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11 - Wireless mobile sensor networks

Published online by Cambridge University Press:  05 December 2014

Mohammad S. Obaidat  and
Sudip Misra
Mohammad S. Obaidat
Affiliation:
Monmouth University, New Jersey
Sudip Misra
Affiliation:
Indian Institute of Technology
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Summary

As we discussed in the previous chapters, a wireless sensor network (WSN) consists of tiny nodes with limited resources. The nodes sense their surroundings and communicate with the sink(s) through multi-hop mechanisms. Nodes are powered by batteries. Often the batteries of a node are not of the rechargeable type or the replacement of the batteries, after exhaustion of battery power, is not a suitable option. Generally, static or stationary WSNs are used. If all nodes of a WSN are stationary, then the WSN is referred to as the stationary wireless sensor network (SWSN), as discussed in [1]. Some limitations of a SWSN can be overcome by using mobile nodes. As an example, if the battery power of a node becomes exhausted during operation, another node can move to the position of the former node and provide services offered by that exhausted node. If all nodes, or at least some, of a WSN are capable of moving, then this type of WSN is called a mobile wireless sensor network (MWSN). Obviously, a mobile node must have the capabilities of communication, computation, and locomotion.

Some of the drawbacks of SWSNs are discussed here. In WSNs, the sensor nodes communicate with the sink or base station through multi-hop mechanism. Moreover, the communication pattern is many-to-one. As a consequence, nodes nearer to the sink forward their own data, as well as data from other more-distant nodes. An example of an SWSN, where sensor nodes are deployed randomly, is shown in Figure 11.1. In the presence of static base station(s), a WSN encounters the funneling/bottleneck effect and the hotspot problem [2].

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Principles of Wireless Sensor Networks , pp. 248 - 281
Publisher: Cambridge University Press
Print publication year: 2014

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References

Jun, J. H., Xie, B. and Agrawal, D. P., “Wireless mobile sensor networks: protocols and mobility strategies,” in Guide to Wireless Sensor Networks, Misra, S., Woungang, I. and Misra, S. C., Ed. Springer, 2009, pp. 607–634.CrossRefGoogle Scholar
Vlajic, N. and Stevanovic, D., “Sink mobility in wireless sensor networks: when theory meets reality,” Proceedings of the 32nd International Conference on Sarnoff Symposium (SARNOFF’09), NJ, USA, 2009.Google Scholar
Wang, B., Lim, H. B. and Ma, D., “A survey of movement strategies for improving network coverage in wireless sensor networks,” Computer Communications, Vol. 32, Nos. 13–14, pp. 1427–1436, 2009.CrossRefGoogle Scholar
Zhang, H. and Hou, J., “On deriving the upper bound of α-lifetime for large sensor networks,” in Proceedings of the 5th ACM International Symposium on Mobile ad hoc Networking and Computing (MobiHoc ’04), New York, NY, USA, 2004, pp. 121–132.CrossRefGoogle Scholar
Berg, M., Cheong, O., Kreveld, M. and Overmars, M., Computational Geometry: Algorithms and Applications, 3rd ed. Berlin: Springer-Verlag, 2008.CrossRefGoogle Scholar
Ghosh, A., “Estimating coverage holes and enhancing coverage in mixed sensor networks,” in Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks (LCN ’04), Washington, DC, USA, 2004, pp. 68–76.CrossRefGoogle Scholar
Wang, G., Cao, G. and Porta, T. L., “Movement-assisted sensor deployment,” IEEE Transactions on Mobile Computing, Vol. 5, No. 6, pp. 640–652, 2006.CrossRefGoogle Scholar
Lee, H. J. et al., “Centroid-based movement assisted sensor deployment schemes in wireless sensor networks,” in Proceedings of the 70th IEEE Vehicular Technology Conference Fall (VTC 2009-Fall), Anchorage, Alaska, USA, Sep. 2009.Google Scholar
Wang, G., Cao, G., Berman, P. and La Porta, T. F., “Bidding protocols for deploying mobile sensors,” IEEE Transactions on Mobile Computing, Vol. 6, No. 5, pp. 563–576, 2007.CrossRefGoogle Scholar
Howard, A., Mataric, M. J. and Sukhatme, G. S., “Mobile sensor network deployment using potential fields: a distributed, scalable solution to the area coverage problem,” in Proceedings of the 6th International Symposium on Distributed Autonomous Robotics Systems (DARS02), Fukuoka, Japan, June 2002.Google Scholar
Ahmed, N., Kanhere, S. S. and Jha, S., “Ensuring area coverage in hybrid wireless sensor networks,” in Proceedings of the 3rd international Conference on Mobile ad-hoc and Sensor Networks (MSN’07), Zhang, H., Olariu, S., Cao, J. and Johnson, D. B., Ed. Berlin, Heidelberg: Springer-Verlag, pp. 548–560, 2007.CrossRefGoogle Scholar
Guo, P., Zhu, G. and Fang, L., “An adaptive coverage algorithm for large-scale mobile sensor networks,” Ubiquitous Intelligence and Computing, Lecture Notes in Computer Science, Vol. 4159/2006, pp. 468–477, 2006.CrossRefGoogle Scholar
Wu, J. and Yang, S., “SMART: a scan-based movement-assisted sensor deployment method in wireless sensor networks,” in Proceedings of 24th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2005), Miami, USA, Vol. 4, 2005, pp. 2313–2324.Google Scholar
Lambrou, T. P. and Panayiotou, C. G., “Collaborative area monitoring using wireless sensor networks with stationary and mobile nodes,” EURASIP Journal on Advances in Signal Processing, Vol. 2009, 2009.
Wang, Y. C., Peng, W. C., Chang, M. H. and Tseng, Y. C., “Exploring load-balance to dispatch mobile sensors in wireless sensor networks,” in Proceedings of 16th International Conference on Computer Communications and Networks,(ICCCN 2007), Honolulu, HI, 2007, pp. 669–674.Google Scholar
Luo, J. and Hubaux, J. P., “Joint mobility and routing for lifetime elongation in wireless sensor networks,” in Proceedings of the 24th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM, 2005), Miami, FL, USA, Vol. 3, 2005, pp. 1735–1746.Google Scholar
Chakrabarti, A., Sabharwal, A. and Aazhang, B., “Using predictable observer mobility for power efficient design of sensor networks,” in Proceedings of the 2nd International Conference on Information Processing in Sensor Networks (IPSN’03), Zhao, F. and Guibas, L., Ed. Berlin, Heidelberg: Springer-Verlag, pp. 129–145, 2003.CrossRefGoogle Scholar
Wang, G., Wang, T., Jia, W., Guo, M., and Li, J., “Adaptive location updates for mobile sinks in wireless sensor networks,” The Journal of Supercomputing, Vol. 47, No. 2, pp. 127–145, 2009.CrossRefGoogle Scholar
Seada, K. and Helmy, A., “Efficient and robust geocasting protocols for sensor networks,” Computer Communications, Vol. 29, No. 2, pp. 151–161, 2006.CrossRefGoogle Scholar
Bi, Y., Sun, L., Ma, J., et al., “HUMS: an autonomous moving strategy for mobile sinks in data-gathering sensor networks,” in EURASIP Journal on Wireless Communications and Networking, Vol. 2007, 2007.
Wang, W., Srinvasan, V. and Chua, K., “Using mobile relays to prolong the lifetime of wireless sensor networks,” in Proceedings of the 11th Annual International Conference on Mobile Computing and Networking (MobiCom ’05), ACM, New York, NY, USA, 2005, pp. 270–283.Google Scholar
Anastasi, G., Conti, M. and Di Francesco, M., “Data collection in sensor networks with data mules: an integrated simulation analysis,” in Proceedings of IEEE Symposium on Computers and Communications, 2008 (ISCC 2008), Marrakech, Morocco, 2008, pp. 1096–1102.CrossRefGoogle Scholar
Shah, R. C., Roy, S., Jain, S. and Brunette, W., “Data MULEs: modeling a three-tier architecture for sparse sensor networks,” in Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, Anchorage, Alaska, USA, 2003, pp. 30–41.CrossRefGoogle Scholar
Yang, Y., Fonoage, M. I. and Cardei, M., “Improving network lifetime with mobile wireless sensor networks,” Computer Communications, Vol. 33, No. 4, pp. 409–419, 2010.CrossRefGoogle Scholar

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