A Distributed Multi-competitive Clustering Approach for Wireless Sensor Networks

Jia, Ya; Zhang, Chiyu; Liang, Kangwu

doi:10.1007/s10776-017-0353-4

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…Reference [15] limits the distance between two CHs to evenly distribute the CHs. However, all clusters have the same size in this approach, so it is not applicable for large WSNs.…”

Section: Related Workmentioning

confidence: 99%

“…where d is the transmission distance. E elec , ε fs , ε mp , and d corssover are constants, where E elec is the energy dissipated per bit to run the transceiver circuitry, ε fs is the amplifier energy parameters corresponding to the free space channel model, ε mp is the amplifier energy parameters corresponding to the multipath channel mode, and d corssover is the distance threshold [15]. e values of experiment are shown in Table 1.…”

Section: Network and Energy Consumption Modelmentioning

confidence: 99%

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A Competition-Based Unequal Clustering Multihop Approach for Wireless Sensor Networks

Liu

et al. 2021

Security and Communication Networks

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The energy efficiency and stability of wireless sensor networks (WSNs) have always been a hot issue in the research. Clustering is a typical architecture for WSNs, and cluster heads (CHs) play a vital role. Unreasonable CH selection causes a lot of energy consumption. In this paper, we propose a competition-based unequal clustering multihop approach (CUCMA). CHs are selected by competition. First, the cluster radius (CR) of a node is calculated according to the distance to base station (BS). Then, CR is resized based on the number of around nodes. Only the nodes with high residual energy and appropriate distances to the selected CHs maybe become CHs, which are usually closer to the surrounding nodes. CUCMA and four related approaches are simulated in different scenarios. The results are analyzed, and it is proved that CUCMA balances the energy consumption of the CHs and reduces the energy consumption of the whole networks, thus leading to prolong the lifetime of WSNs.

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“…Reference [15] limits the distance between two CHs to evenly distribute the CHs. However, all clusters have the same size in this approach, so it is not applicable for large WSNs.…”

Section: Related Workmentioning

confidence: 99%

Section: Network and Energy Consumption Modelmentioning

confidence: 99%

A Competition-Based Unequal Clustering Multihop Approach for Wireless Sensor Networks

Liu

et al. 2021

Security and Communication Networks

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“…We use first order wireless communication model to calculate the energy consumption [7]. (1) Where, l is data sending or receiving whose unit is bit, d is Communication distance.…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…Suppose that the distance between i and a node in its cluster is m. The expectation of m2 is [7]. The number of nodes in the circle with a radius of Ri and a center of i is ni and the average value of ni is nave.…”

Section: Proposed Algorithmmentioning

confidence: 99%

An Unequal Clustering Algorithm with Load Balance for Wireless Sensor Networks

Jia¹,

Liang²,

Zhang³

2018

Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)

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Abstract-Good clustering algorithm can effectively reduce the energy consumption of a wireless sensor network (WSN). The random in clustering will reduce the performance of clustering algorithm. Aiming at this problem, this paper proposes an unequal clustering algorithm with load balance (UCLB) for WSN. UCLB is a multi-hop algorithm and divides the nodes into clusters of different sizes. Considering the two objectives of load balancing and reducing energy consumption, UCLB elects cluster heads according to a cost parameter that is calculated by the number of around nodes and the distances to these nodes. UCLB preferentially select the node with moderate distances to the elected cluster heads as cluster head to distribute cluster heads evenly in networks. Simulation results show that the algorithm can effectively reduce the network energy consumption and prolong the network lifetime.

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Integrated Energy and Trust-Based Semi-Markov Prediction for Lifetime Maximization in Wireless Sensor Networks

Famila¹,

Jawahar²,

Vimalraj³

et al. 2021

Wireless Pers Commun

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A Distributed Multi-competitive Clustering Approach for Wireless Sensor Networks

Cited by 6 publications

References 13 publications

A Competition-Based Unequal Clustering Multihop Approach for Wireless Sensor Networks

A Competition-Based Unequal Clustering Multihop Approach for Wireless Sensor Networks

An Unequal Clustering Algorithm with Load Balance for Wireless Sensor Networks

Integrated Energy and Trust-Based Semi-Markov Prediction for Lifetime Maximization in Wireless Sensor Networks

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