Energy consumption optimization with Ichi Taguchi method for Wireless Sensor Networks

Wireless Sensor Networks (WSN) consists of sensor nodes for monitoring and reporting sensible changes on a field to a specific server. One of the applications of WSN is large area monitoring, where sensor nodes are placed in far fields with limited power sources. Due to the adhered reason, the energy consumption of sensor nodes is considered as one of the major challenge in WSN. Many factor in WSN contributes to energy consumption such as Medium Access Control protocol (MAC), the network topology, and routing protocol. With the variety of factors that affects the energy consumption in WSN; the challenge of optimizing WSN networks toward a low energy consumption is becoming a hard problem. In the literature many efforts are paid for designing, implementing, and improving protocols in terms of power consumption. However, few efforts are paid for optimizing the existing protocols and other network parameters toward a green technology. This paper focuses in WSN infrastructure and protocols optimization by introducing the Ichi Taguchi (Taguchi) optimization method. Taguchi method is used to predict the best design parameters to achieve optimal performance parameters. Moreover, Taguchi method is used to optimize the energy consumed by sensor nodes against network protocols and network topology design parameters. A simulation experiments are curried out on the discrete event simulator OMNET++ for the purposes of this research paper. The obtained results show the impact of the network protocols toward the energy consumption. Furthermore, a proposed network topology and protocols set is introduced, and compared against the existing once.

[1]  Fernando Ordóñez,et al.  Robust Optimization Models for Energy-Limited Wireless Sensor Networks under Distance Uncertainty , 2008, IEEE Transactions on Wireless Communications.

[2]  A.H. Aghvami,et al.  Energy Efficiency Analysis of p-Persistent CSMA and the Effect of Sleeping Periods in a Distributed Sensor Topology , 2008, 2008 Second International Conference on Sensor Technologies and Applications (sensorcomm 2008).

[3]  Cheng Pan,et al.  Task Allocation for Wireless Sensor Network Using Modified Binary Particle Swarm Optimization , 2014, IEEE Sensors Journal.

[4]  Hui Wang,et al.  Network lifetime optimization in wireless sensor networks , 2010, IEEE Journal on Selected Areas in Communications.

[5]  John S. Baras,et al.  Integrated Modeling and Simulation Framework for Wireless Sensor Networks , 2012, 2012 IEEE 21st International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises.

[6]  Ying Cai,et al.  Taguchi method for solving the economic dispatch problem with nonsmooth cost functions , 2005 .

[7]  Henry Leung,et al.  A Joint Fusion, Power Allocation and Delay Optimization Approach for Wireless Sensor Networks , 2011, IEEE Sensors Journal.

[8]  Hui Wang,et al.  Network lifetime maximization with cross-layer design in wireless sensor networks , 2008, IEEE Transactions on Wireless Communications.

[9]  Kwok-Leung Tsui,et al.  AN OVERVIEW OF TAGUCHI METHOD AND NEWLY DEVELOPED STATISTICAL METHODS FOR ROBUST DESIGN , 1992 .

[10]  Indranil Gupta,et al.  Exploring the Energy-Latency Trade-Off for Broadcasts in Energy-Saving Sensor Networks , 2005, 25th IEEE International Conference on Distributed Computing Systems (ICDCS'05).