New methods of routing for the reduction of energy consumption in wireless sensor network

Journal Title: Scientific Journal of Review - Year 2015, Vol 4, Issue 10

Abstract

Wireless sensor network consist of some nodes. Each node is responsible for gathering environment data and sending it to BS in order for received data to be analyzed. One of the main problems of this kind of network is the little primary energy of nodes and the little space of node memories. Each time data is sensed, node energy is reduced. Continuation of this situation results in the reduction of network lifetime or death. Suitable methods are presented for data transfer from nodes to BS. These methods have been able to optimize energy consumption in comparison with similar previous methods. One of the methods of acceptable optimization of energy consumption and network lifetime is the use of genetic algorithm in the network process of routing. Each method makes to using of different parameters that these parameters have created strengths and weaknesses. In this research, we present useful solutions for the reduction of energy consumption in network by the use of genetic algorithm. The main idea is to consider the methods proposed in recent years. The simulation results of creditable essays have been used to show the strong and weak parts of presented methods. Then, optimization solutions have been proposed by the use of simulation results and the weaknesses of existing methods.

Authors and Affiliations

A. A. Baradaran*| Member of Department of Computer Science, Payame Noor University, Kashan, Iran., H. Qamsarizadeh| Student of Department of Computer Science, Azad University (Kashan branch), Kashan, Iran., H. Heidari| Student of Department of Computer Science, Azad University (Kashan branch), Kashan, Iran.

Keywords

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  • EP ID EP214
  • DOI 10.14196/sjr.v4i10.1925
  • Views 513
  • Downloads 33

How To Cite

A. A. Baradaran*, H. Qamsarizadeh, H. Heidari (2015). New methods of routing for the reduction of energy consumption in wireless sensor network. Scientific Journal of Review, 4(10), 165-181. https://europub.co.uk./articles/-A-214