CAJ | 학술논문

针对云计算中多任务调度和资源分配问题，提出一种融合田口方法和差分进化算法（DEA）的改进差分进化算法（IDEA），优化云计算中多任务调度和资源分配。利用田口方法的一个正交表（OA）作为掩膜变异算子对任务进行编码，通过变异、交叉过程产生更好的后代。建立成本和时间模型，以此寻找调度方案的帕累托最优解。仿真具有5个任务和5个资源的云平台环境，以平均交叉率、分布距离、最大宽度和高维空间比率作为性能指标，将IDEA算法与DEA、NSGA-II等现有算法进行比较。实验结果表明，IDEA算法在寻找任务调度和资源分配的帕累托最优解上优于NSGA-II和DEA等算法。此外，对于不同的完工时间和任务调度成本的目标，分别列出了提出算法所寻找到的最优调度方案，能够为决策者提供很大帮助。
침대운계산중다임무조도화자원분배문제，제출일충융합전구방법화차분진화산법（DEA）적개진차분진화산법（IDEA），우화운계산중다임무조도화자원분배。이용전구방법적일개정교표（OA）작위엄막변이산자대임무진행편마，통과변이、교차과정산생경호적후대。건립성본화시간모형，이차심조조도방안적파루탁최우해。방진구유5개임무화5개자원적운평태배경，이평균교차솔、분포거리、최대관도화고유공간비솔작위성능지표，장IDEA산법여DEA、NSGA-II등현유산법진행비교。실험결과표명，IDEA산법재심조임무조도화자원분배적파루탁최우해상우우NSGA-II화DEA등산법。차외，대우불동적완공시간화임무조도성본적목표，분별렬출료제출산법소심조도적최우조도방안，능구위결책자제공흔대방조。
For the issue that multi-task scheduling and resource allocation problems in cloud computing, an Improved Dif-ferential Evolution Algorithm(IDEA)fusing Taguchi method and Differential Evolution Algorithm(DEA)is proposed. The algorithm encodes the tasks by using an Orthogonal(OA)of Taguchi method as a mask mutation operator, produces better offspring by the mutation and crossover process, and establishes a cost and time model in order to find out the Pareto optimal scheduling scheme. A cloud platform environment containing five tasks and five resource is simulated to compare IDEA algorithm with DEA, NSGA-II and other existing algorithms by using average cross rate, distribution distance, max-imum width and high-dimensional space ratio as the performance index. Experimental results show that, IDEA algorithm outperforms NSGA-II, DEA and other algorithms in finding Pareto optimal solution for task scheduling and resource alloca-tion. In addition, the optimal scheduling schemes finding out by this algorithm are listed for the targets with different completion time and task scheduling cost separately which may provide great help to decision-makers.