Energy Efficient Clustering Algorithm Using RFD Based Multi-hop Communication in Wireless Sensor Networks

Guravaiah, Koppala; Velusamy, R. Leela

doi:10.1007/s11277-017-4012-y

Cited by 25 publications

(20 citation statements)

References 26 publications

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“…In addition to well-known academic NP-hard problems like the traveling salesman or Steiner tree problems [19,20], it has also been used in more specific industrial domains, like monitoring electrical power systems [21] or designing VLSI circuits [22,23]. In particular, due to its intrinsic absence of cycles, it has been used to design several routing protocols in computer networks (see, e.g., [24,25]), to test systems [26], or to improve robot navigation [27]. A survey describing the main application domains of RFD can be found in [28].…”

Section: Rfd: River Formation Dynamicsmentioning

confidence: 99%

Water‐Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP‐Hard Problems

Rubio

Rodrı́guez

2019

Complexity

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Many water-based optimization metaheuristics have been introduced during the last decade, both for combinatorial and for continuous optimization. Despite the strong similarities of these methods in terms of their underlying natural metaphors (most of them emulate, in some way or another, how drops collaboratively form paths down to the sea), in general the resulting algorithms are quite different in terms of their searching approach or their solution construction approach. For instance, each entity may represent a solution by itself or, alternatively, entities may construct solutions by modifying the landscape while moving. A researcher or practitioner could assume that the degree of similarity between two water-based metaheuristics heavily depends on the similarity of the natural water mechanics they emulate, but this is not the case. In order to bring some clarity to this mosaic of apparently related metaheuristics, in this paper we introduce them, explain their mechanics, and highlight their differences.

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Section: Rfd: River Formation Dynamicsmentioning

confidence: 99%

Water‐Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP‐Hard Problems

Rubio

Rodrı́guez

2019

Complexity

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“…It effect the aggregation and fusion of data to reduce the number of messages transmitted to the BS. There are a great number of studies about routing procedures in WSNs, and there are several ways to classify the algorithms of clustering: depending on whether the deployed nodes are homogeneous or heterogeneous, that intracluster communication is in one or k‐hop, according to the criteria for determining the CHs: a first possibility is that this decision stems from an elective process and another strategy is that it is the nature of the node which defines the CH. Several approaches exist to create clusters, namely, K‐Medoids and Fuzzy C‐Means .…”

Section: Related Workmentioning

confidence: 99%

Energy‐efficient routing protocol to improve energy consumption in wireless sensors networks

Elkamel

Cherif

2017

Int J Communication

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Summary The energy consumption is considered to be the major challenge in wireless sensor networks. In this paper, we shed light on a new approach to overcome the energy consumption problems. The objective of this work is to integrate an improved algorithm which is the K‐means to create a balanced energy on clusters and to use the Gaussian elimination algorithm during the election of cluster head that will guarantee the distribution of energy consumption. To address the problem of the optimal number of groups, we use Davies Bouldin index to increase the network lifetime. The simulation result shows that the proposed protocol extends the network lifetime compared to Leach, iMod‐Leach, leach‐C, and CELRP.

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“…a distinct capability function is additionally employed through enchanting maintenance of these entries that definitely occupy additional liveliness through substitute by way of transmit nodes trendy pack speedily. A tendency to perform in depth simulation on the planned ways and assess them with many concert metrics as well as network life-time [6], variety of energetic detector unit, liveliness maintenances, whole variety in subdivided information distribution [7] . Our main contributions will be elliptical as follows:  Liner programming and Non liner programming constructions for the direction-finding routing and cluster complications respectively.…”

Section: Introductionmentioning

confidence: 99%

A Particle Swarm Optimization Development for Routing and Cluster Formation in Wireless Sensor Networks

Manikandan,

Jeyakarthic*

2019

IJITEE

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An efficiency capable routing and cluster group are needed for improvement that are deliberate wide toward the extending the maximizing life of wireless detector networking. A new innovative research contributes the non-linear and linear Program design constructions of these problems tracked by anticipated algorithms for identical supported Heuristic Approaches of Particle Swarm Improvement Protocol (HAPSIP). The anticipated designs are tested widely and furthermore the outcomes are contrasted with the present designs with decide their prevalence as far as system life, vitality utilization, dead deduct indicator hubs and conveyance of all information particle to the base station. The testing platform compared and implemented in MATLAB

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Energy Efficient Clustering Algorithm Using RFD Based Multi-hop Communication in Wireless Sensor Networks

Cited by 25 publications

References 26 publications

Water‐Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP‐Hard Problems

Water‐Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP‐Hard Problems

Energy‐efficient routing protocol to improve energy consumption in wireless sensors networks

A Particle Swarm Optimization Development for Routing and Cluster Formation in Wireless Sensor Networks

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