Base-station controlled clustering scheme in wireless sensor networks

Manjula, S H; Reddy, E.B.; Shaila, K; Nalini, L.; Venugopal, K. R.; Patnaik, L M

doi:10.1109/wd.2008.4812856

Cited by 11 publications

(7 citation statements)

References 8 publications

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“…Manjula et al. [14], introduced LEACH‐CE in which 5% of the live nodes are CHs. Before the selection of the CHs begins, 10% of the nodes are forced to go into the sleep mode by the BS.…”

Section: Related Workmentioning

confidence: 99%

“…Results have shown that if TL-LEACH is deployed, the number of rounds consumed when the first node dies (FND) and the last node dies (LND) is approximately 200 and 500 more than that when the LEACH is used respectively. Manjula et al [14], introduced LEACH-CE in which 5% of the live nodes are CHs. Before the selection of the CHs begins, 10% of the nodes are forced to go into the sleep mode by the BS.…”

Section: Related Workmentioning

confidence: 99%

“…Loscri et al[13] � Deploys two levels of CHs � Primary CHs communicate to sink directly � Secondary CHs communicate to sink via primary CHs Two-hop � Reduce energy consumption � Reduce the number of nodes need to send data to sink Manjula et al[14] � Nodes randomly selected to go to sleep mode. Simulated annealing algorithm is used to select the CHs in the first round.…”

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confidence: 99%

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A new energy aware cluster head selection for LEACH in wireless sensor networks

Pour

Javidan

2021

IET Wireless Sensor Systems

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Internet of Things (IoTs) as a new network pattern for the intelligent world usually uses wireless sensor networks (WSNs) as a perception layer which consisted of numerous number of sensor nodes scattered in the environment to gather intended information. The selected information then is sent to a base station (BS) to be sent to cloud server for further processing. Since the energy of sensor nodes is limited, the most significant challenge in these networks is reducing the energy consumption of the network. It is proved that dividing the network to clusters can significantly reduce the energy consumption. One of the most popular clustering protocols in WSNs is the Low-Energy Adaptive Clustering Hierarchy (LEACH). In this protocol, cluster heads (CHs) are selected randomly which results in poor performance in real scenarios. In this article, a new energy aware CH selection algorithm is proposed which selects CHs based on the residual energy, the position and centrality of nodes. It uses a variable range upon which the centrality and the number of neighbours of each node are calculated. Simulation results show that the proposed algorithm outperforms LEACH, Multi-hope Routing with LEACH (MR-LEACH) and Enhanced Multi-hop LEACH (EM-LEACH) in terms of reducing energy consumption, increasing network lifetime and improving network reliability.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Manjula et al. [14], introduced LEACH‐CE in which 5% of the live nodes are CHs. Before the selection of the CHs begins, 10% of the nodes are forced to go into the sleep mode by the BS.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

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A new energy aware cluster head selection for LEACH in wireless sensor networks

Pour

Javidan

2021

IET Wireless Sensor Systems

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“…In [17], LEACH-CCB protocol had been proposed where, 5% of alive nodes are elected as cluster heads in the network . The status message from member nodes is sent only once during the first round, during remaining rounds the energy is estimated with the known parameters like cluster heads, cluster member count, number of frames in the round etc.…”

Section: Related Workmentioning

confidence: 99%

Improving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networks

Raval¹,

Bhavsar²

2015

IJCA

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In this paper an energy usage estimation technique (LCEFCM) has been proposed which employs the Fuzzy C-Means clustering for creating clusters in the Wireless Sensor Networks. LCEFCM reduces the energy consumption considerably compared to other clustering methods like simulated annealing and K-Means clustering. It applies the dynamic clustering mechanism combined with balanced clustering method. LCEFCM outperforms LEACHC, LEACHC Estimate(LCE) and LCEKMeans for various performance measuring factors like network lifetime, data received, alive nodes etc.

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“…In [8], [9], nodes with high density and more remaining energy than the average energy are selected as CHs. LEACH-CCB [10] improves LEACH-CE [11] by avoiding frequent communications of the nodes with the BS and by making certain percent of nodes into sleep at every round. In pLEACH [12], BS selects node with more residual energy as CH in each sector and the current residual energy value of each node is added in the data packet to be sent to BS instead of sending it separately after each round which increases the data overload.…”

Section: Introductionmentioning

confidence: 99%

An approach to improved energy efficient hybrid clustering in wireless sensor networks

Patra

Chouhan

2014

2014 International Conference on Signal Processing and Communications (SPCOM)

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In wireless sensor networks (WSNs), hierarchical clustering approach gives an efficient solution to achieve the goal of maximizing the network lifetime by minimizing energy utilization. In this paper, we introduce a cluster head (CH) selection process and cluster formation algorithm by re-selection of CHs called Improved Energy Efficient Hybrid Clustering Scheme (IEEHCS). In the proposed scheme, energy efficient CHs are selected by a centralized algorithm based on remaining energy, node density and minimum separation distance to reduce the control message overheads. The key idea is that the CH role is repeated with the same settings or shifted to a eligible member nodes instead of re-clustering the whole network at every round. In this way, IEEHCS reduces the frequency of updating CHs, avoids unnecessary re-clustering in every round and saves significant amount of node energy. Simulation results demonstrate that IEEHCS effectively reduces the energy consumption and prolongs the network lifetime for first node death upto 45.39% and 11.36% over LEACH-C and EEHCS, respectively, in certain network settings.

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Base-station controlled clustering scheme in wireless sensor networks

Cited by 11 publications

References 8 publications

A new energy aware cluster head selection for LEACH in wireless sensor networks

A new energy aware cluster head selection for LEACH in wireless sensor networks

Improving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networks

An approach to improved energy efficient hybrid clustering in wireless sensor networks

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