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Nature-inspired optimization algorithms for different computing systems: novel perspective and systematic review

期刊

MULTIMEDIA TOOLS AND APPLICATIONS
卷 81, 期 19, 页码 26779-26801

出版社

SPRINGER
DOI: 10.1007/s11042-021-11011-x

关键词

Sustainability; Energy efficiency; Load balancing; Scheduling; Grid computing; Cloud computing; Distributed computing; Fog computing; Edge computing

资金

  1. King Saud University, Riyadh, Saudi Arabia [RSP-2020/250]

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Nature inspired algorithms play a vital role in solving diverse optimization problems by improving task efficiency and reducing energy consumption and costs. Various computing techniques benefit from these algorithms and have seen significant improvements in results.
Nature inspired algorithm plays a very vibrant role in solving the different optimization problems these days. The fundamental attitude of naturalistic approaches is to boost the competence, improvement, proficiency, success in the task except from it to help in underrating the energy use, cost, size. Several computing techniques are taking the benefits from nature inspired algorithms for solving their problems related to load balancing, scheduling and many others. These algorithms have come up with lots of improvements in the results. The aim of this analysis is to make efforts in the betterment in different areas of computing and help in solving various problems related to load balancing, scheduling and energy efficiency. The structure of the paper includes an introduction, contribution to the work, background study, which includes the role of nature inspired techniques in a different computing environment, research challenges and its applications. The sustainable goal and objective of the article is to perform the energy efficiency, load balancing and scheduling on different computing systems which include grid, cloud, distributed, fog and edge computing by using various nature inspired algorithms. This comprehensive study gives the awareness and valuable provision for the researchers in this area by providing a thorough study of different computing techniques in different research fields.

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