Symmetric multiprocessing (SMP) virtual machines (VMs) allow users to take advantage of a multiprocessor infrastructure. Despite the advantage, SMP VMs can cause synchronization latency to increase significantly, depending on task scheduling. In this paper, we show that even if a SMP VM runs non-concurrent applications, the synchronization latency problem can still occur due to synchronization in the VM kernel.Our experiments show that both of the widely used open source hypervisors, Xen and KVM, with the default schedulers are susceptible to the synchronization latency problem. To remediate this problem, previous works propose a co-scheduling solution where virtual CPUs (vCPUs) of a SMP VM are scheduled simultaneously. However, the co-scheduling approach can cause CPU fragmentation that reduces CPU utilization, priority inversion that degrades I/O performance, and execution delay, leading to deployment impediment. We propose a balance scheduling algorithm which simply balances vCPU siblings on different physical CPUs without forcing the vCPUs to be scheduled simultaneously. Balance scheduling can achieve similar or (up to 8%) better application performance than co-scheduling without the co-scheduling drawbacks, thereby benefiting various SMP VMs. The evaluation is thoroughly conducted against both concurrent and non-concurrent applications with CPU-bound, I/Obound, and network-bound workloads in KVM. For empirical comparison, we also implement the coscheduling algorithm on top of KVM's Completely Fair Scheduler (CFS). Compared to the synchronizationunaware CFS, balance scheduling can significantly improve application performance in a SMP VM (e.g. reduce the average TPC-W response time by up to 85%).
Virtualization allows us to consolidate multiple servers onto a single physical machine, saving infrastructure cost. Yet, consolidation can lead to performance degradation, jeopardizing Service Level Agreement (SLA). In this paper, we analyze and identify the factors to the performance degradation due to consolidation -that is the wait time and the ready time. The wait time is the queuing time caused by other virtual machines (VMs). The ready time is the time the resource takes to be ready to service, such as the seek time incurred in traditional storage. The ready time can substantially deteriorate the request response time. Unfortunately, existing schedulers can only manage the wait time, but not the ready time. To control both quantities, we propose an adaptive disk scheduler called DPack. DPack schedules the VMs based on the likelihood of the VM failing the SLAs. DPack then adjusts the exclusive access time based on the VM resource access prediction. DPack considers the workload changes and request arrival to enhance robustness. We develop DPack based on the default disk scheduler in KVM and evaluate it against several existing disk schedulers available in KVM and Xen. The results show that DPack can improve the 99 th percentile response time up to 76%. In the highly consolidated environment, DPack can also satisfy all the SLAs, while the other schedulers cannot meet the SLAs for at least 50% of the VMs.Index Terms -Adaptive scheduling, virtual machine, quality of service, web services, disk scheduler, hypervisor.
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