RISN: An Efficient Sensor Network Overlay with Support for Autonomous and Distributed Applications

Abstract

Once deployed, sensor networks are capable of providing a comprehensive view of their environment. However, since the current sensor network paradigm promotes isolated networks that are statically tasked, the full power of the harnessed data has yet to be exploited. In recent years, users have become mobile enti-ties that require constant access to data for efficient and autonomous processing. Under the current limita-tions of sensor networks, users would be restricted using only a subset of the vast amount of data being col-lected; depending on the networks they are able to access. Through reliance on isolated networks, prolifera-tion of sensor nodes can easily occur in any area that has high appeals to users. Furthermore, support for dy-namic tasking of nodes and efficient processing of data is contrary to the general view of sensor networks as subject to severe resource constraints. Addressing the aforementioned challenges requires the deployment of a system that allows users to take full advantage of data collected in the area of interest to their tasks. Such a system must enable interoperability of surrounding networks, support dynamic tasking, and swiftly react to stimuli. In light of these observations, we introduce a hardware-overlay system designed to allow users to efficiently collect and utilize data from various heterogeneous sensor networks. The hardware-overlay takes advantage of FPGA devices and the mobile agent paradigm in order to efficiently collect and process data from cooperating networks. The computational and power efficiency of the prototyped system are herein demonstrated. Furthermore, as a proof-of-concept, we present the implementation of a distributed and autonomous visual object tracker implemented atop the Reconfigurable and Interoperable Sensor Network (RISN) showcasing the network’s ability to support ad-hoc agent networks dedicated to user’s tasks.

Share and Cite:

E. Jean, I. Rauschert, R. Collins, A. Hurson, S. Sedigh and Y. Jiao, "RISN: An Efficient Sensor Network Overlay with Support for Autonomous and Distributed Applications," International Journal of Communications, Network and System Sciences, Vol. 4 No. 1, 2011, pp. 1-16. doi: 10.4236/ijcns.2011.41001.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] E. Jean, R. T. Collins, A. R. Hurson, S. Sedigh and Y. Jiao, “Pushing Sensor Network Computation to the Edge,” Proceedings of 5th International Conference on Wireless Communications, Networking and Mobile Computing, Beijing, 24-26 September 2009, pp. 1-4. doi:10.1109/WICOM.2009.5302659
[2] E. Jean, Y. Jiao, A. R. Hurson and V. Kumar, “Pushing Sensor Network Computation to the Edge while Enabling Inter-Network Operability and Securing Agents,” Proceedings of 3rd International Innovations and Real-Time Applications of Distributed Sensor Networks Symposium, Shreveport, 26-27 November 2007, pp. 66-75.
[3] Y. Jiao and A. R. Hurson, “Performance Analysis of Mobile Agents in Mobile Distributed Information Retrieval System—A Quantitative Case Study,” Journal of Interconnection Networks, Vol. 5, No. 3, pp. 351-372. doi:10.1142/S0219265904001210
[4] R. Garcia, A. Gordon-Ross and A. D. George, “Exploiting Partially Reconfigurable FPGAs for Situation-Based Reconfiguration in Wireless Sensor Networks,” Proceedings of 17th IEEE Symposium on Field-Programmable Custom Computing Machines, Napa, 5-7 April 2009, pp. 243-246. http://doi.ieeecomputersociety.org/10.1109/FCCM.2009.45
[5] S. Commuri, V. Tadigotla and M. Atiquzzaman, “Reconfigurable Hardware Based Dynamic Data Aggregation in Wireless Sensor Networks,” International Journal of Distributed Sensor Networks, Vol. 4, No. 2, pp. 194-212. doi:10.1080/15501320802001234
[6] A. Sheth, C. Henson and S. S. Sahoo, “Semantic Sensor Web,” IEEE Internet Computing, Vol. 12, No. 4, pp. 78-83. doi:10.1109/MIC.2008.87
[7] P. B. Gibbons, B. Karp, Y. Ke, S. Nath and S. Seshan, “IrisNet: An Architecture for a Worldwide Sensor Web,” IEEE Pervasive Computing, Vol. 2, No. 4, pp. 22-33. http://doi.ieeecomputersociety.org/10.1109/MPRV.2003.1251166
[8] C. Fok, G. Roman and C. Lu, “Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications,” Proceedings of the 25th IEEE International Conference on Distributed Computing Systems, Columbus, 10 June 2005, pp. 653-662.
[9] Y. Kwon, S. Sundresh, K. Mechitov and G. Agha, “ActorNet: An Actor Platform for Wireless Sensor Networks,” Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems, Hakodate, 8-12 May 2006, pp. 1297-1300.
[10] S. Pattem, S. Poduri and B. Krishnamachari, “Energy- Quality Tradeoffs for Target Tracking in Wireless Sensor Networks,” Proceedings of 2nd International Workshop of Information Processing in Sensor Networks, Palo Alto, 22-23 April 2003, pp. 32-46.
[11] H. Yang and B. Sikdar, “A Protocol for Tracking Mobile Targets Using Sensor Networks,” Proceedings of 1st IEEE International Workshop on Sensor Network Protocols and Applications, Anchorage, 11 May 2003, pp. 71-81. doi:10.1109/SNPA.2003.1203358
[12] W. Zhang and G. Cao, “DCTC: Dynamic Convoy Tree- Based Collaboration for Target Tracking in Sensor Networks,” IEEE Transactions on Wireless Communications, Vol. 3, No. 5, pp. 1689-1701. doi:10.1109/TWC.2004. 833443
[13] L. Szumel, J. LeBrun and J. D. Owens, “Towards a Mobile Agent Framework for Sensor Networks,” Proceedings of 2nd IEEE Workshop on Embedded Networked Sensors, Sydney, 30-31 May 2005, pp. 79-88. http://doi.ieeecomputersociety.org/10.1109/EMNETS.2005.1469102
[14] Anonymous Xilinx Documentation for ML405 Board, July 2008.
[15] J. Altmann, F. Gruber, L. Klug, W. Stockner and E. Weippl, “Using Mobile Agents in Real World: A Survey and Evaluation of Agent Platforms,” Proceedings of 2nd Workshop on Infrastructure for Agents, MAS and Scalable MAS at Autonomous Agents, Montreal, 28 May-1 June 2001, pp. 10-16.
[16] D. B. Lange and M. Oshima, “Programming and Deploying Java Mobile Agents with Aglets,” Addison-Wesley, Boston, 1998.
[17] D. Comaniciu, V. Ramesh and P. Meer, “Real-Time Tracking of Non-Rigid Objects Using Mean Shift,” Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Hilton Head Island, 13-15 June 2000, pp. 142-149.
[18] A. Yilmaz, O. Javed and M. Shah, “Object Tracking: A Survey,” ACM Computing Surveys, Vol. 38, No. 4, pp. 1-45.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.