Hybrid PSO-MOBA for Profit Maximization in Cloud Computing

被引:0
作者
George, Salu [1 ]
机构
[1] Al Dar Univ Coll, Sch Informat Technol, Dubai, U Arab Emirates
关键词
Cloud Computing; Profit Maximization; Admission Control; SLA; Optimization; Hybrid Particle Swam Optimization - Multi Objective Bat Algorithm;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Cloud service provider, infrastructure vendor and clients/Cloud user's are main actors in any cloud enterprise like Amazon web service's cloud or Google's cloud. Now these enterprises take care in infrastructure deployment and cloud services management (IaaS/PaaS/SaaS). Cloud user 's need to provide correct amount of services needed and characteristic of workload in order to avoid over - provisioning of resources and it's the important pricing factor. Cloud service provider need to manage the resources and as well as optimize the resources to maximize the profit. To manage the profit we consider the M/M/m queuing model which manages the queue of job and provide average execution time. Resource Scheduling is one of the main concerns in profit maximization for which we take HYBRID PSO-MOBA as it resolves the global convergence problem, faster convergence, less parameter to tune, easier searching in very large problem spaces and locating the right resource. In HYBRID PSO-MOBA we are combining the features of PSO and MOBA to achieve the benefits of both PSO and MOBA and have greater compatibility.
引用
收藏
页码:159 / 163
页数:5
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