Fuzzy-Logic-Based Energy Optimized Routing for Wireless Sensor Networks

Wireless sensor nodes are usually powered by batteries and deployed in unmanned outdoors or dangerous regions. So, constrained energy is a prominent feature for wireless sensor networks. Since the radio transceiver typically consumes more energies than any other hardware component on a sensor node, it is of great importance to design energy optimized routing algorithm to prolong network lifetime. In this work, based on analysis of energy consumption for data transceiver, single-hop forwarding scheme is proved to consume less energy than multihop forwarding scheme within the communication range of the source sensor or a current forwarder, using free space energy consumption model. We adopt the social welfare function to predict inequality of residual energy of neighbors after selecting different next hop nodes. Based on energy inequality, the method is designed to compute the degree of energy balance. Parameters such as degree of closeness of node to the shortest path, degree of closeness of node to Sink, and degree of energy balance are put into fuzzy logic system. Fuzzy-logic-based energy optimized routing algorithm is proposed to achieve multiparameter, fuzzy routing decision. Simulation results show that the algorithm effectively extends the network lifetime and has achieved energy efficiency and energy balance together, compared with similar algorithms.

[1]  Ossama Younis,et al.  An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic , 2012, Ad Hoc Networks.

[2]  José D. P. Rolim,et al.  Energy balanced data propagation in wireless sensor networks , 2006, Wirel. Networks.

[3]  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.

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

[5]  Wendi Heinzelman,et al.  Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks , 2022 .

[6]  Naveen Chauhan,et al.  Balancing Energy Consumption to Maximize Network Lifetime in Data- Gathering Sensor Networks , 2013 .

[7]  He Huang,et al.  Cooperative Data Processing Algorithm Based on Mobile Agent in Wireless Sensor Networks , 2012, Int. J. Distributed Sens. Networks.

[8]  Mariam Yusuf,et al.  A fuzzy approach to energy optimized routing for wireless sensor networks , 2009, Int. Arab J. Inf. Technol..

[9]  Dimitrios D. Vergados,et al.  Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[10]  Brad Karp,et al.  GPSR : Greedy Perimeter Stateless Routing for Wireless , 2000, MobiCom 2000.

[11]  Jin-Shyan Lee,et al.  Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy Predication , 2012, IEEE Sensors Journal.

[12]  Indranil Gupta,et al.  Cluster-head election using fuzzy logic for wireless sensor networks , 2005, 3rd Annual Communication Networks and Services Research Conference (CNSR'05).

[13]  Li Ge-yang.  Residual energy scheming based energy equilibrium routing protocol for wireless sensor network , 2009 .

[14]  K. Selçuk Candan,et al.  Power-aware single- and multipath geographic routing in sensor networks , 2007, Ad Hoc Networks.

[15]  Xue Feng.  Distributed Energy Balancing Routing Algorithm in Wireless Sensor Networks , 2010 .

[16]  Lovepreet Kaur,et al.  Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey , 2014 .

[17]  Yi-hua Zhu,et al.  An energy-efficient data gathering algorithm to prolong lifetime of wireless sensor networks , 2010, Comput. Commun..

[18]  Wendi B. Heinzelman,et al.  Application-specific protocol architectures for wireless networks , 2000 .

[19]  W. Pan,et al.  Lifetime Enhancement in Wireless Sensor Networks Using Fuzzy Approach and A-Star Algorithm , 2012, IEEE Sensors Journal.

[20]  Seon-Ho Park,et al.  CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks , 2008, 2008 10th International Conference on Advanced Communication Technology.

[21]  Gustavo de Veciana,et al.  Spatial Energy Balancing Through Proactive Multipath Routing in Wireless Multihop Networks , 2007, IEEE/ACM Transactions on Networking.

[22]  Seyyed Javad Mirabedini,et al.  A new method for flat routing in wireless sensor networks using fuzzy logic , 2011, Proceedings of 2011 International Conference on Computer Science and Network Technology.

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

[24]  Young-Bae Ko,et al.  A novel gradient approach for efficient data dissemination in wireless sensor networks , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[25]  F. Bourguignon.  On the Measurement of Inequality , 2003 .