Date of Publication :12th April 2018

Abstract: WSNs are composed of hundreds or thousands of sensor nodes which are deployed either inside the phenomena to be observed or very close to it. These sensor nodes are responsible for collecting & processing and routing data either to other sensor nodes or directly to a base station (BS). In most of the applications, sensor nodes are deployed in a random & uncontrolled manner. These uncontrolled deployment methods cause the random distribution of nodes, i.e., node density is not uniform in the area under consideration. In WSNs, for which designing of protocols is application specific, focus on a single isolated technique cannot lead to optimum levels of energy efficiency, scalability and improved network lifetime. Consequently, exploring several energy efficient and scalable mechanisms that address several different characteristics of the network can help in contributing significant improvements in the various network performance metrics (energy efficiency, scalability, load balancing, network lifetime, overheads, delay, and throughput). The other goal of the paper is to propose an application of computational intelligence-based approaches such as Ant colony optimization which manages WSN characteristics.

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