A Survey of Adaptive Distributed Clustering Algorithms for Wireless Sensor Networks

Prabhu, S.R.Boselin; Sophia, S.

doi:10.5121/ijcses.2011.2412

Cited by 25 publications

(16 citation statements)

References 19 publications

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“…In this segment, literature survey of numerous posted disbursed clustering algorithms for WSNs is provided, based totally on some advantages like efficient usage of conversation bandwidth inside the clusters, heading off redundant message transfer between the sensor nodes, localizing energy efficient route setup in the clusters, reduction in energy consumption [3], and so forth.…”

Section: Distributed Clustering Algorithms For Wsnmentioning

confidence: 99%

Fuzzy C-Means Clustering for Enhancement of Energy in Wireless Sensor Network

Jain¹

2017

IJRASET

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Wireless Sensor Networks (WSNs) consists of a set of sensor nodes that are deployed in a field and interconnected with a wireless communication network. Each of these scattered sensor nodes have the talents to collect information, fuse that data and path the data again to the sink/base station. To collect data, each of these sensor nodes makes decision based on its observation of a part of the environment and on partial a-priori information. In existing work, they used fuzzy logic technique for the cluster head selection to increase lifetime of wireless sensor network. But they used fuzzy based technique like distance of base station and residual energy for selection of cluster head and sometimes one or more cluster heads are formed in the grid. This increase the energy consumption of nodes as nodes has to send data from multiple cluster heads. In proposed work, we used fuzzy-c means for the formation of clusters. Initially deployed the cluster head in the centre of every cluster in every grid and then we select another cluster head on the basis of residual energy and distance with base station. This improves the network lifetime and improvement in the energy consumption of each node to communicate efficiently. We used MATLAB for the simulation to show that our proposed work is much better than the existing techniques. Keywords: Wireless Sensor Network, Clustering, Fuzzy logic, Membership function. I. INTRODUCTION Wireless Network is a type of Computer Network that provides communication between a numbers of nodes without having aPhysical Connectivity between these nodes. No nodes are connected through a Physical Medium to communicate with each other. Rather they use wireless mediums such as air / atmosphere to transmit the data from one node to another. Commonly used wireless transmission mediums encompass Microwave Communication, Radio Wave Communication, Satellite Communication, and many others. WSN is a sub magnificence of Wireless Networks which have the same working principle but are slightly clever or better compared to the conventional Wireless Networks. A Wireless Sensor Network includes spatially disbursed sensors referred to as Sensor Nodes that senses and monitors the environmental situations at the side of communicating with the other nodes or sharing the data between a numbers of nodes. Wireless Sensor Networks (WSNs) consists of a set of sensor nodes that are deployed in a field and interconnected with a wireless communication network. Each of those scattered sensor nodes have the capabilities to acquire statistics, fuse that data and course the data back to the sink/base station. To collect data, each of these sensor nodes makes decision based on its observation of a part of the environment and on partial a-priori information. As large amount of sensors are deployed in harsher environment, it is vital that the distributed computation need to be robust and fault-tolerant. The identification of event in a wireless sensor network should be done as fast as possible, thus the computations ar...

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Section: Distributed Clustering Algorithms For Wsnmentioning

confidence: 99%

Fuzzy C-Means Clustering for Enhancement of Energy in Wireless Sensor Network

Jain¹

2017

IJRASET

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“…There are several ways to classify the clustering algorithms like centralized, distributed and hybrid routing algorithm [6]. In centralized clustering approach centralized architecture is used and there is fixed CH.…”

Section: Classification Of Clustering Schemementioning

confidence: 99%

“…R. Prabhu et al [6] Authors presented some frequently used distributed clustering algorithm and shows the difference among them based on some metrics such as cluster count, stability, cluster head mobility, cluster-head role, clustering objective, cluster-head selection, merits and limitations.…”

Section: Related Workmentioning

confidence: 99%

A Comparative Study of Existing Cluster-Based Routing Protocols in Wireless Sensor Networks

Mishra¹,

Sharma²

2016

IJFGCN

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“…The observed parameters include efficient utilization of communication bandwidth within the clusters, avoiding redundant message transfer between the nodes, localizing energy efficient route setup within the clusters, reduction in energy consumption, etc. [1], [2] made an analysis that reliable routing of packets from nodes to its base station is the most important task for the networks. Routing in wireless networks is bit more complex than other wired networks.…”

Section: Related Workmentioning

confidence: 99%

“…Clustering produces initial categories in which values of a data set are further classified during the classification process. Previous works [1,2] have tried to develop intelligent receivers that are capable of identifying the incoming modulation scheme and reconfigure themselves accordingly. However, these architectures support only a very limited number of constellations, thus limiting both generality and performance [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Improved QoS by Clustering Identically Modulated WSN Nodes using Reprogrammable High Speed Architecture

Selvan¹,

Ravi²,

Jabeen³

2013

IJCA

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A technique for grouping different modulation schemes in a nodal management network (by clustering identically modulated nodes) is presented in this paper. The modulation tracking scheme localizes a specific node (allocated with a unique, but dynamically varying modulation scheme). The clustering mechanism to group the identical nodes exists intrinsically. The proposed modulation identification scheme and clustering mechanism are implemented using high speed architectures and the performance of the proposed approach is validated for multiple modulation scenarios.

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A Survey of Adaptive Distributed Clustering Algorithms for Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSNs)

Cited by 25 publications

References 19 publications

Fuzzy C-Means Clustering for Enhancement of Energy in Wireless Sensor Network

Fuzzy C-Means Clustering for Enhancement of Energy in Wireless Sensor Network

A Comparative Study of Existing Cluster-Based Routing Protocols in Wireless Sensor Networks

Improved QoS by Clustering Identically Modulated WSN Nodes using Reprogrammable High Speed Architecture

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