An Improved BAT-Optimized Cluster-Based Routing for Wireless Sensor Networks

Seelam, Koteswararao; Sailaja, M.; Madhu, T.

doi:10.1007/978-81-322-2268-2_13

Cited by 10 publications

(6 citation statements)

References 19 publications

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“…A typical WSN is constructed using the FCEEC algorithm to validate the energy efficiency and packet delivery across CH and e simulation results are compared with LEACH [27], LEACH-C [28], BO-LEACH [29], and ESD [30] algorithms. e authors have considered the following design parameters which are as listed in Table 1.…”

Section: Resultsmentioning

confidence: 99%

Wireless Sensor Network Cluster Head Selection and Short Routing Using Energy Efficient ElectroStatic Discharge Algorithm

Jagan

Jayarin²

2022

Journal of Engineering

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Wireless sensor networks attract so much attention in current IoT-enabled industrial and domestic applications having either homogeneous or heterogeneous sensors deployed to acquire information of intent. WSNs are designed to operate using self-powered sensor nodes as their choice of application is geographic critical. Such nodes must support energy efficiency so that network longevity becomes high. Cluster head selection plays a crucial stage in a WSN architecture which mainly focuses on the minimization of network energy consumption. It groups sensor nodes in such a way that a sophisticated network cluster is formed to have enhanced life time besides a low power consumption. A popular clustering technique, known as LEACH and its variants, is found to be energy efficient compared to its counterparts. The authors propose a novel fully connected energy efficient clustering (FCEEC) mechanism using the electrostatic discharge algorithm to establish a fully connected network with shortest path routing from sensor nodes (SNs) to cluster head (CH) in a multihop environment. The proposed electrostatic discharge algorithm (ESDA) enhances network life time while attaining energy efficient full connectivity between sensor nodes. As a result of ESD, the dead node count is reduced significantly so that the network longevity is increased. In the end, simulation results exhibited improved performance metrics such as energy efficiency, dead node count, packet delivery, and network latency compared to certain conventional CH selection approach.

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Section: Resultsmentioning

confidence: 99%

Wireless Sensor Network Cluster Head Selection and Short Routing Using Energy Efficient ElectroStatic Discharge Algorithm

Jagan

Jayarin²

2022

Journal of Engineering

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“…Different evolutionary techniques, such as: Harmony Search Algorithm (HS), Ant Colony Algorithm, BAT Algorithm (BA), and Genetic Algorithm (GA) have been used to optimize the clustering algorithms by finding the optimal number of CHŝ aȂŞand therefor the number of clusters-in the WSN. The simulation results compared to the traditional algorithms and demonstrated noticeable improvements in power consumption, network life time, and network coverage [15] [4].…”

Section: Related Workmentioning

confidence: 99%

Evolutionary Clustering for Integrated WSN-RFID Networks

Hamza

Amir

2016

Proceedings of the 10th International Conference on Informatics and Systems

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Emerging practical deployments for the Internet of Things (IoT) trigger a need to integrate and inter-operate a variety of heterogenous networks to realize real business values. Several applications require the integration of wireless sensor networks (WSN), WiFi, and Radio Frequency Identifiers (RFID) into one single network to fulfil business requirements. As most of such deployments are characterized as being large-scale and heterogeneous, special algorithms and techniques are needed in order to deal with data collection, processing, and transmission in such networks. Results reported in the literature confirm that clustering techniques can be very efficient in dealing with routing in large-scale networks. However; due to the heterogeneity of IoT networks, the use of conventional clustering techniques may not result in an efficient clustering. Accordingly, in this paper, we attempt to address this problem by studying the use of evolutionary clustering algorithms in integrated WSN-RFID networks. In particular, the performance of two evolutionary algorithms; namely the Genetic Algorithms (GA) and the Harmony Search (HS), is analyzed and compared. It is shown that, the GA outperforms the HS significantly in the cluster formation process for integrated WSN-RFID networks. CCS Concepts•Networks → Network design and planning algorithms;

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“…The well-known (LEACH) algorithm has been optimized with BAT algorithm [33] to be used for clusters formation and CH selection. Pipelining is used for packet scheduling which either increases clock speed (sampling speed) or reduces power consumption at the same speed in a digital signal processor (DSP) system.…”

Section: 72mentioning

confidence: 99%

Evolutionary Algorithms for Clustering in Wireless Sensor Networks

Hamza

Amir

2017

Journal of Al-Azhar University Engineering Sector

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Recent studies have shown that hierarchical routing is one of the best approaches for routing in Wireless Sensor Networks (WSN). In typical hierarchical routing techniques, the network divided into regions (a.k.a. Clusters); each cluster is then managed as a standalone network with its Cluster Head serving as the node of communication coordination and data collection. Accordingly, nodes across the network can save their energy when attempting to communicate with the other nodes far across the network. Several hierarchical routing techniques have been proposed over the last few years, despite the fact that most of these algorithms are fundamentally similar. Due to the nature and complexity of hierarchical routing, Evolutionary Optimization algorithms have been used recently to perform clustering and routing techniques. In this paper, we present, to the best of our knowledge, one of the first surveys on the use of Evolutionary Algorithms (EA) for clustering in hierarchical routing in WSNs. Categorization and classification of the various clustering techniques are presented and used to understand the existing algorithms. A comparison among these techniques is also presented in this work.

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An Improved BAT-Optimized Cluster-Based Routing for Wireless Sensor Networks

Cited by 10 publications

References 19 publications

Wireless Sensor Network Cluster Head Selection and Short Routing Using Energy Efficient ElectroStatic Discharge Algorithm

Wireless Sensor Network Cluster Head Selection and Short Routing Using Energy Efficient ElectroStatic Discharge Algorithm

Evolutionary Clustering for Integrated WSN-RFID Networks

Evolutionary Algorithms for Clustering in Wireless Sensor Networks

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