Genetic Centralized Dynamic Clustering in Wireless Sensor Networks

Kheireddine, Mekkaoui; Rahmoun, Abdellatif; Ferrari, Gianluigi

doi:10.5815/ijcnis.2015.08.01

Cited by 5 publications

(3 citation statements)

References 7 publications

(10 reference statements)

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“…Insometheoreticalmodelsofwirelesstransmissions,whenacommunicationisassuredbetweentwo nodes,theauthorsassumedthatallenergyisconsumedonlybythetransmitter,andthereceiverdoesn't spendanyenergyduringareception (Pešovićetal.,2010;Kheireddine&Abdellatif,2013;Cook, Meier,Sieber,Secall,&Widmer,2017).Accordingtothem,ifthisschemeistakeninconsideration, thentheshort-hopsstrategywouldbethemostenergyefficient,butsincethereceptioncostshouldn't Inotherworks,theauthorsshowedthedisadvantagesofusinglong-hopsintermsofenergy (Kheireddine, Abdellatif, & Ferrari, 2015, Jain, Saini, & Bhooshan, 2015Chung, Kim, & Han, 2012;Razaque&Elleithy,2013;Zhang,Long,Vasilakos,&Hanzo,2016).Indeed,theuseofa bigtransmissionrangebyanodehelpstotheearlydissipationofitsbattery,sincetheenergyfor transmissionisstronglylinkedtothetransmissiondistance;hencethenecessityoffindingthehops lengthsthatensuresminimalenergyconsumption.…”

Section: Problem Presentationmentioning

confidence: 99%

Optimal Hop Lengths to Ensure Minimum Energy Consumption in Wireless Sensor Networks

Kheireddine

Abdellatif²

2018

International Journal of Technology Diffusion

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In wireless sensor networks, nodes have a low computing capacity, a small antenna and a very limited energy source; thereby batteries are considered as a critical resource and should be used efficiently. On the other hand, the antennas are the biggest consumers of energy, therefore, and their use must be very efficient to minimize energy consumption. In a dense WSN, each node may route messages to destination nodes either through short-hops or long-hops, by using a short or a long radio range. Thus, the hop length optimization can save energy. In this article, the authors propose a theorem to optimize the hop lengths and a routing algorithm to improve the WSN power consumption. The theorem establishes a simple condition to ensure the optimal hop lengths which guarantees the minimum energy consumption. And the proposed algorithm based on that condition is used to find the optimal routing path. The simulation results are obtained by applying the condition and the algorithm on WSNs and reveals a high performance regarding WSNs energy consumption and network lifetime.

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Section: Problem Presentationmentioning

confidence: 99%

Optimal Hop Lengths to Ensure Minimum Energy Consumption in Wireless Sensor Networks

Kheireddine

Abdellatif²

2018

International Journal of Technology Diffusion

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“…However, this is heavily challenging task as a selection of robust cluster head is a big decision to make from network lifetime viewpoint. At present, there are already archives of approaches towards solving clustering problem, [12][13][14][15][16] but there is less evidence of any standard, benchmarked, or robust clustering scheme in WSN that is claimed to offer better communication performance. The existing clustering scheme could not still balance the trade-off between computation and communication problem, and hence, it is yet an open-end problem.…”

Section: Introductionmentioning

confidence: 99%

Interstellar‐based topology control scheme for optimal clustering performance in WSN

Jyothi

Usha

2020

Int J Communication

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Summary Clustering is one of the essential operations in wireless sensor network (WSN) to ensure organized data aggregation followed by energy efficiency. However, obtaining optimal clustering performance is yet an unsolved problem in WSN. Review of existing approaches towards cluster optimization shows that effective balance between energy efficiency and topology control is still missing. Therefore, the proposed system presents a unique topology control mechanism using a novel concept of interstellar orientation toward optimizing the clustering performance in WSN. Adopting an analytical research methodology, the proposed system introduces two interstellar‐based topology control system, which targets the maximum saving of resource consumption of the cluster head. The simulated outcome of the study shows that the proposed topology control system offers significant energy conservation performance in comparison to the existing hierarchical clustering scheme in WSN.

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“…Khanna, R. [15] Genetic Algorithm reduced complexity for optimization of multi-hop sensor networks. Yogeswari et al [16] DCs has most important applications in sensor data collection as it collects the environment data from all sensor nodes periodically.…”

Section: Fig1 Block Diagram Of Data Management Techniques In Wsnmentioning

confidence: 99%

A Review on Wireless Data Center Management

Kumari¹,

Agarwal²

2016

IJCA

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Data Center Management is an important challenge in the fast era to fulfill ever-evolving computational demand around cloud computing, big data and infrastructure. DC (Data Center) are used to resolve the issues related to overutilization of resource, application failures, data security, power usage effectiveness and infrastructure costs which requires proactive solutions that are business intelligent and built over a network of sense-points with the help of sensor networks that are suitable to deliver reliable trends. Sensor networks with telemetry and control functions is used for collection & delivering of the data by improved server rack utilization, improved DC cooling and load balancing with dynamic capping is used. SCADA system is used with sense-point data to process the information wireless sensor networks in DCs comprises sensor nodes, gateways, routers, server platforms and software application for the overall management of various application.

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Genetic Centralized Dynamic Clustering in Wireless Sensor Networks

Cited by 5 publications

References 7 publications

Optimal Hop Lengths to Ensure Minimum Energy Consumption in Wireless Sensor Networks

Optimal Hop Lengths to Ensure Minimum Energy Consumption in Wireless Sensor Networks

Interstellar‐based topology control scheme for optimal clustering performance in WSN

A Review on Wireless Data Center Management

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