Determination method of optimal number of clusters for clustered wireless sensor networks

Li, Wenfeng; Martins, Philippe; Shen, Lianfeng

doi:10.1002/wcm.949

Cited by 7 publications

(7 citation statements)

References 22 publications

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“…For large networks, cluster optimization is still important, even if free space fading energy is low. Li et al [58] presented an analytical model for finding the optimal number of clusters, for minimizing the communication costs in a clustered sensor network. In this, sensor nodes are placed in the sensing field in a random and distributed manner according to a homogeneous poisson point process.…”

Section: Homogeneous Sensor Networkmentioning

confidence: 99%

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A Review Study on Analytical Estimation of Optimal Number of Clusters in Wireless Sensor Networks

Kumar

Dhok

Tripathi

et al. 2014

TNC

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To improve energy efficiency, total network scalability and data aggregation in Wireless Sensor Networks (WSNs), sensor nodes are often grouped into disjoint and mostly non-overlapping subsets called clusters. To provide an energy-efficient system by clustering, there are three main challenges. First is to find the optimum number of nodes in a specific cluster, second is to find the optimum number of clusters in the network and the third is to find the optimum position of Cluster Head (CH) in a specific cluster. Selecting an optimum number of clusters in WSNs provide greater improvement in terms of system scalability, energy efficiency, collision reduction, network lifetime, latency, and efficient routing backbone in the network. Selection of optimal number of clusters in WSNs is affected by level at which WSNs is modeled viz. Radio Energy Model Level, Network Model Level and Clustering Level. The objective of this paper is to present a state-of-the-art survey of distinct analytical methods used to calculate the optimum number of clusters, and its time-line comparative analysis based on network type, mathematical formula for an optimal number of clusters, base station positioning, energy model, strengths, weaknesses and applications of WSNs. We have also discussed the impact of different parameters on selecting the optimal number of clusters in WSNs.

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Section: Homogeneous Sensor Networkmentioning

confidence: 99%

“…It can be used for real transmission [58] Les overhead Algorithms only considered error free communication and do not account for the channel contention…”

Section: It Is Not Applicable For Asymmetrical Channelmentioning

confidence: 99%

A Review Study on Analytical Estimation of Optimal Number of Clusters in Wireless Sensor Networks

Kumar

Dhok

Tripathi

et al. 2014

TNC

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“…Wireless sensor networks are composed of many wireless sensors deployed in a wide range of areas, where each sensor is able to communicate with others through intersensor wireless communication [1][2][3][4][5]. The wireless sensor networks are able to collect, process, and store environmental information [6][7][8]. In wireless sensor networks, the batteries are the main energy sources of sensors, while the sensor nodes are expected to work in batteries for a long time without charging their batteries.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Algorithm of Constructing Virtual Backbone Scheduling for Maximizing the Lifetime of Dual-Radio Wireless Sensor Networks

Liu

Pham

Nguyen

2015

International Journal of Distributed Sensor Networks

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Wireless sensor networks have often been used to monitor environmental conditions, such as temperature, sound, and pressure. Because the sensors are expected to work on batteries for a long time without charging their batteries, the major challenge in the design of wireless sensor networks is to enhance the network lifetime. Recently, many researchers have studied the problem of constructing virtual backbones, which are backbones used for different time periods, to prolong the network lifetime. In this paper, we study the problem of constructing virtual backbones in dual-radio wireless sensor networks to maximize the network lifetime, called the Maximum Lifetime Backbone Scheduling for Dual-Radio Wireless Sensor Network problem, where each sensor is equipped with two radio interfaces. The problem is shown to be NP-complete here. In addition, rather than proposing a centralized algorithm, a distributed algorithm, called a Dominating-Set-Based Algorithm (DSBA), is proposed for a wide range of wireless sensor networks to find a backbone when a new one is required. Simulation results show that the proposed algorithm outperforms some existing algorithms.

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“…A wireless sensor network consists of multiple sensors each able to collect, process, and store environmental information as well as communicate with others via inter‐sensor wireless communication. These characters have facilitated the use of wireless sensor networks in a wide range of applications , including health care; environmental monitoring; battlefield surveillance; nuclear, biological, and chemical attack detection; and intruder detection. In many applications, sensor nodes are deployed in a 3D environment with obstacles, such as buildings and lakes, in which a great deal of holes exist in the 3D wireless sensor networks constructed.…”

Section: Introductionmentioning

confidence: 99%

Efficient delivery‐guaranteed geographic routing in 3D wireless sensor networks with holes

Liu

Cheng

Wen

2014

Wireless Communications

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In many applications, sensor nodes are deployed in a 3D environment with obstacles, in which case a great deal of holes exist in 3D wireless sensor networks constructed. Recently, several geographic routing protocols are proposed for 3D wireless sensor networks. Each of them, however, cannot guarantee packet delivery or demands a long routing path to turn around a hole. In this paper, we first introduce a method of constructing a guide to the navigation on the surface of a hole. Subsequently, a geographic routing protocol termed the Greedy‐Guide_Navigation‐Greedy protocol (GGNG) that can always route a packet to turn around a hole with the help of the guide is proposed. GGNG guarantees packet delivery and can be extended toward a mobile sensor network in a limited 3D space. Simulations show that the path stretch of each routing protocol to GGNG in approximately 90 % of the cases is between 1.02 and 189.24. In addition, the number of messages transmitted by a node surrounding a hole in the guide construction is approximately three. Copyright © 2014 John Wiley & Sons, Ltd.

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Determination method of optimal number of clusters for clustered wireless sensor networks

Cited by 7 publications

References 22 publications

A Review Study on Analytical Estimation of Optimal Number of Clusters in Wireless Sensor Networks

A Review Study on Analytical Estimation of Optimal Number of Clusters in Wireless Sensor Networks

An Efficient Algorithm of Constructing Virtual Backbone Scheduling for Maximizing the Lifetime of Dual-Radio Wireless Sensor Networks

Efficient delivery‐guaranteed geographic routing in 3D wireless sensor networks with holes

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