Improving Energy-Awareness in Selective Reprogramming of WSNs
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Abstract
Saving energy is considered one of the main challenges in wireless sensor networks (WSNs), being radio activities such as message transmission/reception and idle listening the main factors of energy consumption in the nodes. These activities increase with the increase of reliability level required, which is usually achieved through flooding strategies. Procedures such as remote WSNs reprogramming require high-level of reliability leading to an increase in radio activity and, consequently, waste of energy. This energy waste is magnified when dealing with selective reprogramming where only few nodes need to receive the code updates. The main focus of this paper is on improving energy efficiency during selective reprogramming of WSNs, taking advantage of wise routing, decreasing the nodes’ idle listening periods and using multiple cooperative senders instead of a single one. The proposed strategies are a contribution toward deploying energy-aware selective reprogramming in WSNs.
Keywords
WSNs Selective reprogramming Energy-aware strategiesNotes
Acknowledgements
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.
References
- 1.Brown, S., Sreenan, C.J.: Software update recovery for wireless sensor networks. In: Komninos, N. (ed.) SENSAPPEAL 2009. LNICST, vol. 29, pp. 107–125. Springer, Heidelberg (2010)CrossRefGoogle Scholar
- 2.Chlipala, A., Hui, J., Tolle, G.: Deluge: data dissemination for network reprogramming at scale. Technical report, University of California, Berkeley (2004)Google Scholar
- 3.Lima, E., Carvalho, P., Gama, O.: A protocol extension for selective reprogramming of WSNs. In: 2015 23rd International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 280–284. IEEE (2015)Google Scholar
- 4.Zheng, X.-L., Wan, M.: A survey on data dissemination in wireless sensor networks. J. Comput. Sci. Technol. 29, 470–486 (2014)MathSciNetCrossRefGoogle Scholar
- 5.Zheng, X., Sarikaya, B.: Code dissemination in sensor networks with MDeluge. In: 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks, SECON 2006, pp. 661–666. IEEE (2006)Google Scholar
- 6.Panta, R.K., Khalil, I., Bagchi, S.: Stream: low overhead wireless reprogramming for sensor networks. In: IEEE INFOCOM 2007, 26th IEEE International Conference on Computer Communications, pp. 928–936. IEEE (2007)Google Scholar
- 7.Panta, R.K., Bagchi, S., Midkiff, S.P.: Efficient incremental code update for sensor networks. ACM Trans. Sens. Netw. 7, 1–32 (2011)CrossRefGoogle Scholar
- 8.Panta, R.K., Bagchi, S.: Hermes: fast and energy efficient incremental code updates for wireless sensor networks. In: IEEE INFOCOM 2009, pp. 639–647. IEEE (2009)Google Scholar
- 9.Kulkarni, S.S., Wang, L.: MNP: multihop network reprogramming service for sensor networks. In: Proceedings of 25th IEEE International Conference on Distributed Computing Systems, ICDCS 2005, pp. 7–16. IEEE (2005)Google Scholar
- 10.De, P., Liu, Y., Das, S.K.: Energy-efficient reprogramming of a swarm of mobile sensors. IEEE Trans. Mob. Comput. 9, 703–718 (2010)CrossRefGoogle Scholar
- 11.Krasniewski, M.D., Panta, R.K., Bagchi, S., Yang, C.-L., Chappell, W.J.: Energy-efficient on-demand reprogramming of large-scale sensor networks. ACM Trans. Sens. Netw. 4, 2 (2008)CrossRefGoogle Scholar
- 12.Kulkarni, S.S., Arumugam, M.: Infuse: a TDMA based data dissemination protocol for sensor networks. Int. J. Distrib. Sens. Netw. 2, 55–78 (2006)CrossRefGoogle Scholar
- 13.Pásztor, B., Mottola, L., Mascolo, C., Picco, G.P., Ellwood, S., Macdonald, D.: Selective reprogramming of mobile sensor networks through social community detection. In: Silva, J.S., Krishnamachari, B., Boavida, F. (eds.) EWSN 2010. LNCS, vol. 5970, pp. 178–193. Springer, Heidelberg (2010)CrossRefGoogle Scholar
- 14.Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 3, 366–379 (2004)CrossRefGoogle Scholar
- 15.Tomar, G.S., Verma, S.: Dynamic multi-level hierarchal clustering approach for wireless sensor networks (2009)Google Scholar
- 16.OMNeT++. http://www.omnetpp.org. Accessed May 2016