Implementation and comparative analysis of evolutionary algorithms for energy optimization in wireless sensor networks

Kundaliya, Brijesh; Hadia, Sarman K.

doi:10.1002/dac.4787

Cited by 4 publications

(2 citation statements)

References 34 publications

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“…In this scheme, genetic algorithm is introduced to optimize the optimization problem, which can overcome the shortcoming of global searching ability of simulated annealing algorithm. At the same time, the advantages of fast convergence speed and strong local search ability of simulated annealing algorithm are introduced, so as to realize the intelligent optimization scheme [6][7][8] .…”

Section: Algorithm Introductionmentioning

confidence: 99%

Application of intelligent algorithm in wireless sensor network node deployment optimization

2024

jeis

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Wireless sensor network is a self-organizing network composed of a large number of nodes with sensing, computing and communication capabilities. It collaboratively senses, collects and processes the information of the sensing objects in the coverage area of the network, and sends the information through self-organizing to replace some manual sensing and processing work, and finally realizes the monitoring of the sensing area. Node deployment is an important research topic in wireless sensor networks. This paper first analyzes the characteristics and difficulties of the node deployment optimization problem, and then elaborates the application of intelligent algorithm in the node deployment optimization of wireless sensor networks.

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Section: Algorithm Introductionmentioning

confidence: 99%

Application of intelligent algorithm in wireless sensor network node deployment optimization

2024

jeis

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“…9,10 Researchers show more interest in routing mechanisms by considering the diverse aspects of routing that include single path, multi-path, multi-hop, quality-oriented, and so on with traditional and optimization approaches. 2,7,11 For example, in EPSO-CEO, 12 the authors proposed an energy-efficient method using an optimization approach for the CH selection and inter-cluster routing using multi-hop protocol. Likewise, in KDUCR, 13 the authors proposed an algorithm considering k-means and Dijkstra's algorithm to reduce the energy consumption and transmit the data to sink node.…”

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confidence: 99%

A novel approach on energy‐efficient clustering protocol for wireless sensor networks

Zachariah

Kuppusamy

2022

Int J Communication

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Summary Wireless sensor networks are group of nodes capable enough to communicate with other nodes wherever they are deployed. The demanding need for a wireless sensor network in various fields of monitoring and tracking has gained more popularity in recent years. However, as sensor nodes have limited and dissipating battery power, energy conservation is a critical challenge in wireless sensor networks. Clustering is one of the promising methodologies to reduce the consumption of energy. This paper presents a cluster‐based routing algorithm for transferring the data to the base station. The algorithm uses the k‐means approach to select the clusters. Each cluster consists of two cluster heads, one for aggregating the data and the other for data transmission; thereby, they share the load and improve the network lifetime. The data are sent to the base station by a multi‐hop approach. For energy efficiency, a minimum cost path is chosen by considering the energy and distance. Simulations are implemented in NS2. The results obtained show that the proposed protocol is more efficient than the benchmarked algorithms in network lifetime, packet delivery ratio, throughput, total energy consumption, and end to end delay.

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A blockchain‐based resilient and secure framework for events monitoring and control in distributed renewable energy systems

Faheem,

Raza,

Bhutta

et al. 2024

IET Blockchain

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The rapid and green energy transition is essential to deal with the fast‐growing energy needs in both public and industrial sectors. This has paved the way to integrate distributed renewable energy resources () such as solar, hydro, wind, and geothermal into the power grid (). Wind and solar are free, zero‐carbon emission, and everlasting power sources that contribute 5% and 7% of global electricity generation, respectively. Therefore, the fast, secure, and reliable integration of these green is critical to achieve the instant energy demands. Smart grid due to inherited characteristics such as intelligent sensing, computing, and communication technologies can effectively integrate the . However, the existing smart grid communication architecture faces various cyberattacks, resulting in poor integration, monitoring, and control of . In this respect, blockchain technology can provide fast, secure, and efficient end‐to‐end communication between in the smart grid. In this study, the authors propose a blockchain‐based resilient and secure scheme called for wireless sensor networks ‐based events monitoring and control in . Experimental studies and performance analyses are carried out to predict the efficiency of the proposed scheme by considering numerous standard metrics. The extensive numerical results demonstrated that the proposed scheme is significant in terms of secure, resilient, and reliable information transmission for in .

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Implementation and comparative analysis of evolutionary algorithms for energy optimization in wireless sensor networks

Cited by 4 publications

References 34 publications

Application of intelligent algorithm in wireless sensor network node deployment optimization

Application of intelligent algorithm in wireless sensor network node deployment optimization

A novel approach on energy‐efficient clustering protocol for wireless sensor networks

A blockchain‐based resilient and secure framework for events monitoring and control in distributed renewable energy systems

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