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Optimizing the Routing of Wireless Sensor Networks for Obstacles-avoidance

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
A. H. Mohamed, A. M. Nassar

A H Mohamed and A M Nassar. Optimizing the Routing of Wireless Sensor Networks for Obstacles-avoidance. International Journal of Computer Applications 170(8):20-24, July 2017. BibTeX

	author = {A. H. Mohamed and A. M. Nassar},
	title = {Optimizing the Routing of Wireless Sensor Networks for Obstacles-avoidance},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {170},
	number = {8},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {20-24},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017914927},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In the recent years, wireless sensor networks (WSNs), have become essential part in a huge number of the modern applications. Researchers have developed a lot of work to improve their performance. But, practically WSNs still face with different kinds of obstacles those cause main challenges for their reliability. Therefore, finding an optimum obstacle-avoiding route path for the WSNs is considered an important research problem. The present work introduces a new optimum routing algorithm based on the cluster-based method for the WSNs with obstacles. The proposed system uses the cluster-based method and the mobile sink to decrease the power consumptions and increase the lifetime of the WSNs. Besides, it uses the genetic algorithm to optimize the avoiding-obstacles routing path. Suggested system has been applied for a WSN used to communicate between a discovery-radiation robot and its operating system as a case of study. Simulation results for the tested WSN and their comparison with three other route algorithms have proved the effectiveness of the proposed novel method.


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Wireless sensor networks, obstacles, energy-efficient routing, cluster-based, genetic algorithm.