Abstract
Route selection using optimal nodes in Wireless Sensor Network (WSN) is a prominent task to improve network performance without deterioration. Intrinsic characteristics of the node, network traffic are some of the reason where routing algorithms fail to prove their consistency. In such cases, the conventional routing schemes must be equipped with additional network management features to retain network performance. This manuscript proposes a Heuristic Local Search (HLS) algorithm for improving routing efficiency of WSN. This search algorithm is backboned by clustering process; the cluster head is elected by satisfying balanced network metrics: energy and distance. Congestion preventive routing considers the same objective function in selecting an outside intermediate node that mitigates packet loss due to congestion. Implication of similar objective function under different constraints streamlines routing and prolongs the operation period of the cluster head. The process of the proposed HLS is evaluated using extensive simulation for the metrics: throughput, network lifetime, cluster head changes, energy utilization and packet loss ratio.
Highlights
Wireless Sensor Network (WSN) integrates a wide-range of sensors that gathers information from the environment and conveys to a sink node [1]
The structured approach is further classified as hierarchy based and ring based b) unstructured approach are independent which is applicable to any network topology and routing protocols
EAP forms a spanning tree using all the cluster heads the root node communicates to the sink in one-hop, energy consumed in free space is less
Summary
The contributions of the manuscript are as follows: i. Design of an objective based clustering process for improving cluster stability and prolonging the operation time of the cluster head. The factors distance and energy are considered for satisfying the defined objective function. Congestion Preventive routing process wherein the traffic concentrated routes are identified and failures are repaired by redirecting the transmission. The same objective for identifying cluster head is used to identify intermediate node to minimize computational complexity. Performance assessment of the proposed algorithm through appropriate simulations for verifying the consistency of the proposed algorithm. The simulation results and their description demonstrate the likelihood of the proposed algorithm
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