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A Combinatorial Optimization Algorithm for Load Balancing in Cloud Infrastructure

机译:云基础架构负载均衡的组合优化算法

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Cloud Technology is considered as the next generation of Business Process Outsourcing (BPO). It is a fast-evolving service oriented business which is based on Pay-As-You-Go model. Business analysts say that it is a double-edged sword service trade between cloud users and cloud providers. While cloud users are demanding to minimize turnaround time (response time), cloud providers bargain to maximize the profit by optimizing the utility rate of cloud resources. It ends up in a cost-benefit trade-off between the cloud providers and cloud users. In this paper, we propose a Load Balancing (LB) model that optimizes the cost-benefit trade-off between the cloud providers and cloud users. We first formulated the load balancing problem in Cloud as a combinatorial optimization problem. Subsequently, we designed a Modified Branch and Bound-Based Knapsack (MB3K) algorithm to solve the combinatorial optimization load balancing problem. The proposed model eases the cost-benefit trade-off significantly between the cloud users and providers. It is also empirically illustrated that the proposed algorithm performs better than the branch and bound knapsack algorithm and round robin scheduling algorithm.
机译:云技术被认为是下一代业务流程外包(BPO)。它是一种快速发展的,以服务为导向的业务,它基于现收现付模型。业务分析师表示,这是云用户与云提供商之间的双刃剑服务交易。尽管云用户要求最小化周转时间(响应时间),但云提供商通过讨价还价来通过优化云资源的利用率来最大化利润。最终导致云提供商与云用户之间在成本效益方面进行权衡。在本文中,我们提出了一种负载平衡(LB)模型,该模型优化了云提供商与云用户之间的成本效益权衡。我们首先将Cloud中的负载平衡问题表述为组合优化问题。随后,我们设计了一种改进的基于分支和边界的背包(MB3K)算法,以解决组合优化负载均衡问题。所提出的模型极大地减轻了云用户与提供商之间的成本-收益权衡。实验证明,该算法的性能优于分支定界背包算法和循环调度算法。

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