Reliability Analysis for Wireless Sensor Networks Considering Environmental Parameters Using MATLAB

Doohan, Nitika Vats; Mishra, Durgesh Kumar; Tokekar, Sanjiv

doi:10.1109/cicsyn.2011.32

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…packet delivery ratio [23] and message delay [24,25]. Parameters such as link and node failure rates, environmental parameters such as noise, pressure, and temperature in [26] have been considered for developing efficient reliability of WSN. To obtain the network reliability of the overall system for communication purposes, it is essential to develop a network having a smaller number of links.…”

Section: Related Workmentioning

confidence: 99%

Disjoint Spanning Tree Based Reliability Evaluation of Wireless Sensor Network

Lata

Mehfuz

Urooj

2020

Sensors

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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.

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Section: Related Workmentioning

confidence: 99%

Disjoint Spanning Tree Based Reliability Evaluation of Wireless Sensor Network

Lata

Mehfuz

Urooj

2020

Sensors

View full text Add to dashboard Cite

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“…With major advances in the development of wireless sensor networks (WSNs) and on account of their features such as their low cost, easy installation, wide range and high safety, many experimental and commercial deployments are taking place in recent years [1,2]. WSNs are widely used in various applications such as military surveillance, agriculture monitoring and emergency rescue.…”

Section: Introductionmentioning

confidence: 99%

Energy‐efficient network design via modelling: optimal designing point for energy, reliability, coverage and end‐to‐end delay

Ansari¹,

Mahani²,

Kavian

2013

IET Networks

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Considering that practical wireless sensor networks are mostly built upon energy-constrained sensor nodes, network lifetime becomes a key deployment factor for sustainability of such networks initiating an attempt for prolonging the lifetime. Adopting a new multi-mode switching protocol for sensor nodes between active and sleep states, in this study, the authors propose a new mathematical method using an embedded simulation-based computing of an energy-efficient strategy performance metric to maintain resiliency of the network against side effects appearing in duty-cycling protocols. Here, the authors use a Monte Carlo simulation to estimate network reliability. Then the proposed mathematical model enables us to build a decision for optimised performance upon trade-offs between consumed energy, reliability, coverage intensity and endto-end delays by locating a network's operational points. The authors show the trade-off operational significance of the model against the percentage of sleeping probability via some design factors including figure of merit. † Sleep probability p s, † Node density σ, † Number of neighbour nodes n − 1=πr 2 σ, † The non-empty probability (the node's queue is non-empty) in which lead to packet transmission is τ. According to our previous work [16], the wireless channel at any moment is in one of the following states: † idle state (S i), † collision state (S c), † successful transmission state (S s). Fig. 1 Sample graph to show two-terminal reliability computation www.ietdl.org

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“…For computation of reliability the probability of link existence and failure rate of node are not only considered but also reliability of a node depends on various environmental parameters such as noise, temperature, pressure and magnetic effects are also considered. The development of reliability model needs to take in account all of these parameters [31].…”

Section: Classification Of Reliability Modeling and Evaluationmentioning

confidence: 99%

A Survey on Modeling and Enhancing Reliability of Wireless Sensor Network

Venkatesan¹,

Shanmugavel²,

Subramaniam³

2013

WSN

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Design of reliable wireless sensor network (WSN) need to address the failure of single or multiple network components and implementation of the techniques to tolerate the faults occurred at various levels. The issues and requirements of reliability improvement mechanism depend on the available resources and application for which the WSN is deployed. This paper discusses the different modeling approaches to evaluate the reliability and classification of the approaches to improve it. Also the paper analyzes reliability enhancement by existing fault tolerant methods in WSN and compares the performance of these techniques with the technique we developed. From the results of the analysis we highlight the challenges and the characteristics of the sensor network affects the reliability and give some scope of future research directions in order to enhance reliability.

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Reliability Analysis for Wireless Sensor Networks Considering Environmental Parameters Using MATLAB

Cited by 4 publications

References 12 publications

Disjoint Spanning Tree Based Reliability Evaluation of Wireless Sensor Network

Disjoint Spanning Tree Based Reliability Evaluation of Wireless Sensor Network

Energy‐efficient network design via modelling: optimal designing point for energy, reliability, coverage and end‐to‐end delay

A Survey on Modeling and Enhancing Reliability of Wireless Sensor Network

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