Advertisement

Computing

, Volume 99, Issue 10, pp 915–928 | Cite as

PAS: policy-based assistance in sensor networks

  • Jingwei LiEmail author
  • Adam Bowers
  • Dan Lin
  • Peng Jiang
  • Wei Jiang
Article
  • 165 Downloads

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.

Keywords

Policy-based assistance Sensor network Wireless network 

Mathematics Subject Classification

68M10 Network design and communication 90B10 Network models, deterministic 90B18 Communication networks 

Notes

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).

References

  1. 1.
    Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422CrossRefGoogle Scholar
  2. 2.
    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):225–241CrossRefGoogle Scholar
  3. 3.
    Burton H (1970) Bloom. Space/time trade-offs in hash coding with allowable errors, Communications of The ACMGoogle Scholar
  4. 4.
    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. ACMGoogle Scholar
  5. 5.
    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 SocietyGoogle Scholar
  6. 6.
    Jason F, Mahadev S (1999) Energy-aware adaptation for mobile applications, volume 33. ACMGoogle Scholar
  7. 7.
    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 AssociationGoogle Scholar
  8. 8.
    Hou W, Dong H, Yin G (2013) A membership degre refinement-based evolutionary clustering algorithm. J Comput Res Dev 50(3):548–558Google Scholar
  9. 9.
    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. IEEEGoogle Scholar
  10. 10.
    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 AssociationGoogle Scholar
  11. 11.
    National Research Council (2001) Embedded, everywhere: a research agenda for networked systems of embedded computers. National Academy PressGoogle Scholar
  12. 12.
    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. ACMGoogle Scholar
  13. 13.
    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 1Google Scholar
  14. 14.
    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. ACMGoogle Scholar
  15. 15.
    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 1–9Google Scholar
  16. 16.
    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. ACMGoogle Scholar
  17. 17.
    Coordinated resource management for sensor networks (2009) Jason Waterman, Geoffrey Werner Challen, and Matt Welsh. Peloton. In HotOS 9:9–9Google Scholar
  18. 18.
    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. ACMGoogle Scholar
  19. 19.
    Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  • Jingwei Li
    • 1
    Email author
  • Adam Bowers
    • 2
  • Dan Lin
    • 2
  • Peng Jiang
    • 3
  • Wei Jiang
    • 2
  1. 1.Center for Cyber SecurityUniversity of Electronic Science and Technology of ChinaChengduPeople’s Republic of China
  2. 2.Department of Computer ScienceMissouri University of Science and TechnologyRollaUSA
  3. 3.Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijingPeople’s Republic of China

Personalised recommendations