CAJ | 학술논문

针对在云环境中，服务资源在各用户间难以实现最优动态分配的问题，利用帕累托最优理论与粒子群优化算法相互结合应用于云计算模型中，对各种服务资源的效用进行最优化配置，最终使资源利用率达到一个最优的状态。通过CloudSim对云服务资源调度进行仿真实验，结果表明，采用帕累托最优算法优化后的云计算模型具有更好的系统性能，使得资源的调度和配置达到最优。
침대재운배경중，복무자원재각용호간난이실현최우동태분배적문제，이용파루탁최우이론여입자군우화산법상호결합응용우운계산모형중，대각충복무자원적효용진행최우화배치，최종사자원이용솔체도일개최우적상태。통과CloudSim대운복무자원조도진행방진실험，결과표명，채용파루탁최우산법우화후적운계산모형구유경호적계통성능，사득자원적조도화배치체도최우。
In the cloud environment, service resources are hard to realize the optimal dynamic allocation in each user. The paper combines Pareto optimality theory and particle swarm optimization algorithm with each other which have applied in the cloud computing model about the above problem, to optimization configuration for the utility of various service resources, and finally make the utilization rate of resources achieve an optimal state, and make a simulation experiment of cloud service resources scheduling through CloudSim. The results show that the cloud computing model adopted Pareto optimality algo-rithm has better performance than before, and the configuration of resources has been achieved the optimal.