp. S23-S30. DOI=10.1109/MCOM.2005.1509968. 
Summary: This article presents architectures for wireless mesh networks. It also surveys physical, MAC, network transport, and application protocols, as well as approaches for network management and security.

• [System] A High-Throughput Path Metric for Multi-Hop Wireless Routin (ACM DL: Free for Members). 
D. S. J. De Couto, Daniel Aguayo, John C. Bicket, and Robert Morris. Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom), ACM, 2003. DOI=10.1145/938985.939000. 
Summary: The article first uses measurements from rooftop networks to show that the shortest hop count does not lead to the best performing routes. It proposes a new routing metric, called ETX, which quantifies the expected number of transmissions required to deliver a packet from the source to the destination, and can be easily computed based on measured link loss rates. ETX has become a widely used routing metric due to its simplicity and effectiveness.

• [System] Mobile Networking through Mobile IP. 
Charles E. Perkins. IEEE Internet Computing, vol. 2, issue 1 (Jan./Feb.1998), pp. 58-69. DOI=10.1109/4236.656077. 
Summary: This article proposes the mobile IP protocol to enable routing of traffic for mobile nodes. A mobile node has a permanent home address and current care-of-address. A node wanting to reach the mobile node first sends traffic to the mobile node's home address; if the mobile is not there, the home agent is responsible for forwarding the traffic to the current care-of-address for the mobile node.

• [Theory] The Capacity of Wireless Networks. 
P. Gupta and P. R. Kumar. IEEE Transactions on Information Theory, vol. 46, issue 2 (March 2000), pp. 388-404. DOI=10.1109/18.825799. Also available at CiteSeer. 
Summary: This article performs asymptotic analysis of wireless network capacity as the number of nodes increase. It concludes that per-node throughput is θ(W/(sqrt(n logn))) under random node placement, where n is the total number of nodes, and each node can transmit W bits per second. Under optimal node placement, the per-node throughput is θ(W/sqrt(n)).

• [Theory] Impact of Interference on Multi-hop Wireless Network Performance (ACM DL: Free for Members). 
Kamal Jain, Jitendra Padhye, Venkata N. Padmanabhan, and Lili Qiu. Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCo), ACM, 2003. DOI=10.1145/938985.938993. 
Summary: This article models wireless interference using a conflict graph and develops methods for computing the upper and lower bounds of the optimal wireless network throughput for a given network topology and specific traffic demands.

Mobile measurement and profiling is a topic of growing importance in the mobile community because significant insights can be obtained by performing measurements at various network locations and on various platforms. This provides visibility into mobile user behavior, mobile traffic characteristics, and mobile application operation. Measurement and profiling research efforts can be roughly categorized on the basis of the vantage point and objectives. Tools deployed on end-hosts, or mobile devices, offer direct insight into user-perceived performance and energy efficiency. Measurement studies based on data collected inside the network can provide aggregate resource usage as well as global traffic patterns. Beyond studies done for 802.11 wireless networks, there is also growing interest in investigating cellular data networks.

• [System] PowerScope: A Tool for Profiling the Energy Usage of Mobile Applications. 
J. Flinn and M. Satyanarayanan. In Proceedings of the IEEE Workshop on Mobile Computing Systems and Applications (WMCSA), IEEE, 1999. DOI=10.1109/MCSA.1999.749272. 
Also see CiteSeer. 
Summary: The article presents one of the first tools to perform detailed profiling of mobile application energy-consumption at the program structure level. By combining software with hardware instrumentation, PowerScope measures power consumption with kernel support to perform statistical sampling of system activity. Follow-up work such as PowerTutor has been developed for performing real-time profiling of android platforms at the system component level.

• [System] Profiling Resource Usage for Mobile Applications: A Cross-layer Approach (ACM DL: Free for Members). 
Feng Qian, Zhaoguang Wang, Alex Gerber, Z. Morley Mao, Subhabrata Sen, and Oliver Spatscheck. Proceedings of the International Conference on Mobile Systems, Applications and Services (MobiSys), ACM, 2011. DOI=10.1145/1999995.2000026. 
Summary: The article describes the design, implementation, and evaluation of the Application Resource Optimizer (ARO) tool. This is the first tool that efficiently and accurately exposes the interaction among various protocol layers, including radio resource channel state, transport layer, application layer, and the user interaction layer to enable the discovery of inefficient resource usage for smartphone applications. Its effectiveness has been validated by identifying energy inefficiency of popular mobile applications such as Pandora and Fox News.

• [Evaluation] Experiences in a 3G Network: Interplay between the Wireless Channel and Applications (ACM DL: Free for Members). 
Xin Liu, Ashwin Sridharan, Sridhar Machiraju, Mukund Seshadri, and Hui Zang. Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom), ACM, 2008. DOI=10.1145/1409944.1409969. 
Summary: This is one of the first measurement studies done by a cellular network carrier focusing on a commercial CDMA 1xEV-DO networks from the perspective of the physical and MAC layers and their impact on TCP performance. This work performed cross-layer analysis to understand potential interactions, and identified the stability of the wireless channel data-rate.

• [Evaluation] The Changing Usage of a Mature Campus-wide Wireless Network. 
Tristan Henderson, David Kotz, and Ilya Abyzov. Computer Networks, vol. 52, issue 14 (Oct, 2008), pp. 2690-2712. DOI=10.1016/j.comnet.2008.05.003. 
Summary: The follow-up work to a previous study by Kotz and Essien (MobiCom 2002) of the first large-scale WiFi network study to detail the usage of a campus-wide wireless network by several thousand users over a few months. This article demonstrates how the workload changed with the emergence of VOIP and P2P communications. This article first appeared in Mobicom 2004, but this journal version is more complete.

• [Evaluation] Analyzing the MAC-level Behavior of Wireless Networks in the Wild (ACM DL: Free for Members). 
Ratul Mahajan, Maya Rodrig, David Wetherall, and John Zahorjan. Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications (SIGCOMM), ACM, 2006. DOI=10.1145/1151659.1159923. 
Summary: This article presents Wit, a powerful tool for studying wireless-network behavior at the 802.11 MAC layer, recognizing the unique challenges of incomplete data, which is inevitable in such traces; see also the Jigsaw article mentioned in an earlier section of the Tech Pack.

• [General] CRAWDAD.org: A community resource for archiving wireless data at Dartmouth. 
Tristan Henderson and David Kotz. 
Summary: CRAWDAD makes dozens of wireless and mobility traces available to researchers. It also links to an extensive collection of wireless-measurement papers.

For many years, virtual machines have been used in data centers to move services between sets of physical machines to provide processor load balancing, while at the same time ensuring secure isolation between services running on the same machine. However, in recent years research has shown the benefit of using virtual machines to support mobile computing. The idea is that a computation can be migrated from a local computer to a remote computer while the user travels between them, thus removing the need to actually carry a computer. Alternatively, computation can be moved from a powerful desktop computer to a mobile smart phone, and then back to a desktop, thus providing seamless access to the same computation environment on the best available hardware at hand. The following articles present various systems that exploit this idea.

• [System] Slingshot: Deploying Stateful Services in Wireless Hotspots (ACM DL: Free for Members). 
Ya-Yunn Su and Jason Flinn. Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys), ACM, 2005. DOI=10.1145/1067170.1067180. 
Summary: Given a high-bandwidth network connection, a handheld computer can run extremely resource-intensive applications by executing the demanding portions of the code on a remote server. Modern WiFi networks could potentially provide this connection, but the backhaul link from the hotspot to the Internet can be a prohibitive bottleneck for interactive applications. To eliminate this bottleneck, this article proposes a new architecture, called Slingshot, that replicates remote application state on surrogate computers co-located with wireless access points.

• [System] Leveraging Smart Phones to Reduce Mobility Footprints (ACM DL: Free for Members). 
S. Smaldone, B. Gilbert, Benjamin, N. Bila, L. Iftode, E. de Lara, and M. Satyanarayanan.Proceedings of the International Conference on Mobile Systems, Applications, and Services(MobiSys), ACM, 2009. DOI=10.1145/1555816.1555828. 
Summary: The ideas behind ISR and Slingshot above assume there is a viable Internet connection near the location where a user wishes to use their computing systems. When there is no connection, Horatio, as described here, serves as a self-cleaning portable cache for VM state, stored in a smart phone. The authors have built an experimental prototype of Horatio, and their measurements confirm its ability to improve the user experience, even when based on today's smart phones. Looking to the future, some smart phones may be built around the Intel Atom architecture, and thus a cached VM on a smart phone can continue executing, making the computation environment continuous, even while mobile.

• [Experience] Pervasive Personal Computing in an Internet Suspend/Resume System. 
M. Satyanarayanan, B. Gilbert, M.Toups, N.Tolia, A. Surie, D.R. O'Hallaron, A. Wolbach, J. Harkes, A. Perrig, D.J. Farber, M.A. Kozuch, C.J. Helfrich, P. Nath, and H.A. Lagar-Cavilla. 
IEEE Internet Computing, vol. 11, issue 2 (March/April 2007). DOI=10.1109/MIC.2007.46. 
Also available at http://isr.cmu.edu/doc/isr-ieee-march-2007.pdf. 
Summary: The Internet suspend/resume model of mobile computing cuts the tight binding between PC state and PC hardware. By layering a virtual machine on distributed storage, ISR lets the VM encapsulate execution and user customization state; then, distributed storage transports that state across space and time. This article explores the implications of ISR for an infrastructure-based approach to mobile computing. It reports on experiences with three versions of ISR and describes work in progress toward the OpenISR version.

• [Theory] The Case for VM-Based Cloudlets in Mobile Computing. 
Mahadev Satyanarayanan, Paramvir Bahl, Ramón Cáceres, and Nigel Davies. IEEE Pervasive Computing, vol.8, issue 4 (Oct./Dec. 2009), pp. 14-23. DOI=10.1109/MPRV.2009.64. 
Also available at http://research.microsoft.com/pubs/102364/cloudlets09.pdf. 
Summary: This article presents a new vision of computing that liberates mobile devices from severe resource constraints by enabling resource-intensive applications to leverage cloud computing, but free of WAN delays, jitter, congestion, and network failures. This is achieved through high-bandwidth wireless access to servers provisioned near to a mobile device in 
active use.

• MobiSys:  www.sigmobile.org/mobisys/
• MobiCom:  www.sigmobile.org/mobicom/
• MobiHoc:  www.sigmobile.org/mobihoc/
• SenSys:  www.sigmobile.org/sensys/
• UbiComp:  www.ubicomp.org
• Pervasive:  www.pervasiveconference.org
• HotMobile:  www.hotmobile.org
• Mobile HCI:  www.mobilehci.org
• PerCom:  www.percom.org

In addition, conferences such as ACM CHI and UIST have mobile computing sessions; 
see ACM SIGCHI (CHI is the premier conference) at www.sigchi.org; see ACM UISTwww.uist.org.

• ACM Mobile Computing and Communication Review (MC2R). www.sigmobile.org
• IEEE Transactions on Mobile Computing (TMC). www.computer.org/tmc/
• IEEE Pervasive Computing Magazine. www.computer.org/pervasive/
• IEEE Wireless Communication Magazine. dl.comsoc.org/wireless/
• Personal and Ubiquitous Computing, Springer, London.
• Pervasive and Mobile Computing, Elsevler, Amsterdam.

• Ubiquitous Computing Fundamentals. John Krumm (ed.), CRC Press, 2010. ISBN: 978-1-4200-9360-5.
• Mobile, Wireless and Sensor Networks: Technology, Applications and Future Directions. Rajeev Shorey et al. (eds.), Wiley Online Library, 2006. DOI=10.1002/0471755591.
• Morgan and Claypool Synthesis Lecture Series on Pervasive Computing
• The Landscape of Pervasive Computing Standards. Sumi Helal, June 2010. Abstract | PDF (3398 KB) | PDF Plus (1460 KB).
• A Practical Guide to Testing Wireless Smartphone Applications. Julian Harty, 2009. Abstract | PDF (4229 KB) | PDF Plus (1485 KB).
• Location Systems: An Introduction to the Technology Behind Location Awareness. Anthony LaMarca, Eyal de Lara, 2008. Abstract | PDF (9651 KB) | PDF Plus (3103KB).
• Replicated Data Management for Mobile Computing. Douglas B. Terry, 2008, Abstract | PDF (1619 KB) | PDF Plus (959 KB).
• Application Design for Wearable Computing. Dan Siewiorek, Asim Smailagic, Thad Starner, 2008, Abstract | PDF (4260 KB) | PDF Plus (1313 KB).
• Controlling Energy Demand in Mobile Computing Systems. Carla Schlatter Ellis, 2007, Abstract | PDF (1588 KB) | PDF Plus (983 KB).
• RFID Explained: A Primer on Radio Frequency Identification Technologies. Roy Want, 2006, Abstract | PDF (11087 KB) | PDF Plus (2064 KB).

• K.L. Eddie Lawa, Wing-Chung Hung, "Engineering TCP transmission and retransmission mechanisms for wireless networks", Pervasive and Mobile Computing, Article in Press, law_eng_tcp.pdf, PMC site

• Rajput at. al, "Evaluating Mobile Phone Handoff Behavior using Chi-square Statistical Test", Southeastcon, 2008. IEEE PDF

• Jung Woo Lee, Branislav Kusy, Basem Shihada, Tahir Azim, Philip Levis, "Whirlpool Routing for Mobility", MobiCom 2010, PDF

• Aaron Schulman, Vishnu Navda, Ramachandran Ramjee, Neil Spring, "Bartendr: A Practical Approach to Energy-aware Cellular Data Scheduling", MobiCom 2010, PDF PPT Tutorial for measuring energy of mobile phones

• ♠ Tingting Sun, Wade Trappe, Yanyong Zhang, "Improved AP association management using machine learning", MC2R 2010, Site

• Fahad R. Dogar, Peter Steenkiste (Carnegie Mellon University), Konstantina Papagiannaki (Intel Laboratories), "Catnap: Exploiting High Bandwidth Wireless Interfaces to Save Energy for Mobile Devices", PDF

• Moo-Ryong Ra, Jeongyeup Paek, Abhishek B. Sharma, "Energy-Delay Tradeoffs in Smartphone Applications", MobiSys 2010, PDF

• Lane, N.D., Miluzzo, E., Hong Lu, Peebles, D., Choudhury, T., Campbell, A.T., "A survey of mobile phone sensing", IEEE Communications Magazine, 2010, Volume 48, Issue 9, pages 140 - 150, PDF

• Donnie H. Kim, Younghun Kim, Deborah Estrin, Mani B. Srivastava, "SensLoc: Sensing Everyday Places and Paths using Less Energy", SenSys 2010, PDF

• Jeongyeup Paek Joongheon Kim Ramesh Govinda, "Energy-Efficient Rate-Adaptive GPS-based Positioning

for Smartphones", MobiSys 2010, PDF

• Tathagata Das (Microsoft Research India), Prashanth Mohan (University of California, Berkeley), Venkata N. Padmanabhan, Ramachandran Ramjee (Microsoft Research India), Asankhaya Sharma, "PRISM: Platform for Remote Sensing using Smartphones", MobiSys 2010, PDF

• Tingxin Yan, Vikas Kumar, Deepak Ganesan, "CrowdSearch: Exploiting Crowds for Accurate Real-time Image Search on Mobile Phones", MobiSys 2010, PDF

• Suhas Mathur, Tong Jin, Nikhil Kasturirangan, Janani Chandrashekharan, "ParkNet: Drive-by Sensing of Road-Side Parking Statistics",PDF

• Rijurekha Sen, Bhaskaran Raman and Prashima Sharma, "Horn-Ok-Please", MobiSys 2010, PDF PPT Video

• Raghu K. Ganti, Nam Pham, Hossein Ahmadi, Saurabh Nangia, and Tarek F. Abdelzaher, "GreenGPS: A Participatory Sensing Fuel-Efficient Maps

Application", MobiSys 2010, PDF

• Jun Yang, Zhigang Liu, Hong Lu, Nicholas Lane, Choudhury Tanzeem, Campbell Andrew, "The Jigsaw Continuous Sensing Engine for Mobile Phone Applications", Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, ACM, New York (2010)

• Ling Bao and Stephen S. Intille, "Activity Recognition from User-Annotated Acceleration Data", PERVASIVE 2004

• Andrea Mannini and Angelo Maria Sabatini, "Machine Learning Methods for Classifying Human Physical Activity from On-Body Accelerometers", Sensors 2010, 10(2), 1154-1175

• Jennifer R. Kwapisz, Gary M. Weiss, Samuel A. Moore, "Activity Recognition using Cell Phone Accelerometers", SensorKDD ’10, July 25, 2010, Washington, DC, USA.

• Min Mun, Sasank Reddy, Katie Shilton, Nathan Yau, Peter Boday, Jeff Burke, Deborah Estrin, Mark Hansen, Eric Howard, Ruth West, "PEIR, the Personal Environmental Impact Report, as a Platform for Participatory Sensing Systems Research", MobiSys '09

• Danny Wyatt, Matthai Philipose and Tanzeem Choudhury, "Unsupervised Activity Recognition Using Automatically Mined Common Sense", AAAI'05

• Daniel Peebles and Hong Lu and Nicholas D. Lane and Tanzeem Choudhury and Andrew T. Campbell, "Community-Guided Learning: Exploiting Mobile Sensor Users to Model Human Behavior", PDF

• Emiliano Miluzzo, Cory T. Cornelius, Ashwin Ramaswamy, Tanzeem Choudhury, Zhigang Liu, Andrew T. Campbell, "Darwin Phones: The Evolution of Sensing and Inference on Mobile Phones", MobiSys '10, San Francisco, CA, USA, June 15-18, 2010, PDF

• Mining Individual Life Pattern Based on Location History, by Yang Ye et. al (Tsinghua U, Microsoft) PPT PDF

• Lin Liao a, Donald J. Patterson b, Dieter Fox a, Henry Kautz a, "Learning and Inferring Transportation Routines", Journal of Artificial Intelligence, Volume 171, Issue 5-6, April, 2007

• Ling Chen, Mingqi Lv, Gencai Chen, "A system for destination and future route prediction based on trajectory mining", Pervasive and Mobile Computing, Volume 6, Issue 6, 657-676, 2010

• Yu Zheng and Xing Xie, "Mining Individual Life Pattern Based on Location History", MDM 2009 PPT PDF

• Murat Ali Bayir, Murat Demirbas, Nathan Eagle, "Mobility profiler: A framework for discovering mobility profiles of cell phone users", Pervasive and Mobile Computing, Volume 6, Issue 4, August 2010, Pages 435-454, PDF

• ★ Wei Gao and Guohong Cao, "Fine-Grained Mobility Characterization: Steady and Transient State Behaviors", MobiHoc 2010, PDf

• D.J. Patterson, L. Liao, D. Fox, and H. Kautz. , "Inferring High-Level Behavior from Low-Level Sensors", Ubicomp2003

• Mikko Perttunen, Jukka Riekki, and Ora Lassila, "Context Representation and Reasoning in Pervasive Computing: a Review", International Journal of Multimedia and Ubiquitous Engineering, Vol. 4, No. 4, October, 2009 http://www.sersc.org/journals/IJMUE/vol4_no4_2009/1.pdf

• Yun Her, Su-Kyoung Kim, YoungTaek Jin, "A Context-Aware Framework using Ontology for Smart Phone Platform", International Journal of Digital Content Technology and its Applications, Volume 4, Number 5, August, 2010 PDF

• Collin Mulliner, "Privacy Leaks in Mobile Phone Internet Access", Intelligence in Next Generation Networks (ICIN), 2010 14th International Conference on PDF

• ★★ Sudarshan Vasudevan, Dennis Goeckel, Don Towsley, "Security-Capacity Trade-off in Large Wireless Networks Using Keyless Secrecy", MobiHoc 2010, PDF

• ♠ "How Much is Location Privacy Worth?" by George Danezis, Stephen Lewis and Ross Anderson PDF

• Janice Y. Tsai , Patrick Gage Kelley , Lorrie Faith Cranor , Norman Sadeh, "Location-sharing technologies: Privacy risks and controls", In Research Conference on Communication, Information and Internet Policy (TPRC) http://cups.cs.cmu.edu/LBSprivacy/files/TsaiKelleyCranorSadeh_2009.pdf

• Tanzima Hashem, Lars Kulik, "“Don’t trust anyone”: Privacy protection for location-based services ", Pervasive and Mobile Computing, Volume 7, Issue 1, February 2011, Pages 44-59, PMC site

• Raluca Ada Popa, Hari Balakrishnan, Andrew Blumberg, VPriv: Protecting Privacy in Location-Based Vehicular Services, 18th USENIX Security Symposium, Montreal, Canada, August 2009, PDF

• Baik Hoh, Marco Gruteser, "Virtual Trip Lines for Distributed Privacy-Preserving Traffic Monitoring", International Conference on Mobile Systems, Applications, and Services (MOBISYS), June 17-18, Brekenridge, CO, PDF

• Chris Y. T. Ma, David K. Y. Yau, Nung Kwan Yip, Nageswara S. V. Rao, "Privacy Vulnerability of Published Anonymous Mobility Traces", MobiCom 2010, PDF

• Hossein Ahmadi, Nam Pham, Raghu Ganti, Tarek Abdelzaher, Suman Nath, Jiawei Han, "Privacy-aware Regression Modeling of Participatory Sensing Data", Sensys 2010, PDF

• Aaron Beach, Mike Gartrell, Richard Han, "Social-K: Real-Time K-Anonymity Guarantees for Social Network Applications", SESOC 2010, PDF

• ♠ Ioannis Krontiris, Felix C. Freiling, "Integrating people-centric sensing with social networks: A privacy research agenda", SESOC 2010, PDF

• Jiangpeng Dai, Xiaole Bai, Zhimin Yang, Zhaohui Shen, Dong Xuan (The Ohio State University), "PerFallD: A Pervasive Fall Detection System Using Mobile Phones", PerHealth 2010, PDF

• Simon Hay, Alastair R. Beresford (University of Cambridge), "Estimating personal energy expenditure with location data", PerHealth 2010, PDF Slides

• Dae-Ki Cho, Min Mun, Williams J. Kaiser, Mario Gerla (University of California at Los Angeles, USA), Uichin Lee (Bell Labs, Alcatel-Lucent, USA), "AutoGait: A Mobile Platform that Accurately Estimates the Distance Walked", PerCom 2010, PDF

• Arvind Thiagarajan, Lenin Ravindranath, Katrina LaCurts, Sivan Toledo Jakob Eriksson, "VTrack: Accurate, Energy-Aware Road Traffic Delay Estimation Using Mobile Phones", SenSys’09, November 4–6, 2009, Berkeley, CA, USA, PDF

• M. Raya, P. Papadimitratos, I. Aad, D. Jungels, and J.-P. Hubaux, "Eviction of Misbehaving and Faulty Nodes in Vehicular Networks", IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 25, NO. 8, OCTOBER 2007, PDF

• Herrera at. al, "Evaluation of Traffic Data Obtained via GPS-enabled Mobile Phones: the Mobile Century field experiment", Transportation Research, PDF

• Hua Qin, Zi Li, Yanfei Wang, Xuejia Lu and Wensheng Zhang, Guiling Wang, An Integrated Network of Roadside Sensors and Vehicles for Driving Safety: Concept, Design and Experiments, PerCom 2010, PDF

• Andrew Rice, Simon Hay, "Measuring mobile phone energy consumption for 802.11 wireless networking", PMC 2010, Vol 6

• Ionut Constandache, Xuan Bao, Martin Azizyan, Romit Roy Choudhury, "Did You See Bob?: Human Localization using Mobile Phones", MobiCom 2010, PDF

• Andrew T. Campbell, Tanzeem Choudhury, Shaohan Hu, Hong Lu, Matthew K. Mukerjee, Mashfiqui Rabbi, Rajeev D. S. Raizada, "NeuroPhone: Brain-Mobile Phone Interface using a Wireless EEG Headset", in Proc. of The Second ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds (MobiHeld'10), New Delhi, India, August 30, 2010, PDF, Video

• Emiliano Miluzzo, Tianyu Wang, Andrew T. Campbell, "EyePhone: Activating Mobile Phones With Your Eyes". To appear in Proc. of The Second ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds (MobiHeld'10), New Delhi, India, August 30, 2010. PDF Video

• ♠ A Configurable Approach to Privacy Ontology and its Application to Mobile e-Health Services PPT

• Arvind Thiagarajan James Biagioni Tomas Gerlich Jakob Eriksson, "Cooperative Transit Tracking using Smart-phones", SenSys 2010

PDF

• Hossein Falaki (University of California, Los Angeles), Ratul Mahajan, Srikanth Kandula, Dimitrios Lymberopoulos (Microsoft Research), Ramesh Govindan (University of Southern California), Deborah Estrin (University of California, Los Angeles), "Diversity in Smartphone Usage", PDF

• Andre Kalamandeen, Adin Scannell, Eyal de Lara (University of Toronto), Anmol Sheth, Anthony LaMarca (Intel Research Seattle), "Ensemble: Cooperative Proximity-based Authentication", MobiSys 2010, PDF

• Krishna P. N. Puttaswamy, Catherine C. Marshall, Venugopalan Ramasubramanian, Patrick Stuedi, Douglas B. Terry, Ted Wobber (Microsoft Research Silicon Valley), "Docx2Go: Collaborative Editing of Fidelity Reduced Documents on Mobile Devices", MobiSys 2010, PDF

• Xuan Bao, Romit Roy Choudhury (Duke University), "MoVi: Mobile Phone Based Video Highlights Via Collaborative Sensing", PDF