A GA based approach for task scheduling in multi-cloud environment

2015/11/27 by Tripti Tanaya Tejaswi, Tejaswi, Tripti Tanaya, Md Azharuddin +3
Computer Science · #Cloud Computing and Resource Management #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #IoT and Edge/Fog Computing #Parallel #and Cluster Computing (cs.DC)

paper · pdf · doi:10.48550/arxiv.1511.08707

openalex publication_date 2015/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In multi-cloud environment, task scheduling has attracted a lot of attention due to NP-Complete nature of the problem. Moreover, it is very challenging due to heterogeneity of the cloud resources with varying capacities and functionalities. Therefore, minimizing the makespan for task scheduling is a challenging issue. In this paper, we propose a genetic algorithm (GA) based approach for solving task scheduling problem. The algorithm is described with innovative idea of fitness function derivation and mutation. The proposed algorithm is exposed to rigorous testing using various benchmark datasets and its performance is evaluated in terms of total makespan.

Citations

• NP-complete scheduling problems

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