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Coordinate Memory Deduplication and Partition for Improving Performance in Cloud Computing
DOI:10.1109/TCC.2015.2511738.png)
摘要
En 中文
Both limited main memory size and memory interference are considered as the major bottlenecks in virtualization environments. Memory deduplication, detecting pages with same content and being shared into one single copy, reduces memory requirements; memory partition, allocating unique colors for each virtual machine according to page color, reduces memory interference among virtual machines to improve performance. In this paper, we propose a coordinate memory deduplication and partition approach named CMDP to reduce memory requirement and interference simultaneously for improving performance in virtualization. Moreover, CMDP adopts a lightweight page behavior-based memory deduplication approach named BMD to reduce futile page comparison overhead meanwhile to detect page sharing opportunities efficiently. And a virtual machine based memory partition called VMMP is added into CMDP to reduce interference among virtual machines. According to page color, VMMP allocates unique page colors to applications, virtual machines and hypervisor. The experimental results show that CMDP can efficiently improve performance (by about 15.8 percent) meanwhile accommodate more virtual machines concurrently.
Keyword:
Main memory
memory deduplication
memory partition
virtualization
performance
期刊
I
IF:
5
论文数:
1.9K
被引数:
4.3K
机构
引用论文
PARS: A scheduling of periodically active rank to optimize power efficiency for main memoryPARS: 用于优化主内存功率效率的周期性活动等级调度
Managing Performance Overhead of Virtual Machines in Cloud Computing: A Survey, State of the Art, and Future Directions
PROCEEDINGS OF THE IEEE
IF25.9

