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

• 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

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Outline

• Efficient Energy-Aware Web Browsing in Wireless Networks

• In-Network Storage

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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

Characteristics of 3G Radio interface

T2 = 15 sec

T1 = 4 sec

Intuitive Approach

Whether to switch DCH->IDLE: Need predict next interval

Power

Latency

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

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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%

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Computation Limitation

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VM-based Proxy

• The prototype:– Xen virtual machines– Android Phones– UMTS network

• Experiment Result:– Reduces the delay by 60%– Reduces the power by 35%.

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Outline

• Efficient Energy-Aware Web Browsing in Wireless Networks

• In-Network Storage– Social-Aware Data Dissemination in Mobile

Opportunistic Networks

– Cooperative caching in MANET

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

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

Contact

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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.

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• 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

Social Contact

• System development– Testbed: TelosB sensors

– Deployment: 1000+ sensors distributed to high school students

• Heterogeneity of centrality, community, high cluster coefficient

• Flu immunization

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802.15.4/ZigBee compliant10kB RAM, 250kbps data rateTinyOS 2.0

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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