Modified Gossip Protocol in Wireless Sensor Networks Using Chebyshev Distance and Fuzzy Logic

The Flooding is a traditional flat based routing protocol where unlimited broadcasting of the packets in the flooding scheme will cause the huge energy consumption to send the packets from source to sink due to implosion, overlap, resource blindness and consequently creates broadcast storm. However Gossiping routing protocol in WSNs is very much effective due to its simplicity, robustness, distributed and capability to work in noisy and uncertain environments. But due to recirculation of information and repeated data communication of randomized gossip protocol which can lead to a significant energy consumption of the network. This paper proposes an energy efficient routing protocol based on Fuzzy Logic and Chebyshev Distance, which is a modification of gossip protocol. The new protocol determines the optimal routing path from source to destination by selected the best node from candidate nodes in the forwarding paths by favoring highest remaining energy and the lowest distance to the sink. Simulation results shows that the proposed method is efficient to control messages forwarding and improves the performance which minimizes the overall energy consumption and maximize WSNs lifespan.

[1]  Ganesh K. Venayagamoorthy,et al.  Computational Intelligence in Wireless Sensor Networks: A Survey , 2011, IEEE Communications Surveys & Tutorials.

[2]  Arthur L. Liestman,et al.  A survey of gossiping and broadcasting in communication networks , 1988, Networks.

[3]  Mehdi Dabbaghian,et al.  An improved ELGossiping data distribution technique with emphasis on reliability and resource constraints in wireless sensor network , 2010, 2010 2nd International Conference on Electronic Computer Technology.

[4]  Haibo Zhang,et al.  Balancing Energy Consumption to Maximize Network Lifetime in Data-Gathering Sensor Networks , 2009, IEEE Transactions on Parallel and Distributed Systems.

[5]  Sajal K. Das,et al.  EBRP: Energy-Balanced Routing Protocol for Data Gathering in Wireless Sensor Networks , 2011, IEEE Transactions on Parallel and Distributed Systems.

[6]  K. Saraswathi.  A Survey of Routing Protocols in Wireless Sensor Networks , 2015 .

[7]  Lotfi A. Zadeh,et al.  Soft computing and fuzzy logic , 1994, IEEE Software.

[8]  Thomas A. Runkler,et al.  Selection of appropriate defuzzification methods using application specific properties , 1997, IEEE Trans. Fuzzy Syst..

[9]  H. R. Karkvandi,et al.  Effective Lifetime-Aware Routing in Wireless Sensor Networks , 2011, IEEE Sensors Journal.

[10]  Liang Cheng,et al.  Flossiping: a new routing protocol for wireless sensor networks , 2004, IEEE International Conference on Networking, Sensing and Control, 2004.

[11]  Stephen P. Boyd,et al.  Gossip algorithms: design, analysis and applications , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[12]  JAMAL N. AL-KARAKI,et al.  Routing techniques in wireless sensor networks: a survey , 2004, IEEE Wireless Communications.

[13]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[14]  M. Rafiee,et al.  An Improved Gossiping Data Distribution Technique with Emphasis on Reliability and Resource Constraints , 2009, 2009 WRI International Conference on Communications and Mobile Computing.

[15]  Mohamed F. Younis,et al.  A survey on routing protocols for wireless sensor networks , 2005, Ad Hoc Networks.

[16]  A. Dimakis,et al.  Geographic gossip: efficient aggregation for sensor networks , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.