摘要
为提高MapReduce在异构云计算环境下的执行效率,提出一种异构环境下基于负载类型的自适应调度算法——adaptive scheduler based on workload type in heterogeneous environment(ASBT-HE),通过反馈运行结果到Job Tracker,将后续任务根据负载类型分配到相应的Task Trackers上。但为满足用户的Qo S需求、更好的平衡系统负载,将该算进一步法优化为Better ASBT-HE(BASBT-HE)。BASBT-HE能够在考虑Qo S约束的基础上根据负载情况自动调整ASBT-HE中队列的长度。仿真实验结果表明优化后的MapReduce在异构云计算环境下具有高效性,并且考虑了用户Qo S需求,简化了系统参数配置。
To improve the efficiency of MapReduce in heterogeneous cloud computing environment, an adaptive scheduler is presented based on workload type in heterogeneous environment （ASBT-HE）. It feeds back results to the JobTracker to assign subsequent tasks to corresponding TaskTrackers. But in order to meet user＇ s QoS require- ments and better balance the loads of system, ASBT-I-IE is optimized a better ASBT-HE （BASBT-HE）. On the ba- sis of considering the QoS constraints, BASBT-HE can adjust the length of queues in ASBT-HE automatically ac- cording to the actual loads. The ruslts of simulation experiments show that the optimized MapReduce has high effi- ciency in heterogeneous cloud computing environment. And it considers the user＇ s QoS requirements and simplifies the system configuration.
出处
《科学技术与工程》
北大核心
2014年第31期73-77,共5页
Science Technology and Engineering
基金
河北省高等学校科学技术研究重点项目(ZD2014054)
河北省重点基础研究项目(14964206D)资助
