research-article

An Edge Server Placement Algorithm based on Genetic Algorithm

Authors:

Zhexuan Hu,

Xiaolong Xu,

Jinhui ChenAuthors Info & Claims

ACM TURC '21: Proceedings of the ACM Turing Award Celebration Conference - China

Pages 92 - 97

https://doi.org/10.1145/3472634.3472658

Published: 02 October 2021 Publication History

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Abstract

With the development of the Internet of Things (IOT) and 5th Generation Mobile Networks (5G), the data traffic generated by edge terminal devices has exploded. Traditional Cloud Computing (CC) technology cannot meet the business requirements of low latency, high efficiency, and high security. Mobile Edge Computing (MEC) has emerged as the times require. The placement of Edge Servers (ES) is a combinatorial optimization problem, and the problem is NP-hard. Faced with the two objectives of delay and efficiency, an ES placement algorithm based on Genetic Algorithm (GA) called EPG is proposed. In order not to increase the dimension of the solution space, the Base Station Request Search Algorithm (BSRSA) is designed to make the GA perform better. In order to avoid the impact of malignant evolution, the traditional GA is optimized, the optimal gene of each iteration is recorded, and the optimal gene in the record is taken as the final Pareto optimal solution. Finally, the EPG was evaluated with the real Shanghai Telecom base station data set.

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Cited By

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Vali AAzizi SShojafar M(2024)RESP: A Recursive Clustering Approach for Edge Server Placement in Mobile Edge ComputingACM Transactions on Internet Technology10.1145/366609124:3(1-25)Online publication date: 15-Jul-2024
https://dl.acm.org/doi/10.1145/3666091
Ghasemzadeh AAghdasi HSaeedvand S(2024)Edge server placement and allocation optimization: a tradeoff for enhanced performanceCluster Computing10.1007/s10586-024-04277-x27:5(5783-5797)Online publication date: 12-Feb-2024
https://doi.org/10.1007/s10586-024-04277-x
Bahrami BKhayyambashi MMirjalili S(2023)Edge server placement problem in multi-access edge computing environment: models, techniques, and applicationsCluster Computing10.1007/s10586-023-04025-726:5(3237-3262)Online publication date: 22-May-2023
https://dl.acm.org/doi/10.1007/s10586-023-04025-7
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An Edge Server Placement Algorithm based on Genetic Algorithm
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ACM TURC '21: Proceedings of the ACM Turing Award Celebration Conference - China

July 2021

284 pages

ISBN:9781450385671

DOI:10.1145/3472634

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 02 October 2021

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ACM TURC 2021: ACM Turing Award Celebration Conference - China ( ACM TURC 2021)

July 30 - August 1, 2021

Hefei, China

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Vali AAzizi SShojafar M(2024)RESP: A Recursive Clustering Approach for Edge Server Placement in Mobile Edge ComputingACM Transactions on Internet Technology10.1145/366609124:3(1-25)Online publication date: 15-Jul-2024
https://dl.acm.org/doi/10.1145/3666091
Ghasemzadeh AAghdasi HSaeedvand S(2024)Edge server placement and allocation optimization: a tradeoff for enhanced performanceCluster Computing10.1007/s10586-024-04277-x27:5(5783-5797)Online publication date: 12-Feb-2024
https://doi.org/10.1007/s10586-024-04277-x
Bahrami BKhayyambashi MMirjalili S(2023)Edge server placement problem in multi-access edge computing environment: models, techniques, and applicationsCluster Computing10.1007/s10586-023-04025-726:5(3237-3262)Online publication date: 22-May-2023
https://dl.acm.org/doi/10.1007/s10586-023-04025-7
Moorthy RArikumar KPrathiba B(2023)An Improved Whale Optimization Algorithm for Optimal Placement of Edge ServerAdvances in Distributed Computing and Machine Learning10.1007/978-981-99-1203-2_8(89-100)Online publication date: 28-Jun-2023
https://doi.org/10.1007/978-981-99-1203-2_8

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Cost-Effective Edge Server Placement in Edge Computing

Edge server placement problem in multi-access edge computing environment: models, techniques, and applications

An improved genetic algorithm with conditional genetic operators and its application to set-covering problem

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