基于蜂群算法的多维QoS云计算任务调度

针对云计算环境下用户日益多样化的QoS需求和高效的资源调度要求,提出了基于改进蜂群算法的多维QoS云计算任务调度算法,其中包括构建任务模型、云资源模型和用户QoS模型。为了获得高效的调度,引入蜂群算法。针对该算法在后期收敛速度变慢且易陷入局部最优的问题,引入收益比、跟随比概念及当前个体最优值及随机向量,避免"早熟"现象的出现。通过实验仿真,将该算法HEFT与和ABC算法进行比较,实验表明,该算法能获得较高的调度效率和用户满意度。

Multi dimensional QoS cloud task scheduling based on colony algorithm

In order to meet the users’ Quality of Service(QoS) requirements and the efficient resource scheduling requirements in cloud environment, we propose a multi dimensional QoS cloud task scheduling algorithm based on the artificial bee colony algorithm, which includes building a task model, a cloud resource model and a QoS model. In order to achieve efficient scheduling, we introduce an artificial bee colony algorithm. Because of its defects such as slow convergence and easy to fall into local optimization at the later stage, we introduce the profitability ratio, following ratio, current personal best value and random vectors to avoid the premature phenomenon. We compare this algorithm with the heterogeneous earliest finish time(HEFT ) algorithm and the artificial bee colony(ABC) algorithm through simulation, and experimental results show that the proposed algorithm can achieve higher operation efficiency and user satisfaction.