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Modified Elite Chaotic Immune Clonal Selection Algorithm for sever resource allocation in cloud computing systems

机译:云计算系统中服务器资源分配的改进精英混沌免疫克隆选择算法

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Cloud computing is a promising technology to improve computational efficiency for both IT enterprise and individuals. Resource allocation in cloud computing is very challenging as both server computing power and network bandwidth are limited. The computational efficiency of cloud computing system can be significantly improved if the resources are allocated in a balanced fashion. However, resource allocation in cloud computing is a multi-constrained nonlinear optimization problem. The computational complexity for an exhaustive search over all combinations of resource allocations is too high for practical implementation. In this paper, we develop a Modified Elite Chaotic Immune Clonal Selection Algorithm to increase the overall efficiency of the system. An elite strategy and chaotic approaches are designed to improve population diversity and escape from local optima. Performance comparisons are made with simulated annealing algorithm (SA) and three other heuristic algorithms. Simulation results show that the Modified Elite Chaotic Immune Clonal Selection Algorithm solves the resource allocation problem with higher system resource efficiency than all other heuristic algorithms.
机译:云计算是一种有前途的技术,可以提高IT企业和个人的计算效率。由于服务器计算能力和网络带宽都受到限制,因此云计算中的资源分配非常具有挑战性。如果以平衡的方式分配资源,则可以显着提高云计算系统的计算效率。但是,云计算中的资源分配是一个多约束非线性优化问题。对于资源分配的所有组合进行穷举搜索的计算复杂度对于实际实现而言太高了。在本文中,我们开发了一种改进的精英混沌免疫克隆选择算法,以提高系统的整体效率。设计了一种精英策略和混乱的方法来改善人口多样性并摆脱局部最优状态。使用模拟退火算法(SA)和其他三种启发式算法进行性能比较。仿真结果表明,改进的精英混沌免疫克隆选择算法解决了资源分配问题,具有比其他所有启发式算法更高的系统资源效率。

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