Title :
Shared Memory Optimization in Virtualized Cloud
Author :
Qi Zhang ; Ling Liu
Author_Institution :
Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
Shared memory management is widely recognized as an optimization technique in the virtualized cloud. Most current shared memory techniques allocate shared memory resources from guest VMs based on pre-defined system configurations. Such static management of shared memory not only increases the VM memory pressure, but also limits the flexibility to balance shared memory resources across multiple VMs running on a single host. In this paper, we present a dynamic shared memory management framework that enables multiple VMs to dynamically access shared memory resources according to their demands. We illustrate our system design through two case studies: One aims to improve the performance of inter-domain communication while the other aims to improve VM memory swapping efficiency. We demonstrate that the dynamic shared memory mechanism not only improves the utilization of shared memory resources but also significantly enhances the performance of VM applications. Our experimental results show that by using dynamic shared memory management, we can improve the performance of inter-VM communication by up to 45 times, while mitigating the VM memory swapping overhead by up to 58%.
Keywords :
cloud computing; optimisation; resource allocation; shared memory systems; storage management; virtual machines; VM memory pressure; VM memory swapping efficiency; dynamic shared memory management framework; shared memory optimization; shared memory resource allocation; shared memory technique; static management; virtualized cloud; Dynamic scheduling; Kernel; Memory management; Optimization; Resource management; Virtual machine monitors; Shared memory; resource management; virtualization;
Conference_Titel :
Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
Conference_Location :
New York City, NY
Print_ISBN :
978-1-4673-7286-2
DOI :
10.1109/CLOUD.2015.43