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In cloud systems, computing resources, such as the CPU, memory, network, and storage devices, are virtualized and shared by multiple users. In recent decades, methods to virtualize these resources efficiently have been intensively studied. Nevertheless, the current virtualization techniques cannot achieve effective I/O virtualization when packets are transferred between a virtual machine and a host system. For example, VirtIO, which is a network device driver for KVM-based virtualization, adopts an interrupt-based packet-delivery mechanism, and incurs frequent switch overheads between the virtual machine and the host system. Therefore, VirtIO wastes valuable CPU resources and decreases network performance. To address this limitation, this paper proposes an adaptive polling-based network I/O processing technique, called NetAP, for virtualized environments. NetAP processes network requests via a periodical polling-based mechanism. For this purpose, NetAP adopts the golden-section search algorithm to determine the near-optimal polling interval for various workloads with different characteristics. We implement NetAP in a Linux kernel and evaluated it with up to six virtual machines. The evaluation results show that NetAP can improve the network performance of virtual machines by up to 31.16%, while only using 32.92% of the host CPU time used by VirtIO for packet processing.
Hyunchan Park; Juyong Seong; Munkyu Lee; Kyungwoon Lee; Cheol-Ho Hong. NetAP: Adaptive Polling Technique for Network Packet Processing in Virtualized Environments. Applied Sciences 2020, 10, 5219 .
AMA StyleHyunchan Park, Juyong Seong, Munkyu Lee, Kyungwoon Lee, Cheol-Ho Hong. NetAP: Adaptive Polling Technique for Network Packet Processing in Virtualized Environments. Applied Sciences. 2020; 10 (15):5219.
Chicago/Turabian StyleHyunchan Park; Juyong Seong; Munkyu Lee; Kyungwoon Lee; Cheol-Ho Hong. 2020. "NetAP: Adaptive Polling Technique for Network Packet Processing in Virtualized Environments." Applied Sciences 10, no. 15: 5219.
In cloud computing, a shared storage server, which provides a network-attached storage device, is usually used for centralized data management. However, when multiple virtual machines (VMs) concurrently access the storage server through the network, the performance of each VM may decrease due to limited bandwidth. To address this issue, a flash-based storage device such as a solid state drive (SSD) is often employed as a cache in the host server. This host-side flash cache saves remote data, which are frequently accessed by the VM, locally in the cache. However, frequent VM migration in the data center can weaken the effectiveness of a host-side flash cache as the migrated VM needs to warm up its flash cache again on the destination machine. This study proposes Cachemior, Firepan, and FirepanIF for rapid flash-cache migration in cloud computing. Cachemior warms up the flash cache with a data preloading approach using the shared storage server after VM migration. However, it does not achieve a satisfactory level of performance. Firepan and FirepanIF use the source node’s flash cache as the data source for flash cache warm-up. They can migrate the flash-cache more quickly than conventional methods as they can avoid storage and network congestion on the shared storage server. Firepan incurs downtime of the VM during flash cache migration for data consistency. FirepanIF minimizes the VM downtime with the invalidation filter, which traces the I/O activity of the migrated VM during flash cache migration in order to invalidate inconsistent cache blocks. We implement and evaluate the three flash cache migration techniques in a realistic virtualized environment. FirepanIF demonstrates that it can improve the performance of the I/O workload by up to 21.87% compared to conventional methods.
Hyunchan Park; Munkyu Lee; Cheol-Ho Hong. FirepanIF: High Performance Host-Side Flash Cache Warm-Up Method in Cloud Computing. Applied Sciences 2020, 10, 1014 .
AMA StyleHyunchan Park, Munkyu Lee, Cheol-Ho Hong. FirepanIF: High Performance Host-Side Flash Cache Warm-Up Method in Cloud Computing. Applied Sciences. 2020; 10 (3):1014.
Chicago/Turabian StyleHyunchan Park; Munkyu Lee; Cheol-Ho Hong. 2020. "FirepanIF: High Performance Host-Side Flash Cache Warm-Up Method in Cloud Computing." Applied Sciences 10, no. 3: 1014.