Coordinate Memory Deduplication and Partition for Improving Performance in Cloud Computing

[EN] 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.This work was supported by "Qing Lan Project", "the National Natural Science Foundation of China under Grants 61572172, 61401147, and 61572164", " the Natural Science Foundation of Jiangsu Province of China, Nos. BK20131137 and BK20140248", "Zhejiang provincial Natural Science Foundation Nos. LQ14F020011 and LQ12F02003", by Instituto de Telecomunicacoes, Next Generation Networks and Applications Group (NetGNA), Covilha Delegation, Portugal and by National Funding from the FCT Fundacao para a Ciencia e a Tecnologia through the UID/EEA/500008/2013 Project. Guangjie Han is the corresponding author.Jia, G.; Han, G.; Rodrigues, JJPC.; Lloret, J.; Li, W. (2019). Coordinate Memory Deduplication and Partition for Improving Performance in Cloud Computing. IEEE Transactions on Cloud Computing. 7(2):357-368. https://doi.org/10.1109/TCC.2015.25117383573687