An improved Hybrid Fuzzy-Ant Colony Algorithm Applied to Load Balancing in Cloud Computing Environment

被引：31

作者：

Ragmani, Awatif ^{[1
]}

Elomri, Amina ^{[1
]}

Abghour, Noreddine ^{[1
]}

Moussaid, Khalid ^{[1
]}

Rida, Mohammed ^{[1
]}

机构：

[1] Univ Hassan II Casablanca, Fac Sci AinChock, Casablanca 20100, Morocco

来源：

10TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT 2019) / THE 2ND INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40 2019) / AFFILIATED WORKSHOPS | 2019年 / 151卷

关键词：

Ant Colony Optimization; Fuzzy Logic; Cloud computing; Load Balancing; Taguchi; Response time;

D O I：

10.1016/j.procs.2019.04.070

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper outlines a novel hybrid algorithm based on the Fuzzy logic and ant colony optimization (ACO) concepts to improve the load balancing in the Cloud environment. Unfortunately, the large number of requests processed as well as the servers available at each instant t, make the conventional algorithms of load balancing ineffective. The proposed algorithm considers the load balancing and response time objectives in the Cloud. Moreover, the performance of the ACO algorithm is strongly correlated with the ACO parameters' values. The introduced approach (i) applies the Taguchi experimental design to identify the best value of ACO parameters (ii) and define a fuzzy module to evaluate the pheromone value in order to improve the calculation duration. The achieved simulations through CloudAnalyst platform demonstrate the effectiveness of the combined Fuzzy-ACO algorithm in comparison with other load balancing algorithms. (C) 2019 The Authors. Published by Elsevier B.V.

引用

页码：519 / 526

页数：8

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