Event Based Fairness for Video Surveillance Sensor Networks

(Work in Progress)
  • Yunus Durmus
  • Bahri Atay Ozgovde
  • Cem Ersoy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5550)

Abstract

With their ease of installation, infrastructureless mode of operation and flexible deployment style, Video Surveillance Sensor Networks (VSSNs) provide more opportunities than legacy surveillance methods for applications such as habitat monitoring and border surveillance. We argue that events created in the coverage area of a VSSN are the application level messaging units and propose to employ Event Based Fairness (EBF) which aims at a fair distribution of nodes’ resources according to the event flows. We carried out simulation experiments to compare the application level performances of two different EBF implementations with that of FCFS based queueing. We observe that EBF enhances the VSSN performance in two ways: Firstly, when the video traffic due to the events created exceed the total capacity of the network, EBF increases the overall number of events properly reported to the sink. Secondly, EBF reduces the initial event reporting delay, thus decreases the response time to the occurring events within the network.

Keywords

Video Surveillance Sensor Networks Fairness Queue Management 

References

  1. 1.
    Downes, I., Rad, L., Aghajan, H.: Development of a mote for wireless image sensor networks. In: Proc. of COGnitive systems with Interactive Sensors (COGIS), Paris, France (March 2006)Google Scholar
  2. 2.
    Rahimi, M., Baer, R., Iroezi, O.I., Garcia, J.C., Warrior, J., Estrin, D., Srivastava, M.: Cyclops: in situ image sensing and interpretation in wireless sensor networks. In: SenSys 2005: Proceedings of the 3rd international conference on Embedded networked sensor systems, pp. 192–204. ACM Press, New York (2005)Google Scholar
  3. 3.
    Demers, A., Keshav, S., Shenker, S.: Analysis and simulation of a fair queueing algorithm. In: SIGCOMM 1989: Symposium proceedings on Communications architectures & protocols, pp. 1–12. ACM, New York (1989)Google Scholar
  4. 4.
    Shreedhar, M., Varghese, G.: Efficient fair queueing using deficit round robin. SIGCOMM Comput. Commun. Rev. 25(4), 231–242 (1995)CrossRefGoogle Scholar
  5. 5.
    Bertsekas, D., Gallager, R.: Data networks, 2nd edn. Prentice-Hall, Inc., NJ (1992)MATHGoogle Scholar
  6. 6.
    Jun, J., Sichitiu, M.: Fairness and qos in multihop wireless networks. In: IEEE 58th Vehicular Technology Conference, VTC, vol. 5, pp. 2936–2940 (2003)Google Scholar
  7. 7.
    Raniwala, A., De, P., Sharma, S., Krishnan, R., cker Chiueh, T.: End-to-end flow fairness over ieee 802.11-based wireless mesh networks. In: IEEE INFOCOM, pp. 2361–2365 (2007)Google Scholar
  8. 8.
    Rangwala, S., Gummadi, R., Govindan, R., Psounis, K.: Interference-aware fair rate control in wireless sensor networks. In: Rizzo, L., Anderson, T.E., McKeown, N. (eds.) SIGCOMM, pp. 63–74. ACM, New York (2006)Google Scholar
  9. 9.
    Fan, K.-W., Zheng, Z., Sinha, P.: Steady and fair rate allocation for rechargeable sensors in perpetual sensor networks. In: Proc. of ACM SENSYS, Raleigh, NC (November 2008)Google Scholar
  10. 10.
    Chen, S., Fang, Y., Xia, Y.: Lexicographic Maxmin Fairness for Data Collection in Wireless Sensor Networks. IEEE Transactions On Mobile Computing, 762–776 (2007)Google Scholar
  11. 11.
    Sridharan, A., Krishnamachari, B.: Max-min fair collision-free scheduling for wireless sensor networks. In: Workshop on Multihop Wireless Networks (MWN 2004), IPCCC (2004)Google Scholar
  12. 12.
    Akan, O.B., Akyildiz, I.F.: Event-to-sink reliable transport in wireless sensor networks. IEEE/ACM Trans. Netw. 13(5), 1003–1016 (2005)CrossRefGoogle Scholar
  13. 13.
    Wan, C.-Y., Eisenman, S.B., Campbell, A.T.: Coda: congestion detection and avoidance in sensor networks. In: SenSys 2003: Proceedings of the 1st international conference on Embedded networked sensor systems, pp. 266–279. ACM, New York (2003)Google Scholar
  14. 14.
    He, T., Stankovic, J.A., Lu, C., Abdelzaher, T.F.: Speed: A stateless protocol for real-time communication in sensor networks. In: ICDCS, pp. 46–55 (2003)Google Scholar
  15. 15.
    Tassiulas, L., Sarkar, S.: Maxmin fair scheduling in wireless networks. In: INFOCOM (2002)Google Scholar
  16. 16.
    Nuyens, M., Wierman, A.: The Foreground-Background queue: A survey. Performance Evaluation 65(3-4), 286–307 (2008)CrossRefGoogle Scholar
  17. 17.
    Rai, I., Urvoy-Keller, G., Biersack, E.: Analysis of LAS scheduling for job size distributions with high variance. In: Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems, pp. 218–228. ACM Press, New York (2003)CrossRefGoogle Scholar
  18. 18.
    Wierman, A., Bansal, N., Harchol-Balter, M.: A note on comparing response times in the M/GI/1/FB and M/GI/1/PS queues. Operations Research Letters 32(1), 73–76 (2004)MathSciNetCrossRefMATHGoogle Scholar
  19. 19.
    Wierman, A., Harchol-Balter, M.: Classifying scheduling policies with respect to unfairness in an M/GI/1. ACM SIGMETRICS Performance Evaluation Review 31(1), 238–249 (2003)CrossRefGoogle Scholar
  20. 20.
    Shao, Z., Madhow, U.: Scheduling heavy-tailed data traffic over the wireless Internet. In: Proceedings of IEEE 56th Vehicular Technology Conference, 2002. VTC 2002-Fall, vol. 2 (2002) Google Scholar
  21. 21.
    Ye, W., Heidemann, J., Estrin, D.: Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Trans. Netw. 12(3), 493–506 (2004)CrossRefGoogle Scholar
  22. 22.
    Inc, O.: OPNET ModelerGoogle Scholar
  23. 23.
    Komar, C., Ersoy, C.: Optimization of power consumption using trespassers favorite path and variable sensing range integrated sleep schedule in surveillance wireless sensor networks. In: 23rd International Symposium on Computer and Information Sciences, 2008. ISCIS 2008, pp. 1–5 (2008)Google Scholar
  24. 24.
    Ozgovde, A., Demirkol, I., Ersoy, C.: Effect of sleep schedule and frame rate on the capabilities of Video Sensor Networks. In: 3rd International Symposium on Wireless Pervasive Computing, 2008. ISWPC 2008, pp. 156–159 (2008)Google Scholar
  25. 25.
    Durmus, Y., Ozgovde, A., Ersoy, C.: Exploring the effect of the network parameters of video sensor networks. In: Proceedings of ISCN 2008 8th International Symposium on Computer Networks, pp. 188–192 (2008)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Yunus Durmus
    • 1
  • Bahri Atay Ozgovde
    • 1
  • Cem Ersoy
    • 1
  1. 1.Computer Networks Research Laboratory Department of Computer EngineeringBoǧaziçi University BebekIstanbulTurkey

Personalised recommendations