Self-Identification of Boundary’s Nodes in Wireless Sensor Networks


Kouider Elouahed Moustafa, Haffaf Hafid, Journal of Information Processing Systems Vol. 13, No. 1, pp. 128-140, Feb. 2017  

10.3745/JIPS.03.0062
Keywords: Boundary Recognition, Military Applications, Military Surveillance, Wireless Sensor Network
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Abstract

The wireless sensor networks (WSNs) became a very essential tool in borders and military zones surveillance, for this reason specific applications have been developed. Surveillance is usually accomplished through the deployment of nodes in a random way providing heterogeneous topologies. However, the process of the identification of all nodes located on the network’s outer edge is very long and energy-consuming. Before any other activities on such sensitive networks, we have to identify the border nodes by means of specific algorithms. In this paper, a solution is proposed to solve the problem of energy and time consumption in detecting border nodes by means of node selection. This mechanism is designed with several starter nodes in order to reduce time, number of exchanged packets and then, energy consumption. This method consists of three phases: the first one is to detect triggers which serve to start the mechanism of boundary nodes (BNs) detection, the second is to detect the whole border, and the third is to exclude each BN from the routing tables of all its neighbors so that it cannot be used for the routing.


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Cite this article
[APA Style]
Moustafa, K. & Hafid, H. (2017). Self-Identification of Boundary’s Nodes in Wireless Sensor Networks. Journal of Information Processing Systems, 13(1), 128-140. DOI: 10.3745/JIPS.03.0062.

[IEEE Style]
K. E. Moustafa and H. Hafid, "Self-Identification of Boundary’s Nodes in Wireless Sensor Networks," Journal of Information Processing Systems, vol. 13, no. 1, pp. 128-140, 2017. DOI: 10.3745/JIPS.03.0062.

[ACM Style]
Kouider Elouahed Moustafa and Haffaf Hafid. 2017. Self-Identification of Boundary’s Nodes in Wireless Sensor Networks. Journal of Information Processing Systems, 13, 1, (2017), 128-140. DOI: 10.3745/JIPS.03.0062.