An Energy-efficient hierarchical routing protocol for long range transmission in wireless sensor networks

Clustering is an effective approach to hierarchically organizing network topology and to prolong the lifetime of a wireless sensor network. Current clustering protocols usually utilize two techniques: selecting cluster heads with more residual energy and rotating cluster heads periodically to distribute the energy consumption among nodes in each cluster. Most of the researches in this field has focused on energy-efficient solutions, but caring less about the communication between Cluster Head (CH) nodes and Base Station (BS). When the sensor field is far away from the base station, the cluster heads are burdened with heavier relay traffic and tend to die much faster. To mitigate the problem, we propose an Energy-Efficient Hierarchical Routing Protocol (EEHRP) for long range transmission in the wireless sensor networks. It uses a number of gateway nodes, which do not engage in clustering, to connect the CHs and base station. They are responsible for transmitting packets received from the CHs to the base station, thus the CHs can preserve some energy in data forwarding and the gateway nodes can ease their burden by not participating in clustering. Simulation results show that EEHRP obviously increases the network lifetime and well balances the energy consumption among the sensor nodes.

[1]  He Yan Performance Analysis of an Improved Immune Genetic Algorithm , 2008 .

[2]  Hyun-Kyo Jung,et al.  Optimal design of synchronous motor with parameter correction using immune algorithm , 1997 .

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

[4]  H. F. Wang,et al.  Interactions and multivariable design of multiple control functions of a unified power flow controller , 2002 .

[5]  L. Yadong A New Genetic Chaos Optimization Combination Method , 2002 .

[6]  Jiangtao Xi,et al.  An Energy-Aware Multilevel Clustering algorithm for wireless sensor networks , 2008, 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[7]  Günter Rudolph,et al.  Convergence analysis of canonical genetic algorithms , 1994, IEEE Trans. Neural Networks.

[8]  Jie Wu,et al.  An unequal cluster-based routing protocol in wireless sensor networks , 2009, Wirel. Networks.

[9]  Chern-Lin Chen,et al.  Coordinated Synthesis of Multimachine Power System Stabilizer Using an Efficient Decentralized Modal Control (DMC) Algorithm , 1987, IEEE Transactions on Power Systems.

[10]  Yi-Chih Hsieh,et al.  Using immune-based genetic algorithms for single trader's periodic marketing problem , 2008, Math. Comput. Model..

[11]  Wendi B. Heinzelman,et al.  Prolonging the lifetime of wireless sensor networks via unequal clustering , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[12]  Ossama Younis,et al.  An experimental study of routing and data aggregation in sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[13]  Adrian Perrig,et al.  ACE: An Emergent Algorithm for Highly Uniform Cluster Formation , 2004, EWSN.

[14]  LI Shi-yong Adaptive immune evolutionary algorithm , 2004 .

[15]  Qiaofu Chen,et al.  A novel active power filter with fundamental magnetic flux compensation , 2004 .

[16]  Richard Y. K. Fung,et al.  An immune-genetic algorithm for introduction planning of new products , 2009, Comput. Ind. Eng..

[17]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

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

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