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p-acohoneybeE: A Novel Load Balancer for Cloud Computing Using Mathematical Approach

Computers, Materials & Continua 2022年第10期73卷 1943-1959页

作者： Sunday Adeola Ajagbe Mayowa O.Oyediran Anand Nayyar Jinmisayo A.Awokola Jehad F.Al-Amri Computer Engineering Department Ladoke Akintola University of TechnologyLAUTECHOgbomosoNigeria Computer Science Department Ajayi Crowther UniversityOyoNigeria Graduate School Faculty of Information TechnologyDuy Tan UniversityDa NangVietnam Department of Computer Sciences Precious Cornerstone UniversityIbadanNigeria Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Cloud computing is a collection of disparate resources or services,a web of massive infrastructures,which is aimed at achieving maximum utilization with higher availability at a minimized *** of the most attractive applications for cloud computing is the concept of distributed information ***,privacy,energy saving,reliability and load balancing are the major challenges facing cloud computing and most information technology *** balancing is the process of redistributing workload among all nodes in a network;to improve resource utilization and job response time,while avoiding overloading some nodes when other nodes are underloaded or idle is a major ***,this research aims to design a novel load balancing systems in a cloud computing *** research is based on the modification of the existing approaches,namely;particle swarm optimization(pSO),honeybee,and ant colony optimization(ACO)with mathematical expression to form a novel approach called *** experiments were conducted on response time and *** results of the response time of honeybee,pSO,SASOS,round-robin,pSO-ACO,and p-acohoneybeE are:2791,2780,2784,2767,2727,and 2599(ms)*** outcome of throughput of honeybee,pSO,SASOS,round-robin,pSO-ACO,and p-acohoneybeE are:7451,7425,7398,7357,7387 and 7482(bps)*** is observed that p-acohoneybeE approach produces the lowest response time,high throughput and overall improved performance for the 10 *** research has helped in managing the imbalance drawback by maximizing throughput,and reducing response time with scalability and reliability.

关键词： ACO cloud computing load balancing swarm intelligence pSO p-acohoneybe honeybee swarm

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