Two energy-efficient cluster head selection techniques based on distance for wireless sensor networks

Energy efficiency in data collection and transmission is always a crucial factor in wireless sensor networks (WSN). Thus, minimizing energy dissipation and maximizing network life-time are key factors in the design of routing protocols for WSNs. In this paper, based on Low Energy Adaptive Clustering Hierarchy (LEACH) protocols, we propose two new distance-based clustering routing protocols, which we call DB-LEACH and DBEA-LEACH. The first approach (distance-based) selects a cluster head node by considering geometric distance between the candidate nodes to the base station. To further improve DB-LEACH, DBEA-LEACH (distance-based energy-aware) additionally selects a cluster head not only based on distance, but also by examining residual energy of the node greater than the average residual energy level of nodes in the network. The simulation results show that our two proposed algorithm outperformed a traditional LEACH as well as its derivatives in terms of conserving energy such that prolonging network lifetime.

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

[2]  Yan Zhang,et al.  Research on Clustering Routing Algorithms in Wireless Sensor Networks , 2010, 2010 International Conference on Intelligent Computation Technology and Automation.

[3]  Makoto Takizawa,et al.  A Survey on Clustering Algorithms for Wireless Sensor Networks , 2010, 2010 13th International Conference on Network-Based Information Systems.

[4]  Ting Peng,et al.  Improvement of LEACH protocol for WSN , 2012, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery.

[5]  Chirag Prajapati,et al.  Energy Efficient Cluster Head Selection in Wireless Sensor Networks , 2014 .

[6]  Feng Liu,et al.  The improvement of LEACH protocol in WSN , 2011, Proceedings of 2011 International Conference on Computer Science and Network Technology.

[7]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[8]  Hwee Pink Tan,et al.  Clustering algorithms for maximizing the lifetime of wireless sensor networks with energy-harvesting sensors , 2013, Comput. Networks.

[9]  Aimin Wang,et al.  A clustering algorithm based on energy information and cluster heads expectation for wireless sensor networks , 2012, Comput. Electr. Eng..

[10]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[11]  R. Biswas,et al.  ALEACH: Advanced LEACH routing protocol for wireless microsensor networks , 2008, 2008 International Conference on Electrical and Computer Engineering.

[12]  Hamid Sarbazi-Azad,et al.  Performance modeling of the LEACH protocol for mobile wireless sensor networks , 2011, J. Parallel Distributed Comput..

[13]  Neeraj Kumar,et al.  A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks , 2013, J. Netw. Comput. Appl..

[14]  A. Manjeshwar,et al.  TEEN: a routing protocol for enhanced efficiency in wireless sensor networks , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[15]  Ahmad Patooghy,et al.  I-LEACH: An efficient routing algorithm to improve performance & to reduce energy consumption in Wireless Sensor Networks , 2013, The 5th Conference on Information and Knowledge Technology.

[16]  Yaodong Zhang,et al.  A Wireless Sensor Network Clustering Algorithm Based on Energy and Distance , 2009, 2009 Second International Workshop on Computer Science and Engineering.

[17]  Chatchai Khunboa,et al.  Performance Evaluation of LEACH on Cluster Head Selection Techniques in Wireless Sensor Networks , 2013 .

[18]  Walid Osamy,et al.  IBLEACH: intra-balanced LEACH protocol for wireless sensor networks , 2014, Wireless Networks.

[19]  Akramul Azim,et al.  Hybrid LEACH: A relay node based low energy adaptive clustering hierarchy for wireless sensor networks , 2009, 2009 IEEE 9th Malaysia International Conference on Communications (MICC).

[20]  Dirk Timmermann,et al.  Low energy adaptive clustering hierarchy with deterministic cluster-head selection , 2002, 4th International Workshop on Mobile and Wireless Communications Network.

[21]  Chitsutha Soomlek,et al.  MAP: An Optimized Energy-Efficient Cluster Header Selection Technique for Wireless Sensor Networks , 2014 .