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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 sensor networks, vehicular networks, wireless network security, data dissemination/access in wireless P2P 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, 1 MS, and 2 visiting scholars • Alumni: 11 PhD, including faculty members at Iowa State University, University of Tennessee, Frostburg State University, and students in Qualcomm, Cisco, Microsoft. • 12 MS students went to various companies

  3. Outline • Efficient Energy-Aware Web Browsing in Wireless Networks • In-Network Storage

  4. Web Browsing in 3G Networks • Smartphones in 3G networks: • Increasingly used to access the Internet • Consume more power • Current status: • Limited computation capability, data transmission distributed whole loading time • 3G radio interface always on, timer control • Radio resource is not released, reduce network capacity

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

  6. Latency Power Intuitive Approach Whether to switch DCH->IDLE: Need predict next interval

  7. Our Solution • Reorganize the computation sequence of the web browser when loading a web page. • First run the computations that will generate new data transmissions. • 3G radio interface into low power state, release the radio resource • Then run the remaining computations • After a webpage is downloaded, predict the user reading time on the webpage (Gradient Boosted Regression Trees (GBRT) • This time > a threshold: switch into low power state

  8. 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%

  9. Computation Limitation

  10. VM-based Proxy • The prototype: • Xen virtual machines • Android Phones • UMTS network • Experiment Result: • Reduces the delay by 60% • Reduces the power by 35%.

  11. Outline • Efficient Energy-Aware Web Browsing in Wireless Networks • In-Network Storage • Social-Aware Data Dissemination in Mobile Opportunistic Networks • Cooperative caching in MANET

  12. Data Dissemination in Mobile Opportunistic Networks • System development: recording users’ interests • Data access via Samsung Nexus S smartphones • Categorized web news from CNN • Application scenarios • Disaster recovery, military environment • Public commute systems: bus, subway • Public event sites: stadium, shopping mall • Android 2.3.3 webpage XML format phone display

  13. Social Interest • User interests: dynamically updated by users’ activities • System execution • 20 users at Penn State, 5-month period • 11 categories, 86,914 transceived, 25, 872 read by users A Contact C B

  14. Caching in Mobile Ad Hoc Networks • In Battlefield, mobile devices of the soldiers form a MANET. • After a soldier obtains enemy information (e.g., battlefield map, enemy distribution) from the commander (data center), it is very likely that nearly soldiers also need the same information. • Bandwidth and power can be saved if these data accesses are served by the soldier with the cached data instead of the data center which may be far away.

  15. CachePath: Cache the data path • Suppose N1 has requested a data item from N11. N3 knows that N1 has the data. Later if N2 requests for the data, it forwards the request to N1 instead of N11. • CacheData: Cache the data • In the above example, N3 caches the data, and forwards the data to N2 directly. • Many technical issues not shown here

  16. 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

  17. Other Projects • Efficient Energy-Aware Web Browsing in Wireless Networks • In-Network Storage • Security in Cellular Networks • Z. Zhu, G. Cao, S. Zhu, S. Ranjan, A. Nucci, "A Social Network Based Patching Scheme for Worm Containment in Cellular Networks," IEEE INFOCOM, 2009. • B. Zhao, C. Chi, W. Gao, S. Zhu, G. Cao, "A Chain Reaction DoS Attack on 3G Networks: Analysis and Defenses," IEEE INFOCOM, 2009. • Z. Zhu and G. Cao, "APPLAUS: A Privacy-Preserving Location Proof Updating System for Location-based Services," IEEE Infocom, 2011. • Data Dissemination in Vehicular Ad Hoc Networks

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