.png){kind=icon}
Return
Static Memory Deduplication for Performance Optimization in Cloud Computing
.png){kind=icon}
OA
AI
DOI：10.3390/s17050968.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In a cloud computing environment, the number of virtual machines (VMs) on a single physical server and the number of applications running on each VM are continuously growing. This has led to an enormous increase in the demand of memory capacity and subsequent increase in the energy consumption in the cloud. Lack of enough memory has become a major bottleneck for scalability and performance of virtualization interfaces in cloud computing. To address this problem, memory deduplication techniques which reduce memory demand through page sharing are being adopted. However, such techniques suffer from overheads in terms of number of online comparisons required for the memory deduplication. In this paper, we propose a static memory deduplication (SMD) technique which can reduce memory capacity requirement and provide performance optimization in cloud computing. The main innovation of SMD is that the process of page detection is performed offline, thus potentially reducing the performance cost, especially in terms of response time. In SMD, page comparisons are restricted to the code segment, which has the highest shared content. Our experimental results show that SMD efficiently reduces memory capacity requirement and improves performance. We demonstrate that, compared to other approaches, the cost in terms of the response time is negligible.
Keywords:
main memory
memory deduplication
cloud computing
virtualization
performance
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.5
Papers:
7.2W
Citations:
20.9W
Organization
Cited Papers
ShareSave
ShareSaveShareSaveShareSaveManaging Performance Overhead of Virtual Machines in Cloud Computing: A Survey, State of the Art, and Future Directions.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
ShareSaveDynamic Resource Partitioning for Heterogeneous Multi-Core-Based Cloud Computing in Smart CitiesIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSaveA Privacy-Preserving and Copy-Deterrence Content-Based Image Retrieval Scheme in Cloud Computing
PREAI
ShareSave
View more