In a cloud computing environment, the number of virtual machines (VMs) on a single\nphysical server and the number of applications running on each VM are continuously growing.\nThis has led to an enormous increase in the demand of memory capacity and subsequent increase\nin the energy consumption in the cloud. Lack of enough memory has become a major bottleneck\nfor scalability and performance of virtualization interfaces in cloud computing. To address this\nproblem, memory deduplication techniques which reduce memory demand through page sharing\nare being adopted. However, such techniques suffer from overheads in terms of number of online\ncomparisons required for the memory deduplication. In this paper, we propose a static memory\ndeduplication (SMD) technique which can reduce memory capacity requirement and provide\nperformance optimization in cloud computing. The main innovation of SMD is that the process of\npage detection is performed offline, thus potentially reducing the performance cost, especially in\nterms of response time. In SMD, page comparisons are restricted to the code segment, which has the\nhighest shared content. Our experimental results show that SMD efficiently reduces memory capacity\nrequirement and improves performance.We demonstrate that, compared to other approaches, the cost\nin terms of the response time is negligible.
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