Dynamic Multi-hop Routing Protocol Based on Fuzzy-Firefly Algorithm for Data Similarity Aware Node Clustering in WSNs

In multi-hop routing, cluster heads close to the base station functionaries as intermediate nodes for father cluster heads to relay the data packet from regular nodes to base station. The cluster heads that act as relays will experience energy depletion quicker that causes hot spot problem. This paper proposes a dynamic multihop routing algorithm named Data Similarity Aware for Dynamic Multi-hop Routing Protocol (DSA-DMRP) to improve the network lifetime, and satisfy the requirement of multi-hop routing protocol for the dynamic node clustering that consider the data similarity of adjacent nodes. The DSA-DMRP uses fuzzy aggregation technique to measure their data similarity degree in order to partition the network into unequal size clusters. In this mechanism, each node can recognize and note its similar neighbor nodes. Next, K-hop Clustering Algorithm (KHOPCA) that is modified by adding a priority factor that considers residual energy and distance to the base station is used to select cluster heads and create the best routes for intra-cluster and inter-cluster transmission. The DSA-DMRP was compared against the KHOPCA to justify the performance. Simulation results show that, the DSA DMRP can improve the network lifetime longer than the KHOPCA and can satisfy the requirement of the dynamic multi-hop routing protocol.

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

[2]  Xin-She Yang,et al.  Cuckoo Search and Firefly Algorithm , 2014 .

[3]  Mohammad Shokouhifar,et al.  Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks , 2016, Expert Syst. Appl..

[4]  Hui Wang,et al.  Firefly algorithm with neighborhood attraction , 2017, Inf. Sci..

[5]  Jó Ueyama,et al.  Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks , 2015, Comput. Geosci..

[6]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[7]  Jie Wu,et al.  An energy-efficient unequal clustering mechanism for wireless sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[8]  Muddassar Farooq,et al.  Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions , 2011, Inf. Sci..

[9]  Tuan Dinh Le,et al.  Design and deploy a wireless sensor network for precision agriculture , 2015, 2015 2nd National Foundation for Science and Technology Development Conference on Information and Computer Science (NICS).

[10]  Adnan Yazici,et al.  An energy aware fuzzy approach to unequal clustering in wireless sensor networks , 2013, Appl. Soft Comput..

[11]  Zun-wen He,et al.  An Energy Consumption Balanced Clustering Algorithm for Wireless Sensor Network , 2010, 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM).

[12]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .

[13]  Matthias R. Brust,et al.  Dynamic multi-hop clustering for mobile hybrid wireless networks , 2008, ICUIMC '08.

[14]  Riri Fitri Sari Data Similarity Based Dynamic Node Clustering Using Bio-Inspired Algorithm for Self-Organized Wireless Sensor Networks , 2016, Intelligent Environments.

[15]  Haibin Duan,et al.  New progresses in swarm intelligence-based computation , 2015, Int. J. Bio Inspired Comput..

[16]  Manoj Kollam,et al.  Zigbee Wireless Sensor Network for better Interactive Industrial Automation , 2011, 2011 Third International Conference on Advanced Computing.

[17]  Shigenobu Sasaki,et al.  An Unequal Multi-hop Balanced Immune Clustering protocol for wireless sensor networks , 2016, Appl. Soft Comput..

[18]  Vikas Deep,et al.  Implementation of ICT and Wireless Sensor Networks for Earthquake Alert and Disaster Management in Earthquake Prone Areas , 2016 .

[19]  Thinh Nguyen,et al.  Distance Based Thresholds for Cluster Head Selection in Wireless Sensor Networks , 2012, IEEE Communications Letters.

[20]  Sachin Tripathi,et al.  Fuzzy based unequal energy aware clustering with multi-hop routing in wireless sensor network , 2015, 2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI).

[21]  Rui Zhou,et al.  Event-triggered cooperative target tracking in wireless sensor networks , 2016 .

[22]  Rajat Gupta,et al.  Security for wireless sensor networks in military operations , 2013, 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT).

[23]  M. Mehdi Afsar,et al.  Clustering in sensor networks: A literature survey , 2014, J. Netw. Comput. Appl..

[24]  Sachin Gajjar,et al.  FUCP: Fuzzy based unequal clustering protocol for wireless sensor networks , 2015, 2015 39th National Systems Conference (NSC).

[25]  Alia Ghaddar,et al.  Algorithm for data similarity measurements to reduce data redundancy in wireless sensor networks , 2010, 2010 IEEE International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM).

[26]  Muhammad Khurram Khan,et al.  A robust and anonymous patient monitoring system using wireless medical sensor networks , 2018, Future Gener. Comput. Syst..

[27]  Master Gardener,et al.  Mathematical games: the fantastic combinations of john conway's new solitaire game "life , 1970 .

[28]  Sanjay Jha,et al.  Experimental evaluation of multi-hop routing protocols for wireless sensor networks , 2010, IPSN '10.