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Research Projects in the Mobile Computing and Networking (MCN) Lab

Research Projects in the Mobile Computing and Networking (MCN) Lab. Guohong Cao Department of Computer Science and Engineering The Pennsylvania State University http://www.cse.psu.edu/~gcao. Mobile Computing and Networking (MCN) Lab.

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Research Projects in the Mobile Computing and Networking (MCN) Lab

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  1. Research Projects in the Mobile Computing and Networking (MCN) Lab Guohong Cao Department of Computer Science and Engineering The Pennsylvania State University http://www.cse.psu.edu/~gcao

  2. Mobile Computing and Networking (MCN) Lab • MCN lab conducts research in many areas of wireless networks and mobile computing, emphasis on designing and evaluating mobile systems, protocols, and applications. • Current Projects: smartphones, wireless network security, data dissemination/access in wireless P2P networks, vehicular networks, wireless sensor networks, resource management in wireless networks. • Support: NSF (CAREER, ITR, NeTS, NOSS, CT, CNS), Army Research Office, NIH, DoD/Muri, DoD/DTRA, PDG/TTC and member companies Cisco, Narus, Telcordia, IBM and 3ETI. • Current students: • 10 PhD students • 1 PostDoc • 3 visiting scholars

  3. Alumni • 15 PhDs • Hao Zhu (8/2004), Qualcomm. • Liangzhong Yin (12/2004), Microsoft. • Wensheng Zhang (8/2005), Associate Professor, Iowa State University • Hui Song (8/2007), Assistant Professor, Frostburg State University • Jing Zhao (8/2008), Cisco Systems. • Min Shao (12/2008), Microsoft • Changlei Liu (5/2010), UMUC • Yang Zhang (2/2011), Palo Alto Networks. • BaojunQiu (Co-chaired with J. Yen) 8/2011, eBay. • Bo Zhao (10/2011), AT&T. • Zhichao Zhu (2/2012), Nokia. • QiangZheng (5/2012), Google • Wei Gao (5/2012), Assistant Professor, University of Tennessee. • Qinghua Li (5/2013), Assistant Professor, University of Arkansas. • Yi Wang (5/2013), Google. • 12 MS students went to various companies • 5 visiting scholars

  4. Outline • Efficient Energy-Aware Web Access in Wireless Networks • Social-Aware Data Dissemination in Delay Tolerant Networks • Resilient and Efficient Data Access in Cognitive Radio Networks • Privacy-Aware Mobile Sensing

  5. Web Browsing in 3G/4G Networks • Smartphones in 3G/4G networks: • Increasingly used to access the Internet • Consume more power • Cellular interface consumes lots of energy • 30%-50% of total energy • Current status: • 3G/4G radio interface always on, timer control • Radio resource is not released, reduce network capacity

  6. T1 = 4 sec T2 = 15 sec Characteristics of 3G Radio interface

  7. Traffic Load of Opening Webpages Radio interface is always on during data transmission

  8. Reorder the Computation Sequence • Reorganize the computation sequence of the web browser, so that it first runs the computations that will generate new data transmissions and retrieve these data from the web server. • Then, the web browser can put the 3G radio interface into low power state, and then run the remaining computations.

  9. Reducing the Energy of FACH State • After a webpage is downloaded, predict the user reading time on the webpage • This time > a threshold (delay vs. power): switch into low power state • Prediction is based on Gradient Boosted Regression Trees (GBRT). • Selected 10 features such as Data transmission time, webpage data size, figure size, no. of downloaded objects, etc. • Also consider user interest.

  10. Evaluations • The prototype: • Android Phones • T-Mobile 3G/UMTS network • Implement the prototype and collect real traces • Experimental results: • Reduce power consumption: 30% • Reduce loading time: 17% • Increase network capacity: 19%

  11. Motivation Tail Power Power Power Power Power Data transmission t t t t t Tail Promotion How to reduce tail energy and promotion delay?

  12. Basic idea Power Power Power Power • Aggregation traffics on one node (proxy) • How? An optimization problem. • Forward via P2P (Bluetooth or WiFi direct) t t t t Power P2P interface t Proxy

  13. Testbed Results • Total energy saving rate: 30.4% • Average delay reducing rate: 31%

  14. Outline • Efficient Energy-Aware Web Access in Wireless Networks • Social-Aware Data Dissemination in Delay Tolerant Networks • Resilient and Efficient Data Access in Cognitive Radio Networks • Privacy-Aware Mobile Sensing

  15. Data Dissemination in DTNs • Lack of infrastructure support in disaster recovery, battlefield, environmental monitoring, etc. • Mobile devices can form mobile opportunistic networks or Disruption Tolerant Networks (DTN). • General methodology: Carry-and-forward • The key issue is to select which node (relay) to forward the data. Japan tsunami 2010

  16. Social-Aware Data Dissemination • Exploiting social relations among mobile nodes for relay selections • Stable long-term characteristics compared to node mobility • Centrality (Degree or betweenness), which shows the importance of some nodes to help communications among other nodes. • High centrality nodes can be used as relay nodes. • Community, i.e., nodes have common acquaintances have higher probabilities to know each other. • data can reach the destination easier if it reaches someone in the same social community as the destination.

  17. Our Results • Social interest: User-Centric Data Dissemination in Disruption Tolerant Networks (infocom’11) • Social Contact Patterns: On Exploiting Social Contact Patterns for Data Forwarding in Delay Tolerant Networks (icnp’10, TMC’13) • Social selfishness: Routing in socially selfish disruption tolerant networks (infocom’10, Adhoc’12) • Social-aware caching: Supporting Cooperative Caching in Disruption Tolerant Networks (icdcs’11, icdcs’12, TMC’13) • Social relationship: Social-Aware Data Diffusion in Delay Tolerant MANETs (book chapter’12) • Social-aware multicast: Social-aware Multicast in Disruption Tolerant Networks (Mobihoc’09, ToN’12)

  18. Social Interest • System development: recording users’ interests • Data access via Samsung Nexus S smartphones • Categorized web news from CNN • Application scenarios • Public commute systems: bus, subway • Public event sites: stadium, shopping mall • Disaster recovery • Android webpage XML format phone display

  19. Social Interest • User interests: dynamically updated by users’ activities • System execution • 30 users at Penn State, 5-month period • 11 categories, 306,914 transceived, 40, 872 read by users A Contact C B

  20. Social Contact • 802.15.4/ZigBee compliant • 10kB RAM, 250kbps data rate • TinyOS 2.0 • System development • Testbed: TelosB sensors • Deployment: 1000+ sensors distributed to high school students • Heterogeneity of centrality, community, high cluster coefficient • Flu immunization B A C

  21. Outline • Efficient Energy-Aware Web Access in Wireless Networks • Social-Aware Data Dissemination in Delay Tolerant Networks • Resilient and Efficient Data Access in Cognitive Radio Networks • Privacy-Aware Mobile Sensing

  22. Emergence of Cognitive Radio • Unlicensed use of licensed spectrum is approved by government agencies • Cognitive radio – dynamically configure the operating spectrum

  23. Cognitive Radio Networks • Dynamic spectrum access • Must avoid interference with primary users (licensed users) • With infrastructure / without infrastructure (ad-hoc)

  24. Our Work

  25. Data Caching • No caching • Caching (delay is statistically bounded)

  26. Outline • Efficient Energy-Aware Web Access in Wireless Networks • Social-Aware Data Dissemination in Delay Tolerant Networks • Resilient and Efficient Data Access in Cognitive Radio Networks • Privacy-Aware Mobile Sensing

  27. Proliferation of Mobile Devices • Mobile devices • Smartphone, tablet, vehicle, medical device, pollution sensor • Sensing capabilities • Camera, microphone, accelerometer, GPS • Communication capabilities • 3G/4G, WiFi, Bluetooth A huge opportunity for mobile sensing

  28. Obstacles in Collecting Sensing Data • Privacy concern • Location, activity, health • <location, noise> • <amount of exercise> • Cost of participation • Power, bandwidth, human attention • Lack of network connectivity • Devices without comms infrastructure (e.g., 3G) • Circumstances of unavailable or cost-inefficient infrastructure

  29. Research Summary • Solutions Privacy-aware incentive Privacy-aware aggregation Secure opportunistic mobile networking More data collected from more users • Privacy-aware incentives [PerCom’13] [ICNP’12,PETS’13] [Infocom’10]: selfishness [TDSC’13]: flood attack More data collected from more devices [TIFS’12]: drop attack

  30. Summary • Efficient energy-aware web access in wireless networks • reducing the power consumption of smartphones by dealing with the special characteristic of the 3G/4G radio interface • Social-aware data dissemination in delay tolerant networks • Exploiting the knowledge of social contact patterns, social interests, and social relationships. • Two testbeds for data collection. • Resilient and efficient data access in cognitive radio networks • mitigating the effects of primary user appearance • Privacy-aware mobile sensing

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