内存云架构的磁盘节能策略

Energy-efficient strategy for disks in RAMCloud

内存云(RAMCloud)的出现改善了在线数据密集型(OLDI)应用的用户体验,但其能耗高于传统的云数据中心。针对该问题,提出一种适用于该架构的磁盘节能策略。首先,引入遗传算法中适应度函数和轮盘赌法,尽量选择更为节能的磁盘进行数据持久化备份;其次,设定合理的服务器内存缓冲区来延长磁盘的平均连续空闲时间,使得部分服务器磁盘在空闲时进入待机状态。仿真实验结果表明,在50台服务器的内存云系统中,该策略能有效节能约12.69%;而缓冲区大小的设定对于节能效果和数据可用性具有双重影响,需权衡考虑。

The emergence of RAMCloud has improved user experience of Online Data-Intensive( OLDI) applications.However, its energy consumption is higher than traditional cloud data centers. An energy-efficient strategy for disks under this architecture was put forward to solve this problem. Firstly, the fitness function and roulette wheel selection which belong to genetic algorithm were introduced to choose those energy-saving disks to implement persistent data backup; secondly,reasonable buffer size was needed to extend average continuous idle time of disks, so that some of them could be put into standby during their idle time. The simulation experimental results show that the proposed strategy can effectively save energy by about 12. 69% in a given RAMCloud system with 50 servers. The buffer size has double impacts on energy-saving effect and data availability, which must be weighed.