An Optimal Load Balancing Framework for Fog-Assisted Smart Grid Applications

Title

An Optimal Load Balancing Framework for Fog-Assisted Smart Grid Applications

Creator

Sharma V.; Tripathy S.S.; Bebortta S.; Iwendi C.; Osamor J.

Description

The growth of the Internet of Things (IoT) causes a significant amount of data to come in from physical devices and sensors, which adds to the latency and processing delays in smart grid applications. The pay-per-model method of transmitting gathered data that cloud computing offers improves scalability and functionality for end devices, which increases smart grid efficiency. Milliseconds matter in the crucial realms of load balancing, resource usage, and distribution systems, where any latency or jitter is unacceptable. By strategically positioning processing, networking, storage, and communication capabilities at the network edge, fog computing, an outgrowth of cloud technology, successfully addresses current issues in service groups. This paper introduces a unique hybrid framework on a highly virtualized platform and proposes three potential load balancing algorithms: throttled, Round Robin, and a novel Equilibrium Optimizer with Simulated Annealing (EO-SA). The article provides a comprehensive investigation on several load balancing techniques for obtaining optimized services in a smart grid environment thereby focusing on better utilization of network resources and reduction of costs. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Source

Lecture Notes in Networks and Systems, Vol-1043 LNNS, pp. 589-601.

Date

2024-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Cloud computing; Fog computing; Load balancing; Optimization; Performance evaluation; Smart grid

Coverage

Sharma V., Computer Science Department, Christ University, Delhi NCR Campus, India; Tripathy S.S., School of Computer Engineering, KIIT Deemed to Be University, Bhubaneswar, 751024, India; Bebortta S., Department of Computer Science, Ravenshaw University, Cuttack, 753003, India; Iwendi C., School of Creative Technologies, University of Bolton, Bolton, United Kingdom; Osamor J., University of Westminster, London, United Kingdom

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981974227-1

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-97-4228-8_38

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