Energy and Network Balanced Distributed Clustering in Wireless Sensor Network

Chowdhury, Srijit; Giri, Chandan

doi:10.1007/s11277-019-06137-z

Cited by 13 publications

(16 citation statements)

References 23 publications

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“…If there are too many CHs in the network, redundant CH nodes will consume more energy in the network. If the number of CH nodes in the network is too small, remote nodes will not be able to find suitable CHs to join, resulting in the loss of monitoring data and excessive network delay [25].…”

Section: Algorithm Design and Implementationmentioning

confidence: 99%

Hybrid PSO and Evolutionary Game Theory Protocol for Clustering and Routing in Wireless Sensor Network

Song

Liu

2020

Journal of Sensors

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Compared with traditional networks, WSNs have more limited resources such as energy, communication, computing, and storage. The problem of how to achieve energy saving, extend network life cycle, and improve network performance under these limited resources has always been an issue of great interest in WSN research. However, existing protocols do not consider that sensor nodes within the BS threshold may not be clustered. These nodes can directly transmit data to the BS. This simplifies the cluster routing process of the entire WSN and saves more energy. This paper introduces an efficient, and energy-efficient, clustering and equalization routing protocol called the PSOLB-EGT protocol. This protocol introduces a new approach by combining improved particle swarm optimization (PSO) and evolutionary game theory (EGT) algorithms to address the problem of maximizing the network lifetime. The operation of the wireless sensor network is divided into an initialization phase and a data transmission phase. In the initialization phase of the wireless sensor network, the improved PSO algorithm is used to establish clusters and select CHs in areas other than the BS threshold. Entering the data transmission phase, we analyze this problem from the perspective of game theory. We use improved noncooperative evolutionary game theory to build models to solve the problem of the energy waste caused by routing congestion. The proposed PSOLB-EGT protocol is intensively experimented with a number of topologies in various network scenarios, and the results are compared with the well-known cluster-based routing protocols that include the swarm intelligence-based protocols. The obtained results prove that the proposed protocol has increased 9%, 8%, and 5% compared with the ABC-SD protocol in terms of network life, network coverage, and amount of data transmitted, respectively.

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Section: Algorithm Design and Implementationmentioning

confidence: 99%

Hybrid PSO and Evolutionary Game Theory Protocol for Clustering and Routing in Wireless Sensor Network

Song

Liu

2020

Journal of Sensors

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“…The UPIoT contains numerous sensor nodes that communicate wirelessly and transmit data via self-organized multi-hop routing [10,11]. Due to their small size, the sensors generally have an upper limit on their energy storage.…”

Section: Overviewmentioning

confidence: 99%

“…Step 5: After preliminary clustering, judge if the node density of each cluster exceeds the pre-set threshold. If yes, adjust the communication radius of the cluster head by formula (11); otherwise, the cluster head will allocate the time slots for data transmission to the intra-cluster nodes.…”

Section: Endmentioning

confidence: 99%

Energy Efficiency Management and Route Optimization for Wireless Sensor Network under the Ubiquitous Power Internet of Things

Zhang¹

2019

EJEE

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The traditional routing algorithms for data transmission in the wireless sensor network (WSN) under the ubiquitous power Internet of Things (UPIoT) are faced with two common defects, namely, the imbalance between the nodes in energy consumption and the premature death of many nodes. To solve the problems, this paper puts forward a method to manage the energy efficiency and optimize the route for the WSN under the UPIoT. Firstly, an energy consumption model of network nodes was established after analyzing the causes of node energy loss, which effectively reduces the energy consumed by each node during the clustering process. Next, the author designed a way to compute node quality, and selected cluster heads by node quality, such that the energy consumption is balanced across the WSN. On this basis, a node clustering routing algorithm was presented to dynamically adjust the communication radii of cluster heads and general nodes, thus extending the lifecycle of the WSN under the UPIoT. The simulation results show that our method outperformed the traditional clustering routing algorithm in controlling energy loss of nodes and enhancing network reliability and stability. The research findings provide a valuable reference for the efficient data transmission of the WSN under the UPIoT.

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“…The existing clustering scheme could not still balance the trade‐off between computation and communication problem, and hence, it is yet an open‐end problem. Energy efficiency is another important term connected with every clustering approach . It is because maximum energy is drained by the cluster head cumulatively while performing data forwarding task to the base station.…”

Section: Introductionmentioning

confidence: 99%

“…Energy efficiency is another important term connected with every clustering approach. 17 It is because maximum energy is drained by the cluster head cumulatively while performing data forwarding task to the base station. There is no specific solution towards solving this energy efficiency problem in WSN.…”

Section: Introductionmentioning

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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Energy and Network Balanced Distributed Clustering in Wireless Sensor Network

Cited by 13 publications

References 23 publications

Hybrid PSO and Evolutionary Game Theory Protocol for Clustering and Routing in Wireless Sensor Network

Hybrid PSO and Evolutionary Game Theory Protocol for Clustering and Routing in Wireless Sensor Network

Energy Efficiency Management and Route Optimization for Wireless Sensor Network under the Ubiquitous Power Internet of Things

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

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