MSoC: Multi-scale Optimized Clustering for Energy Preservation in Wireless Sensor Network

Jyothi, A. P.; Usha, S.

doi:10.1007/s11277-019-06146-y

Cited by 14 publications

(5 citation statements)

References 20 publications

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“…New WSN routing methods in Ref. [9] ensure that all nodes have a stable supply of power, resulting in longer network lifespans. The suggested technique creates virtual regions, each with a cluster head node.…”

Section: Related Workmentioning

confidence: 99%

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Meenakshi,

Ahmad,

Prabu

et al. 2024

Tsinghua Sci. Technol.

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The Wireless Sensor Network (WSN) is a network that is constructed in regions that are inaccessible to human beings. The widespread deployment of wireless micro sensors will make it possible to conduct accurate environmental monitoring for a use in both civil and military environments. They make use of these data to monitor and keep track of the physical data of the surrounding environment in order to ensure the sustainability of the area. The data have to be picked up by the sensor, and then sent to the sink node where they may be processed. The nodes of the WSNs are powered by batteries, therefore they eventually run out of power. This energy restriction has an effect on the network life span and environmental sustainability. The objective of this study is to further improve the Engroove Leach (EL) protocol's energy efficiency so that the network can operate for a very long time while consuming the least amount of energy. The lifespan of WSNs is being extended often using clustering and routing strategies. The Meta Inspired Hawks Fragment Optimization (MIHFO) system, which is based on passive clustering, is used in this study to do clustering. The cluster head is chosen based on the nodes' residual energy, distance to neighbors, distance to base station, node degree, and node centrality. Based on distance, residual energy, and node degree, an algorithm known as Heuristic Wing Antfly Optimization (HWAFO) selects the optimum path between the cluster head and Base Station (BS).They examine the number of nodes that are active, their energy consumption, and the number of data packets that the BS receives. The overall experimentation is carried out under the MATLAB environment. From the analysis, it has been discovered that the suggested approach yields noticeably superior outcomes in terms of throughput, packet delivery and drop ratio, and average energy consumption.

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Section: Related Workmentioning

confidence: 99%

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Meenakshi,

Ahmad,

Prabu

et al. 2024

Tsinghua Sci. Technol.

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“…This algorithm uses a particle swarm optimization algorithm to minimize the energy consumption in WSNs. In [33][34][35][36], it was suggested to use genetic algorithms to optimize cluster head selection for single and multiple data sinks in heterogeneous wireless sensor networks. To increase lifetime using MADM approaches, multiple parameter-based energy balanced and optimized clustering for WSN was proposed [34].…”

Section: Related Workmentioning

confidence: 99%

Multi-Objective Clustering Algorithm using Ordered Weighted Averaging (OWA) Operator for Heterogeneous WSN

Rajpoot,

Avtar,

Pandey

et al. 2023

Preprint

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Wireless Sensor Networks have become a vast field of study. In the past few years, it has been seen that the use of wireless sensor networks in various fields, such as health monitoring, landslide detection, agriculture field, etc., is increased. In such real-life applications, many sensor nodes are required for monitoring and collecting data from the environment, and these sensor nodes work autonomously. The network of complete sensor nodes that works on an application is termed WSN. In a WSN, clustering refers to dividing the sensor nodes into several groups called clusters. A cluster head is selected among all clusters, temporarily acting as the particular cluster's base station. This cluster head is chosen based on several factors, including the node's residual energy, distance from the base station, and distance from other sensor nodes. Mainly the cluster head is responsible for increasing the efficiency and scalability of the entire network. Utilizing the Ordered Weighted Averaging (OWA) operator, we have suggested an algorithm for cluster head selection that works better and uses less energy during data transmission. Simulation results showed that our suggested algorithm outperforms others and extends network lifetime by 5–12%.

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“…Apart from this, energy will be required to be reduced in a highly deterministic way irrespective of whatever is the degree of successful clustering operation in WSN. Therefore, the proposed study will be a continuation of our prior work where such problems are addressed. Hence, the research problem arrived is “To develop an effective topology control system as an outcome of energy efficient cluster optimization scheme in WSN.” The next section briefs of the proposed solution in the form of research methodology to address this research problem.…”

Section: Research Problemmentioning

confidence: 99%

Interstellar‐based topology control scheme for optimal clustering performance in WSN

Jyothi

Usha

2020

Int J Communication

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Summary Clustering is one of the essential operations in wireless sensor network (WSN) to ensure organized data aggregation followed by energy efficiency. However, obtaining optimal clustering performance is yet an unsolved problem in WSN. Review of existing approaches towards cluster optimization shows that effective balance between energy efficiency and topology control is still missing. Therefore, the proposed system presents a unique topology control mechanism using a novel concept of interstellar orientation toward optimizing the clustering performance in WSN. Adopting an analytical research methodology, the proposed system introduces two interstellar‐based topology control system, which targets the maximum saving of resource consumption of the cluster head. The simulated outcome of the study shows that the proposed topology control system offers significant energy conservation performance in comparison to the existing hierarchical clustering scheme in WSN.

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MSoC: Multi-scale Optimized Clustering for Energy Preservation in Wireless Sensor Network

Cited by 14 publications

References 20 publications

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

Multi-Objective Clustering Algorithm using Ordered Weighted Averaging (OWA) Operator for Heterogeneous WSN

Interstellar‐based topology control scheme for optimal clustering performance in WSN

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