Disjoint Spanning Tree Based Reliability Evaluation of Wireless Sensor Network

Abstract

Wireless sensor networks (WSNs) are becoming very common in numerous manufacturing industries; especially where it is difficult to connect a sensor to a sink. This is an evolving issue for researchers attempting to contribute to the proliferation of WSNs. Monitoring a WSN depends on the type of collective data the sensor nodes have acquired. It is necessary to quantify the performance of these networks with the help of network reliability measures to ensure the stable operation of WSNs. Reliability plays a key role in the efficacy of any large-scale application of WSNs. The communication reliability in a wireless sensor network is an influential parameter for enhancing network performance for secure, desirable, and successful communication. The reliability of WSNs must incorporate the design variables, coverage, lifetime, and connectivity into consideration; however, connectivity is the most important factor, especially in a harsh environment on a large scale. The proposed algorithm is a one-step approach, which starts with the recognition of a specific spanning tree only. It utilizes all other disjoint spanning trees, which are generated directly in a simple manner and consume less computation time and memory. A binary decision illustration is presented for the enumeration of K-coverage communication reliability. In this paper, the issue of computing minimum spanning trees was addressed and it is a pertinent method for further evaluating reliability for WSNs. This paper inspects the reliability of WSNs and proposes a method for evaluating the flow-oriented reliability of WSNs. Further, a modified approach for the sum-of-disjoint products to determine the reliability of WSN from the enumerated minimal spanning trees is proposed. The proposed algorithm when implemented for different sizes of WSNs demonstrates its applicability to WSNs of various scales. The proposed methodology is less complex and more efficient in terms of reliability.

Reliability analysis of complex networks based on irredundant subset cut group

“…The developed algorithms are coded in MATLAB 2013a, and implemented on an Intel(R) Core(TM) i3 CPU with Windows 7 operating system. The proposed methodology was applied on various benchmark networks available in Soh and Rai, 27 Soh et al, 28 and Lata et al 41 and obtained reliability value was exactly same which authenticates the correctness of the approach.…”

“…Since, the main problem in capacitated networks reliability evaluation is the generation of valid and non-redundant subset cut groups from the cutsets, this paper aims to provide an efficient solution of the problem. The proposed approach is compared with the methods available in Soh and Rai, 27 Soh et al, 28 and Lata et al 41 and compared as follows.…”

“…Benchmark networks taken from Lata et al 41 : (a) 6N9L network, (b) 8N12L network, (c) 7N1L network, (d) 7N14L network, (e) 6N8L network, and (f) 9N4L network.…”

“…The proposed framework have been implemented on various benchmark networks 41 with varying complexity of the networks. The results obtained are shown in Table 3.…”

MiA-CODER: A Multi-Intelligent Agent-Enabled Reinforcement Learning for Accurate Coverage Hole Detection and Recovery in Unequal Cluster-Tree-Based QoSensing WSN

“…Authors in [24] insist that the importance of reliability in the WSN and the connectivity between the nodes in the network is addressed. This is achieved by implementing a network topology-based approach in which the nodes in the network are constructed as a spanning tree which greatly reduces the link failure problem in the network.…”