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A New Hybrid Multi-objective Optimization Algorithm for Task Scheduling in Cloud Systems by Arslan Nedhir Malti; Mourad Hakem; Badr Benmammar is a Computer Science article available to read on EtoBox.

What is A New Hybrid Multi-objective Optimization Algorithm for Task Scheduling in Cloud Systems about?

Nowadays, cloud computing is widely used in various fields and is booming day by day with different services offered to users according to their needs and contracts. However, this has brought many challenges and constraints that organizations must to be aware of and address to fully harness its power. In practice, the most important issue that has gained significant influence in improving system performances is task scheduling. Unfortunately, it is commonly known that this problem is NP-hard and the use of both heuristics and metaheuristics is required to obtain near optimal solutions but in a reasonable amount of computation time. Despite the fact that several studies have been published in the literature, there are still interesting and relevant questions to be addressed. For instance, when it comes to the stagnation phenomenon of local solutions and the premature convergence of the search process, it is crucial to execute the exploration and exploitation stages carefully as improperly performed stages may result in inefficient task mapping solutions. Consequently, to overcome the limitations of existing techniques in terms of local optimality trap and immature convergence, a nov

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Author

Arslan Nedhir Malti; Mourad Hakem; Badr Benmammar

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)