Abstract
During the last one and a half decades, wireless sensor networks (WSNs) have witnessed significant growth and tremendous development. While enjoying the wide variety of applications, the sensors in WSN have constrained resources, affecting their living lives, working times, assigned tasks, etc. Though a large number of efforts have been devoted into designing protocols that save energy as much as possible, they are still a passive solution. In this paper, we propose a novel approach called policy-based assistance system (PAS) that addresses the issue of resource limitation in a proactive manner. Complementary to existing works which focus on saving energy in individual nodes, our proposed approach further allows sensors with limited resources to make requests to other sensors to help complete the tasks. In this way, the resources in the whole WSN are better utilized and more tasks can be completed with little communication overhead.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422
Bertino E, Brodie C, Calo SB, Cranor LF, Karat C, Karat J, Li N, Lin D, Lobo J, Ni Q et al (2009) Analysis of privacy and security policies. IBM Journal of Research and Development 53(2):225–241
Burton H (1970) Bloom. Space/time trade-offs in hash coding with allowable errors, Communications of The ACM
Geoffrey WC, Jason W, Matt W (2010) Idea: integrated distributed energy awareness for wireless sensor networks. In: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, MobiSys ’10, pp 35–48, New York, NY, USA. ACM
Jason F, Satyanarayanan M (1999) PowerScope: a tool for profiling the energy usage of mobile applications. In: Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications, WMCSA ’99, p 2, Washington, DC, USA, 1999. IEEE Computer Society
Jason F, Mahadev S (1999) Energy-aware adaptation for mobile applications, volume 33. ACM
Rodrigo F, Prabal D, Philip L, Ion S (2008) Quanto: tracking energy in networked embedded systems. In: Proceedings of the 8th USENIX Conference on Operating Systems Design and Implementation, OSDI’08, pp 323–338, Berkeley, CA, USA, 2008. USENIX Association
Hou W, Dong H, Yin G (2013) A membership degre refinement-based evolutionary clustering algorithm. J Comput Res Dev 50(3):548–558
Sushama K, Cinzia Squicciarini A, Carminati B(2013) Policy-compliant search query routing for web service discovery in peer to peer networks. In: 2013 IEEE International Conference on Web Services (ICWS), pp 387–394. IEEE
Geoffrey M, Parkes DC, Matt W (2005) Decentralized, adaptive resource allocation for sensor networks. In: Proceedings of the 2Nd Conference on Symposium on Networked Systems Design & Implementation-Volume 2, NSDI’05, pp 315–328, Berkeley, CA, USA. USENIX Association
National Research Council (2001) Embedded, everywhere: a research agenda for networked systems of embedded computers. National Academy Press
Rumble SM, Ryan S, Philip L, David M, Nickolai Z (2009) Apprehending joule thieves with cinder. In: Proceedings of the 1st ACM Workshop on Networking, Systems, and Applications for Mobile Handhelds, MobiHeld ’09, pp 49–54, New York, NY, USA. ACM
Shah RC, Rabaey JM (2002) Energy aware routing for low energy ad hoc sensor networks. In: 2002 IEEE Wireless Communications and Networking Conference, 2002. WCNC2002, vol 1, pp 350–355 vol 1
Jacob S, Alexander K, Matthew G, Matthew B, Corner MD, Berger ED (2007) Eon: a language and runtime system for perpetual systems. In: Proceedings of the 5th International Conference on Embedded Networked Sensor Systems, SenSys ’07, pp 161–174, New York, NY, USA. ACM
Soua R, Minet P (2011) A survey on energy efficient techniques in wireless sensor networks. In: Wireless and Mobile Networking Conference (WMNC), 2011 4th Joint IFIP, pp 1–9
Jianfeng W, Jingdong W, Nenghai Y, Shipeng L (2013) Order preserving hashing for approximate nearest neighbor search. In: Proceedings of the 21st ACM International Conference on Multimedia, MM ’13, pp 133–142, New York, NY, USA. ACM
Coordinated resource management for sensor networks (2009) Jason Waterman, Geoffrey Werner Challen, and Matt Welsh. Peloton. In HotOS 9:9–9
Ya X, John H, Deborah E (2001) Geography-informed energy conservation for ad hoc routing. In: Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, MobiCom ’01, pp 70–84, New York, NY, USA. ACM
Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330
Acknowledgements
This work is partially supported by the Fundamental Research Funds for the Central Universities (Grant No. ZYGX2016KYQD115), the National Natural Science Foundation of China (Grant No. 61602092) and the National Science Foundation (Grant No. DGE-1433659).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, J., Bowers, A., Lin, D. et al. PAS: policy-based assistance in sensor networks. Computing 99, 915–928 (2017). https://doi.org/10.1007/s00607-016-0531-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00607-016-0531-8