CAJ | 학술논문

针对云计算的MapReduce编程框架，提出一种融合蚁群算法和模拟退火算法的混合调度算法（ACOSA）。该算法以最小化调度时间为目标，引入了任务与资源的匹配因子和负载均衡度，先利用蚁群算法得到一组任务到资源的优化解，然后通过模拟退火算法对解进行路径的优化和信息素的更新。通过扩展Cloudsim云计算仿真平台，对其进行重新编译，实现了所提出的算法，实验结果表明该算法在调度时间、负载均衡等方面表现良好。
침대운계산적MapReduce편정광가，제출일충융합의군산법화모의퇴화산법적혼합조도산법（ACOSA）。해산법이최소화조도시간위목표，인입료임무여자원적필배인자화부재균형도，선이용의군산법득도일조임무도자원적우화해，연후통과모의퇴화산법대해진행로경적우화화신식소적경신。통과확전Cloudsim운계산방진평태，대기진행중신편역，실현료소제출적산법，실험결과표명해산법재조도시간、부재균형등방면표현량호。
It studies the task scheduling in cloud computing , and proposes a hybrid scheduling algorithm ( ACOSA) combined with ant colony algorithm and simulated annealing algorithm for the MapReduce pro-gramming framework of cloud computing .This algorithm aims at minimizing the scheduling time and in-troduces the task and resource matching factors and load balance .Firstly, the ant colony algorithm was used to get the optimal solution to a set of tasks and resources .Then, the path was optimized , and the pheromone of solution was updated by the simulated annealing algorithm .Lastly, they were recompiled by extending Cloudsim cloud computing simulation platform , and the ACOSA algorithm was achieved .The experimental results show that the algorithm has a good performance in scheduling time and load balan -cing .