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Performance Evaluation of Mini-sinks Mobility Using Multiple Paths in Wireless Sensor Networks
David Fotue, Houda Labiod, Thomas Engel
Pages - 150 - 167     |    Revised - 15-05-2012     |    Published - 20-06-2012
Volume - 6   Issue - 3    |    Publication Date - June 2012  Table of Contents
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KEYWORDS
Wireless Sensor Networks, Mini-sink Mobility, Multiple Paths, Congestion, Network Performance
ABSTRACT
This paper presents a new approach based on the use of many data collectors, which we designate Mini-Sinks (MSs), instead of a single sink to collect the data in order to improve Wireless Sensor Network (WSN) performance. One or more MS are mobile and move according to a controlled arbitrary mobility model inside the sensor field in order to maintain a fully-connected network topology, collecting data within their coverage areas and forwarding it towards the single main sink. Energy Conserving Routing Protocol (ECRP), based on route diversity, is implemented in MSs and sensors in order to optimize the transmission cost of the forwarding scheme. A set of multiple routing paths between MSs and sensors is generated to distribute the global traffic over the entire network. Simulations were performed in order to validate the performance of our new approach. We compare the results obtained with those for a single static sink and mobile sink, and show that our approach can achieve better performances such as packet delivery ratio, throughput, end-to-end delay, network lifetime, residual energy, energy and routing diversity overhead.
CITED BY (1)  
1 Abbasy, M. B., & Ordonez, L. M. L. (2013, March). Single-Sink Mobility Performance Analysis on a Wireless Senosr Networks. In Advanced Information Networking and Applications Workshops (WAINA), 2013 27th International Conference on (pp. 407-412). IEEE.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 TechRepublic 
5 Scribd 
6 SlideShare 
7 PdfSR 
1 P. Wang, R. Dai and I. Akyildiz. “Collaborative Data Compression Using Clustered Source Coding for Wireless Multimedia Sensor Networks,” in Proc. the 29thIEEE INFOCOM, 2010, pp. 2106-2114.
2 D. Kandris, M. Tsagkaropoulos, I. Politis, A. Tzes and S. Kotsopoulos. “Energy efficient and perceived QoS aware video routing over Wireless Multimedia Sensor Networks.” Ad Hoc networks Journal, vol. 9, no. 4, pp. 591-607, 2011.
3 J.H. Chang and L. Tassiulas. “Maximum lifetime routing in wireless sensor networks.” IEEE/ACM Transactions on Networking, vol. 12, pp. 609-619, 2004.
4 D. Fotue, F. Melakessou, H. Labiod and T. Engel. “Design of an Enhanced Energy Conserving Routing Protocol based on Route Diversity in Wireless Sensor Networks.” In Proc. of the 9thIEEE/IFIP Annual Mediterranean Ad Hoc Networking Workshop, 2010, pp. 1-7.
5 I. Chatzigiannakis, A. Kinalis and S. Nikoletseas. “Sink mobility protocols for data collection in wireless sensor networks.” In Proc. of the Forth ACM International Workshop on Mobility Management and Wireless Access (MOBIWAC), 2006, pp.52-59.
6 Q. Dong and W. Dargie. “A Survey on Mobility and Mobility-Aware MAC Protocols in Wireless Sensor Networks.” IEEE Communications Surveys and Tutorials, pp. 1-13, 2011.
7 M.S.G. Premi and K.S. Shaji. “Impact of Mobility Models on MMS Routing in Wireless Sensor Networks.” International Journal of Computer Applications (IJCA), vol. 22, No 9, pp. 47-51, 2011.
8 M. Vecchio, A.C. Viana, A. Ziviani and R. Friedman. “DEEP: Density-based proactive data dissemination protocol for wireless sensor networks with uncontrolled sink mobility.” Computer Communications journal (ComCom), vol. 33, Issue 8, pp. 929-939, 2010.
9 E.B. Hamida and G. Chelius. “Strategies for data dissemination to mobile sinks in wireless sensor networks.” IEEE Wireless Communications Magazine, vol. 15, Issue 6, pp. 31-37, 2008.
10 M. Marta and M. Cardei. “Improved sensor network lifetime with multiple mobile sinks.” Pervasive and Mobile Computing Journal, vol. 5, Issue 5, pp. 542-555, 2009.
11 H. Yang, F. Ye and B. Sikdar. “SIMPLE: Using Swarm Intelligence Methodology to Design Data Acquisition Protocol in Sensor Networks with Mobile Sinks.” in Proc. of INFOCOM, 2006.
12 X. Li, A. Nayak and I. Stojmenovic. “Exploiting Actuator Mobility for Energy-Efficient Data Collection in Delay-Tolerant Wireless Sensor Networks.” in Proc. of the IEEE Fifth International Conference on Networking and Services (ICNS), 2009.
13 F. Cuomo, E. Cipollone and A. Abbagnale. “Performance analysis of IEEE 802.15.4 wireless sensor networks: An insight into the topology formation process.” Computer Networks Journal (Elsevier), vol. 53, Issue 18, pp. 3057-3075, December 2009.
14 N. Vlajic and D. Stevanovic. “Sink mobility in wireless sensor networks: When theory meets reality.” in Proc. of the IEEE Sarnoff Symposium (SARNOFF), 2009, pp. 1-8.
15 Z.M. Wang, S. Basagni, E. Melachrinoudis and C. Petrioli. “Exploiting Sink Mobility for Maximizing Sensor Networks Lifetime.” in Proc. of the 38thAnnual Hawaii International Conference on System Sciences (HICSS),2005.
16 J. Luo and J.P. Hubaux. “Joint mobility and routing for lifetime elongation in wireless sensor networks.” in Proc. of the 24thINFOCOM, 2005, pp. 1735-1746.
17 D. Fotue, F. Melakessou, H. Labiod and T. Engel. “Mini-Sink Mobility on Route Diversity- Based Congestion Reduction and Low Latency in Wireless Sensor Networks.” in Proc. of the 8thACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor and Ubiquitous Networks (PE-WASUN), 2011, pp. 1-7.
18 W. Alsalih, S. Akl and H. Hassanein. “Placement of multiple mobile base stations in wireless sensor networks.” in Proc. of the IEEE International Symposium on Signal Processing and Information Technology, 2007, pp. 229-233.
19 K. P. Sushil and A. Dhawan. “Distributed Algorithms for Lifetime of Wireless Sensor NetworksBased on Dependencies Among Cover Sets.” in Proc. of the 14thInternational Conference on High Performance Computing (HiPC), 2007, pp. 381-392.
20 M. MacGregor and W. Grover. “Optimized k-Shortest-Paths Algorithm for Facility Restoration.”Software Practice and Experience journal,vol. 24, no. 9, pp. 823-834, 1994.
21 M. Tariquea, K. Tepeb, S. Adibic and S. Erfanib. “Survey of multipath routing protocols for mobile ad hoc networks.” Journal of Network and Computer Applications, vol. 32, pp. 1125- 1143, 2009.
22 S. Li, X. Ma, X. Wang and M. Tan.“Energy-efficient multipath routing in wireless sensor networks considering wireless interference.” Journal of Control Theory and Applications, vol. 9, pp. 127-132, 2011.
23 B. Yahya and J. Ben-Othman. “REER: Robust and energy efficient multipath routing protocol for wireless sensor networks.” in Proc. of the IEEE Global Telecommunications Conference (GLOBECOM), 2009, pp. 1-7.
24 E. Zegura, K. Calvert, and M. Donahoo. “A Quantitative Comparison of Graph-based Models for Internet Topology.” IEEE Transactions on Networking, 1997.
25 W. Ye, J. Heidemann and D. Estrin. “An energy efficient MAC protocol for wireless sensor networks.” in Proc. of the IEEE INFOCOM, 2005. March, 2005.
26 Z. Cheng, M. Perillo and W. Heinzelman. “General network lifetime and cost models for evaluating sensor network deployment strategies.” IEEE Transactions on Mobile Computing, vol. 7, pp. 484-497, 2008.
Mr. David Fotue
University of Luxembourg - Luxembourg
david.fotue@uni.lu
Professor Houda Labiod
Télécom ParisTech - France
Professor Thomas Engel
University of Luxembourg - Luxembourg