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http://dx.doi.org/10.3837/tiis.2014.01.008

Distributed Information Extraction in Wireless Sensor Networks using Multiple Software Agents with Dynamic Itineraries  

Gupta, Govind P. (Department of Computer Science & Engineering, Indian Institute of Technology)
Misra, Manoj (Department of Computer Science & Engineering, Indian Institute of Technology)
Garg, Kumkum (Faculty of Engineering, Manipal University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.1, 2014 , pp. 123-144 More about this Journal
Abstract
Wireless sensor networks are generally deployed for specific applications to accomplish certain objectives over a period of time. To fulfill these objectives, it is crucial that the sensor network continues to function for a long time, even if some of its nodes become faulty. Energy efficiency and fault tolerance are undoubtedly the most crucial requirements for the design of an information extraction protocol for any sensor network application. However, most existing software agent based information extraction protocols are incapable of satisfying these requirements because of static agent itineraries and large agent sizes. This paper proposes an Information Extraction protocol based on Multiple software Agents with Dynamic Itineraries (IEMADI), where multiple software agents are dispatched in parallel to perform tasks based on the query assigned to them. IEMADI decides the itinerary for an agent dynamically at each hop using local information. Through mathematical analysis and simulation, we compare the performance of IEMADI with a well known static itinerary based protocol with respect to energy consumption and response time. The results show that IEMADI provides better performance than the static itinerary based protocols.
Keywords
Wireless sensor network; software agent; dynamic itinerary; agent migration; information extraction;
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1 Chen, M., et al., "Itinerary Planning for Energy-efficient Agent Communication in Wireless Sensor Networks," IEEE Transactions on Vehicular Technology, pp. 1-1, 2011.
2 Mpitziopoulos A., Konstantopoulos C., Gavalas D., and Pantziou G., "A pervasive assistive environment for visually impaired people using wireless sensor network infrastructure," Journal of Network and Computer Applications, vol. 34, pp. 194-206, 2011.   DOI   ScienceOn
3 Averbakh I. and Berman O., "Sales-delivery man problems on treelike networks," Networks, vol. 25, pp. 45-58, 1995.   DOI   ScienceOn
4 Xu, Y., & Qi, H., "Mobile agent migration modeling and design for target tracking in wireless sensor networks," Ad Hoc Networks, vol. 6(1), pp. 1-16, 2008.   DOI   ScienceOn
5 Gupta G. P., Misra M., and Garg K., "Multiple Mobile Agents based Data Dissemination Protocol for Wireless Sensor Networks," in Proc. of Springer International Conference on Advances in Computer Science and Information Technology, Networks and Communications, pp. 334-345, 2012.
6 Akyildiz I.F., Su W., Sankarasubramaniam Y., Cayirci E., "Wireless sensor networks: a survey," Computer Networks, vol. 38, pp. 393-422, 2002.   DOI   ScienceOn
7 Chen, M., Gonzalez, S., Leung, V., "Applications and design issues for mobile agents in wireless sensor networks," IEEE Wireless Communication, 14, (6), pp. 20-26, 2007.
8 Qi H., Iyengar S. S., and Chakrabarty K., "Multi-Resolution Data Integration Using Mobile Agents in Distributed Sensor Networks," IEEE Transactions on Systems, Man, and Cybernetics, Part C, vol. 31, no. 3, pp. 383-391, Aug. 2001.   DOI   ScienceOn
9 Bulusu N., Heidemann J., and Estrin D., "GPS-Less Low Cost Outdoor Localization for Very Small Devices," IEEE Personal Communication, vol. 7, no. 5, pp. 28-34, Oct. 2000.
10 Mao G., Fidan B., Anderson B. D., "Wireless sensor network localization techniques," Computer Networks, vol. 51(10), pp. 2529-2553, 2007.   DOI   ScienceOn
11 Wang Y., Wang X.,Wang D., Agrawal D. P., "Range-free localization using expected hop progress in wireless sensor networks," IEEE Transactions on Parallel and Distributed Systems, vol. 20(10), pp.1540-1552, 2009.   DOI   ScienceOn
12 Rachuri K. K., Murthy C.S.R., "On the scalability of expanding ring search for dense wireless sensor networks," Journal of Parallel and Distributed Computing, vol. 70(9), pp.917-929, 2010.   DOI   ScienceOn
13 C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann, and F. Silva, "Directed diffusion for wireless sensor networking," IEEE/ACM Transactions on Networking, vol. 11, pp. 2-16, 2003.   DOI   ScienceOn
14 Intanagonwiwat C., Estrin D., Govindan R., Heidemann J., "Impact of network density on data aggregation in wireless sensor networks," in Proc. of ICDCS'02, the 22nd International Conference on Distributed Computing Systems, pp.457, Jul.2002.
15 Verma V, Joshi R. C., Xie B, Agrawal D. P., "Combating the bloated state problem in mobile agents based network monitoring applications," Computer Networks, vol.52(17), pp.3218 - 3228, 2008.   DOI   ScienceOn
16 Castalia Simulator (March 2012) [online] http://castalia.npc.nicta.com.au/.
17 Qi H. and Wang F., "Optimal Itinerary Analysis for Mobile Agents in Ad Hoc Wireless Sensor Networks," in Proc. 13th International Conference on Wireless Communications (Wireless'2001), vol. 1, Calgary, Canada, pp. 147-153, Jul. 2001.
18 Wu Q., Rao N., Barhen J., Iyengar S., Vaishnavi V., Qi H., Chakrabarty K.,, "On Computing Mobile Agent Routes for Data Fusion in Distributed Sensor Networks," IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 6, pp. 740-753, Jun. 2004.   DOI   ScienceOn
19 Gavalas, D., Mpitziopoulos, A., Pantziou, G., Konstantopoulos, C., "An approach for near-optimal distributed data fusion in wireless sensor networks," Springer Wireless Network, vol. 16, pp. 1407-1425, 2009.
20 Cai W., Chen M., Hara T., Shu L., Kwon T., "A genetic algorithm approach to multi-agent itinerary planning in wireless sensor networks," Springer Mobile Network application, 16 (6), pp. 782-793, 2011.   DOI
21 Konstantopoulos, C., Mpitziopoulos, A., Gavalas, D., Pantziou, G., "Effective determination of mobile agent itineraries for data aggregation on sensor networks," IEEE Transaction on Knowledge and Data Engineering, vol. 22(12), pp. 1679-1693, 2010.   DOI   ScienceOn
22 Mpitziopoulos, A., Gavalas, D., Konstantopoulos, C., Pantziou, G., "CBID: a scalable method for distributed data aggregation in WSNs," Hindawi International Journal of Distributed Sensor Network, vol. 2010, Article ID 206517, pp.13, 2010.