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Aware Diffusion: A Semi-Holistic Routing Protocol for Wireless Sensor Networks

DOI: 10.4236/wsn.2016.83004, PP. 37-49

Keywords: Directed Diffusion, Shortest Path, Wireless Sensor Networks, Hop Count, Power Consumption, Reliable Delivery

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Abstract:

Routing is a challenging task in Wireless Sensor Networks (WSNs) due to the limitation in energy and hardware capabilities in WSN nodes. This challenge prompted researchers to develop routing protocols that satisfy WSNs needs. The main design objectives are reliable delivery, low energy consumption, and prolonging network lifetime. In WSNs, routing is based on local information among neighboring nodes. Routing decisions are made locally; each node will select the next hop without any clue about the other nodes on the path. Although a full knowledge about the network yields better routing, that is not feasible in WSNs due to memory limitation and to the high traffic needed to collect the needed data about all the nodes in the network. As an effort to try to overcome this disadvantage, we are proposing in this paper aware diffusion routing protocol. Aware diffusion follows a semi-holistic approach by collecting data about the available paths and uses these data to enforce healthier paths using machine learning. The data gathering is done by adding a new stage called data collection stage. In this stage, the protocol designer can determine which parameters to collect then use these parameters in enforcing the best path according to certain criteria. In our implementation of this paradigm, we are collecting total energy on the path, lowest energy level on the path, and hop count. Again, the data collected is designer and application specific. The collected data will be used to compare available paths using non-incremental learning, and the outcome will be preferring paths that meet the designer criteria. In our case, healthier and shorter paths are preferred, which will result in less power consumption, higher delivery rate, and longer network life since healthier and fewer nodes will be doing the work.

References

[1]  Pantazis, N.A. (2012) Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey. IEEE of Communications Surveys & Tutorials, 15, 551-591.
[2]  Rahman, Md.A., Pramanik, Md.I. and Rahman, Md.F. (2013) A Survey on Energy Efficient Routing Techniques in Wireless Sensor Networks. ICACT, 200-205.
[3]  Merret, G.V. (2010) Wireless Sensor Networks: Application-Centric Design. InTech.
[4]  Singh, S.K., Singh, M.P. and Singh, D.K. (2010) Routing Protocols in Wireless Sensor Networks—A Survey. International Journal of Computer Science & Engineering Survey (IJCSES), 1, 63-83.
http://dx.doi.org/10.5121/ijcses.2010.1206
[5]  Kazem Sohraby, D.M. and Znati, T. (2007) Wireless Sensor Networks Technology, Protocols, and Applications. Wiley.
[6]  Paolo Bellavista, G.C. (2013) Convergence of MANET and WSN in IoT Urban Scenarios. IEEE Sensors Journal, 13.
http://dx.doi.org/10.1109/jsen.2013.2272099
[7]  Cirstea, C. (2011) Energy Efficient Routing Protocols for Wireless Sensor Networks: A Survey. IEEE SIITME, 277-282.
http://dx.doi.org/10.1109/siitme.2011.6102735
[8]  Al-Karaki, J.N. and Kamal, A.E. (2004) Routing Techniques in Wireless Sensor Networks: A Survey. IEEE Wireless Communications, 11, 6-28.
http://dx.doi.org/10.1109/MWC.2004.1368893
[9]  Waltenegus Dargie, C.P. (2010) Fundamentals of Wireless Sensor Networks Theory and Practice. Wiley, United Kingdom.
http://dx.doi.org/10.1002/9780470666388
[10]  Karl, H. and Willig, A. (2005) Protocols-and-Architectures-for-Wireless-Sensor-Networks. John Wiley & Sons Ltd.
http://dx.doi.org/10.1002/0470095121
[11]  Mahalik, N.P. (2007) Sensor Networks and Configuration: Fundamentals, Standards, Platforms, and Applications. Springer.
http://dx.doi.org/10.1007/3-540-37366-7
[12]  Intanagonwiwat, C., Govindan, R. and Estrin, D. (2000) Directed Diffusion: A Scalable and Robustcommunication Paradigm for Sensor Networks. Proceedings of 6th Annual International Conference on Mobile Computing and Networking, Boston, 56-67.
http://dx.doi.org/10.1145/345910.345920
[13]  Chalermek Intanagonwiwat, R.G., Estrin, D., Heidemann, J. and Silva, F. (2003) Directed Diffusion for Wireless Sensor Networking. IEEE/ACM Transactions on Networking, 11, 2-16.
http://dx.doi.org/10.1109/TNET.2002.808417
[14]  Chen, Y.-S., Nian, Y.-W. and Sheu, J.-P. (2002) An Energy-Efficient Diagonal-Based Directed Diffusion for Wireless Senor Networks. Proceedings of Ninth International Conference of Parallel and Distributed Systems, 445-450.
[15]  Handziski, V., Kopke, A., Karl, H., Frank, C. and Drytkiewicz, W. (2004) Improving the Energy Efficiency of Directed Diffusion Using Passive Clustering. EWSN 2004, LNCS 2920, 172-187.
[16]  Liu, X., Li, F., Kuang, H. and Wu, X. (2006) The Study of Directed Diffusion Routing Protocol Based on Clustering for Wireless Sensor Network. The Sixth World Congress on Intelligent Control and Automation, Vol. 1, 5120-5124.
[17]  Cheng, D., Song, Y., Mao, Y. and Wang, X. (2014) LDDP: A Location-Based Directed Diffusion Routing Protocol for Smart Home Sensor Network. 2nd International Conference on Systems and Informatics (ICSAI).
http://dx.doi.org/10.1109/icsai.2014.7009340
[18]  Bi, J.N. and Xu, E. (2012) A Secure and Energy-Efficient Data Aggregation Protocol Based on Directed Diffusion. International Symposium on Information Science and Engineering (ISISE).
[19]  Choe, J. and Kim, K. (2008) EADD: Energy Aware Directed Diffusion for Wireless Sensor Networks. International Symposium an Parallel and Distributed Processing with Applications.
http://dx.doi.org/10.1109/ispa.2008.104
[20]  Qi, H., Wang, F. and Wang, B. (2011) Energy Aware Adaptive Directed Diffusion Algorithm of Wireless Sensor Networks. International Conference on Computer Science and Service System (CSSS).
[21]  Li, Z.Y. and Shi, H.S. (2007) Design of Gradient and Node Remaining Energy Constrained Directed Diffusion Routing for WSN. International Conference on Wireless Communications, Networking and Mobile Computing (WiCom).
http://dx.doi.org/10.1109/wicom.2007.647
[22]  Sutton, R.S. and Barto, A.G. (2000) Reinforcement Learning: An Introduction. The MIT Press, 3rd Printing.
[23]  Kulkarni, R., Forster, A. and Venayagamoorthy, G.K. (2010) Computational Intelligence in Wireless Sensor Networks: A Survey. IEEE Communications Surveys & Tutorials, 13, 68-96.
[24]  Boulis, A. Castalia User’s Manual. NICTA.

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