Paper list for “Hot Topics on Computer Network Research” 2014
Introduction of Wireless Networks
1.
Lonut Constandache, Romit Roy Choudhury, Injong Rhee: Towards Mobile Phone Localization without War-Driving.
INFOCOM 2010: 2321-2329.
2.
Jay Chen, Lakshminarayanan Subramanian, Eric A. Brewer: SMS-based web search for low-end mobile devices. MOBICOM
2010: 125-136
3.
Martin Azizyan, Ionut Constandache, Romit Roy Choudhury: SurroundSense: mobile phone localization via ambience
fingerprinting. MOBICOM 2009: 261-272
4.
Aaron Carroll, Gernot Heiser, An Analysis of Power Consumption in a Smartphone, USENIX technical conference,
Boston, MA, USA Month: Jun Year: 2010
Ch1 Wireless cellular systems (GSM, CDMA, UMTS)
1.
Keralapura, R., Nucci, A., Zhang, Z., and Gao, L. Profiling users in a 3g network using hourglass co-clustering. In
Proceedings of MOBICOM. 2010, 341-352
2.
Chunyi Peng, Suk-Bok Lee, Songwu Lu, Haiyun Luo, Hewu Li, Traffic-Driven Power Saving in Operational 3G Networks,
Mobicom'11, Sep 2011. (acceptance rate: 29/214 = 13.5%)
3.
M. Zubair Shafiq, Lusheng Ji, Alex X. Liu, Jeffrey Pang, and Jia Wang, A First Look at Cellular Machine-to-Machine Traffic
- Large Scale Measurement and Characterization in Proceedings of the ACM International Conference on Measurement and
Modeling of Computer Systems (SIGMETRICS), pages 65-76, London, United Kingdom, June 2012..
Ch2 Wireless LANs and MAC layer protocols (802.11, Bluetooth, ZigBee)
1.
Amitabha Ghosh, Rittwik Jana, V. Ramaswami, Jim Rowland, and N. K. Shankaranarayanan Modeling and
Characterization of Large-Scale Wi-Fi Traffic in Public Hot-Spots, INFOCOM 2011 (accepted), Shanghai, China, April
2011
2.
References: M. S. A. Mishra and W. Arbaugh. An Empirical analysis of the IEEE 802.11 MAC Layer Handoff. Process,
UMIACS Tech. Report TR-2002-75
3.
A. Balasubramanian, R. Mahajan, A. Venkataramani, B. N. Levine, and J. Zahorjan, Interactive WiFi Connectivity For
Moving Vehicles. In. Proc. of ACM SIGCOMM, Sept. 2008
4.
Xi Chen and Daji Qiao, "HaND: Fast Handoff with Null Dwell Time for IEEE 802.11 Networks,", IEEE INFOCOM 2010,
San Diego, CA, Mar. 2010
5.
C.-J. M. Liang, B. Priyantha, J. Liu, A. Terzis, Surviving Wi-Fi Interference in Low Power ZigBee Networks , SenSys
2010
6.
R. Zhou, Y. Xiong, G. Xing, L. Sun, and J. Ma, ZiFi: wireless LAN discovery via ZigBee interference signatures, in Proc.
MOBICOM, 2010, pp.49-60.
7.
Hao Han, Yunxin Liu, Guobin Shen, Yongguang Zhang, and Qun Li. DozyAP: Power-Efficient Wi-Fi Tethering, The 10th
International Conference on Mobile Systems, Applications, and Services, Low Wood Bay, UK, June 2012.
Ch3
3-1 Ad Hoc Routing (7/15)
3-1-1 Geo-routing, Motion assisted routing，Direction Forwarding, Opportunistic Routing
1.
J.Lee, B. Kusy, T. Azim, B. Shihada and P. Levis, "Whirlpool Routing for Mobility," in Proceedings of ACM
MobiHoc, Chicago, IL, USA, 2010.
2.
Kebin Liu, Mo Li, Yunhao Liu, Xiang-Yang Li, Minglu Li, Huadong Ma, "Exploring the Hidden Connectivity in
Urban Vehicular Networks", Proceedings of IEEE ICNP 2010.
3.
B. Cheng, M. Yuksel, and S. Kalyanaraman, Orthogonal Rendezvous Routing Protocol for Wireless Mesh Networks,
Proceedings of IEEE ICNP 2006.
4.
Chen Qian and Simon S. Lam, ``Greedy Distance Vector Routing,'' in Proceedings of The 31st International
Conference on Distributed Computing Systems (IEEE ICDCS), Minneapolis, Minnesota, 2011.
5.
G. Tan, Z. Yin, and H. Jiang. Trap Array: A Unified Model for Scalability Evaluation of Geometric Routing. In
Proceedings of ACM SIGMETRICS, 2013
3-2 Multicast and network coding
1. R. Chandra, S. Karanth, T. Moscibroda, V. Navda, J. Padhye, R. Ramjee, and L. Ravindranath, "DirCast:
A Practical and Efficient Wi-Fi Multicast System" ICNP2009
2.
3-3 Wireless Ad Hoc TCP (5/7)
Ch4 Sensor networks
4-1 Introduction and applications:
1.
Jiakang Lu, Tamim Sookoor, Vijay Srinivasan, Ge Gao, Brian Holben, John Stankovic, Eric Field and Kamin
Whitehouse, The Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes, 8th ACM
Conference on Embedded Networked Sensor Systems (SenSys'10), November 2010.
2.
Lenin S. Ravindranath and Calvin Newport and Hari Balakrishnan and Samuel Madden, Improving Wireless
Network Performance Using Sensor Hints, 8th USENIX Symp. on Networked Systems Design and
Implementation (NSDI), 2011,March,Boston, MA
3.
Vladimir Dyo, Stephen A. Ellwood, David W. Macdonald, Andrew Markham, Cecilia Mascolo, Bence Pasztor,
Salvatore Scellato, Niki Trigoni, Ricklef Wohlers, Kharsim Yousef. Evolution and Sustainability of a Wildlife
Monitoring Sensor Network. In Proceedings of the 8th ACM Conference on Embedded Networked Sensor
Systems (Sensys 2010). Zurich, Switzerland. November 2010
4-2 Protocol:
4.
X. Liang, X. Li, J.Q. Shen, R. Lu, X. Lin, X. Shen, and W. Zhang, "Exploiting Prediction to Enable Secure and
Reliable Routing in Wireless Body Area Networks," In Proceedings of the 31st IEEE International Conference on
Computer Communications (INFOCOM),2012
5.
Zhenyun Zhuang, Kyu-Han Kim, and Jatinder P. Singh. "Improving Energy Efficiency of Location Sensing on
Smartphones", in Proceedings of ACM MobiSys 2010, San Francisco, CA, June 2010.
6.
Jiangwei Zhou, Yu Chen, Ben Leong, and Pratibha Sundar Sundaramoorthy; Practical 3D geographic routing for
wireless sensor networks. In Proceedings of ACM Sensys 2010. November 2010.
7.
Bin Xu, Ran Yu, Guodong Sun, and Zheng Yang, Whistle: Synchronization-Free TDOA for Localization. IEEE
ICDCS 2011, Minneapolis, Minnesota, USA, June 20-24, 2011.
8.
Liqun Li, Guoliang Xing, Limin Sun, Wei Huangfu, Ruogu Zhou, Hongsong Zhu, Exploiting FM Radio Data
System for Adaptive Clock Calibration in Sensor Networks, The 9th International Conference on Mobile
Systems, Applications, and Services (MobiSys), June 28 – July 1, Washington DC, USA,
5 Capacity of Wireless networks (Ph.D)
Ch 0
Novel Smartphone Application Related to Networking、 Data Collection….
Ch1
WiFi Handoff Problem
Ch2
Location Service
Projects:
1. Underwater Pressure Routing:
A SEA Swarm (Sensor Equipped Aquatic Swarm) is a group of underwater sensors that move with the water current and
enable space and time monitoring of local underwater events such as contaminants and intruders. In this project we study
real-time monitoring using the SEA Swarm: under water sensors report sensed data to sonobuoys on the surface; the
sonobuoys then deliver the data to the command ship. In sensor networks, it is a must to have a location tag for each
sensed data/event. Localization in underwater is very costly, however, because it requires periodic network wide
dissemination of coordinates. Another costly protocol is proactive/reactive routing because of the route discovery and
maintenance requirements. In this project, we use underwater pressure to do routing (we assume each node can measure
pressure using a simple barometer).
Sub-project 1: Pressure routing implementation in QualNet or Ns-2 (a team of two students)
Sub-project 2: 3D localization and visualization (a team of two students). Mobile sensors periodically report sensor data to
the command center. Given the available date, one should be able to re-construct the 3D map of sensor nodes.
Related Papers:
[1] DBR: Depth-Based Routing for Underwater Sensor Networks, Networking’08
http://www.engr.uconn.edu/~jcui/UWSN_papers/Networking08_DBR.pdf
[2] Phero-Trail: a Bio-inspired Location Service for Mobile Underwater Sensors" WUWNet'08
http://netlab.cs.ucla.edu/wiki/files/wuwnet08pherotrail.pdf
[3] On throughput efficiency of geographic opportunistic routing,
http://spinlab.wpi.edu/pubs/Zeng_QSHINE_2007_preprint.pdf
[4] Least-Cost Opportunistic Routing, Henri Dubois-Ferriere, Matthias Grossglauser, Martin Vetterli, Allerton'07
http://www.csl.uiuc.edu/allerton/archives/allerton07/PDFs/papers/0219.pdf
[5] Efficient Geographic Routing in Multihop Wireless Networks, Mobihoc 2005
http://www.cs.umd.edu/users/slee/pubs/nadv-mobihoc05.pdf
2. Energy-efficient number of cluster heads in randomly distributed sensor networks
In a randomly distributed sensor network, cluster-head task is rotated among all sensors so as to save energy, what would
be the optimum number of cluster heads in such a way that:
1) The total energy consumption can be minimized.
2) Avoid situations where we have no cluster head at some points of time (considering the distribution function of the
number of cluster-heads).
In this project, we need to perform Monte Carlo simulations on different network layouts in terms of the location of the
base station and the shape of the sensor field. In our mind, the optimum number of cluster heads depend on 1) routing
protocol 2) MAC protocol 3) network
layout 4) total number of the nodes and etc.
Up to now, we have considered the following references:
[1] M.Gerla and J. T.-C.Tsai, "Multicluster, mobile, multimedia radio network," ACM-Baltzer J. Wireless Networks, vol.
1, no. 3, pp.
255-265, 1995.
[2] Yuh-Ren Tsai: Coverage-Preserving Routing Protocols for Randomly Distributed Wireless Sensor Networks. IEEE
Transactions on Wireless Communications 6(4): 1240-1245 (2007)
[3] W. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, "An Application-Specific Protocol Architecture for
Wireless Microsensor Networks," IEEE Transactions on Wireless Communications, Vol. 1, No. 4, pp. 660-670, Oct 2002.
3.Congestion Control in Ad Hoc Networks with Network Coding
Congestion control is a well known challenge of wireless multicast networking due to radio channel impairments, node
mobility, and distributed control. In particular, congestion control is more important in network coding since receivers
cannot decode original packets with large number of packet drop. TCP takes care of congestion control using Additive
Increase and Multiplicative Decrease (AIMD) scheme in unicast mode, but it cannot be effectively extended to multicast
because of the ACK implosion problem. Some congestion control schemes for ad hoc unicast have been proposed in the
literature [1] but very few ad hoc multicast congestion control schemes have been proposed [2][3][4]. Those ad hoc
multicast congestion control schemes, however, work in specific environments such as low traffic, and thus we need new
congestion control techniques in multicast. We will first evaluate a congestion detection scheme (network and queue
monitoring and back-pressure) and develop a utility function to find optimal source transmission rate.
[1] C. Lochert, B. Scheuermann, and M. Mauve. A Survey on Congestion Control for Mobile Ad Hoc Networks. Wireless
Communications and Mobile Computing, 2007.
[2] J. Peng, and B. Sikdar. A Multicast Congestion Control Scheme for Mobile Ad-Hoc Networks. Proceedings of the
IEEE Global Telecommunications Conference (Globecom),, 2003.
[3] K. Tang, K. Obraczka, S-J. Lee, and M. Gerla. Congestion Controlled Adaptive Lightweight Multicast in Wireless
Mobile Ad Hoc Networks. Proceedings of ISCC ‘02, 2002.
[4] W-Q. Xu, T-M. Wang, and C-H. Yu. MMCC : Multirate Multicast Congestion Control for Optimal Resource
Allocation in Ad Hoc Networks. Proceedings of Communications and Networking in China (ChinaCome ’06), 2006.
J-S. Park, M. Gerla, D.S. Lun, Y. Yi, M. Medard, “Codecast: a network-coding-based ad hoc multicast protocol,” IEEE
Wireless Communications, 2006.
4. DTCAST: Delay Tolerant Multicast in Ad Hoc Networks
Mobile ad hoc networks with intermittent connectivity, called Delay/Disruption Tolerant Networks (DTNs), have recently
received a lot of attention because of their applicability in various applications, including multicasting. We design a DTN
multicast protocol which is called DT-CAST for ad hoc multicast in intermittent connectivity environments. DTCAST
transmits packets using ODMRP (a very popular ad hoc multicast protocol) in normal situation, but it switches to
“epidemic content distribution” when a network is partitioned. In this case, leaf nodes store received packets and transfer
packets whenever they encounter disconnected multicast receivers. In this project, if time permits, we may also enhance
ODMRP with network coding ability. The DTN “extension” of ODMRP can utilize network coding to better exploit
opportunistic encounters. There are several sub tasks in this project:
Task 1: DTCAST protocol design and implementation in QualNet. Also, implement other DTN multicast protocols for
comparisons (e.g., tree-based OS-Multicast)
Task 2: DTCAST protocol design and implementation in Linux (Click modular router); Need to implement DTCAST,
based on the ODMRP code on top of Click. Also, test DTCAST using a small scale wireless testbed.
Reference:
[1] S. Lee, W. Su, M. Gerla, On-Demand multicast routing protocol, in: Proc. IEEE Wireless Communications and
Networking Conference, WCNC '99
[2] Multicasting in Delay Tolerant Networks: Semantic Models and Routing Algorithms, Zhao et al.
http://www.cc.gatech.edu/people/home/wrzhao/pub/wdtn05.pdf
[3] OS-multicast: On-demand Situation-aware Multicasting in Disruption Tolerant Networks, Qing Ye, Liang Cheng,
Mooi Choo Chuah and Brian D. Davison, VTC'06 http://www.cse.lehigh.edu/~brian/pubs/2006/VTC/OS-multicast.pdf
[4] Practical network coding, http://research.microsoft.com/~pachou/pubs/ChouWJ03.pdf
[5] CodeCast, http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4015713