Coverage constrained non-uniform node deployment in wireless sensor networks for load balancing

Chatterjee, Punyasha; Das, Nabanita

doi:10.1109/aimoc.2014.6785530

Cited by 17 publications

(10 citation statements)

References 17 publications

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“…In existing literature, many researchers [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] have discussed different clustering techniques but still issues such as load balancing, ZH selection and reselection, and energy consumption exist. In addition, topology management is also very important to uniformly distribute the nodes in clusters/grids and make the network efficient [2,3].…”

Section: Related Workmentioning

confidence: 99%

Section: Variable Clusteringmentioning

confidence: 99%

“…A nonuniform deterministic node distribution is proposed by Chatterjee and Das [21] in which the number of nodes increases towards sink node. The problem of energy hole due to uniform clustering is addressed in [21]. Energy Aware Distributed Clustering (EADC) [29] is proposed for nonuniform distribution of nodes to balance load across the network.…”

Section: Variable Clusteringmentioning

confidence: 99%

“…Optimal range ratio (ORR) is required to split the zones, which is defined from 0.75 to 1.0 after extensive simulations. if Zone is Cand zone SC then (4) if (zone density SC > UB) then (5) Find the indices of nodes in SC (6) end if (7) = ⌈(SC/ )⌉ (8) = ((SC − 1) mod ) + 1 (9) if (ORR ≥ 0.75 and ≤ 1) then (10) Split horizontally (11) Go to End (12) end if (13) if (ORR ≥ 0.75 and ≤ 1) then (14) Split vertically (15) Go to End (16) end if (17) if (ORR ≥ 0.75 and ≤ 1) then (18) Split diagonally (45 ∘ ) (19) Go to End (20) end if (21) if (ORR ≥ 0.75 and ≤ 1) then (22) Split diagonally (135 ∘ ) (23)…”

Section: Splitting Of High Density Zone (Hdz)mentioning

confidence: 99%

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Grid-Based Hybrid Network Deployment Approach for Energy Efficient Wireless Sensor Networks

et al. 2016

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Wireless sensor networks (WSN) empower applications for critical decision-making through collaborative computing, communications, and distributed sensing. However, they face several challenges due to their peculiar use in a wide variety of applications. One of the inherent challenges with any battery operated sensor is the efficient consumption of energy and its effect on network lifetime. In this paper, we introduce a novel grid-based hybrid network deployment (GHND) framework which ensures energy efficiency and load balancing in wireless sensor networks. This research is particularly focused on the merge and split technique to achieve even distribution of sensor nodes across the grid. Low density neighboring zones are merged together whereas high density zones are strategically split to achieve optimum balance. Extensive simulations reveal that the proposed method outperforms state-of-the-art techniques in terms of load balancing, network lifetime, and total energy consumption.

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Section: Related Workmentioning

confidence: 99%

Section: Variable Clusteringmentioning

confidence: 99%

Section: Variable Clusteringmentioning

confidence: 99%

Section: Splitting Of High Density Zone (Hdz)mentioning

confidence: 99%

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Grid-Based Hybrid Network Deployment Approach for Energy Efficient Wireless Sensor Networks

et al. 2016

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“…The weaknesses of uniform clustering is pointed out in nonuniform deterministic node distribution (NUDND) [21], where it can lead towards energy hole in the network. A new model nonuniform deterministic node distribution is proposed, where node density increases towards sink node.…”

Section: (Vi) Unequal Clustering Size Model (Ucs)mentioning

confidence: 99%

Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

Jan

Farman

Javed

et al. 2017

Wireless Communications and Mobile Computing

125

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Wireless sensor networks (WSN) are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH) while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

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IoT Sensing Capabilities: Sensor Deployment and Node Discovery, Wearable Sensors, Wireless Body Area Network (WBAN), Data Acquisition

Poongodi

Rathee²,

Indrakumari

et al. 2019

Intelligent Systems Reference Library

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Coverage constrained non-uniform node deployment in wireless sensor networks for load balancing

Cited by 17 publications

References 17 publications

Grid-Based Hybrid Network Deployment Approach for Energy Efficient Wireless Sensor Networks

Grid-Based Hybrid Network Deployment Approach for Energy Efficient Wireless Sensor Networks

Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

IoT Sensing Capabilities: Sensor Deployment and Node Discovery, Wearable Sensors, Wireless Body Area Network (WBAN), Data Acquisition

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