In this paper, we propose a synchronization-aware VM scheduler for parallel applications in Xen. The proposed scheduler prevents threads from waiting for a significant amount of time during synchronization. For this purpose, we propose an identification scheme that can identify the threads that have awaited other threads for a long time. In this scheme, a detection module that can infer the internal status of guest OSs was developed. We also present a scheduling policy that can accelerate bottlenecks of concurrent VMs. We implemented our VM scheduler in the recent Xen hypervisor with para-virtualized Linux-based operating systems. We show that our approach can improve the performance of concurrent VMs by up to 43% as compared to the credit scheduler.

This paper proposes a rate adjustment scheme for inbound data traffic on a virtualized host. Most prior studies on network virtualization have only focused on outbound traffic, yet many cloud applications rely on inbound traffic performance. The proposed scheme adjusts the inbound rates of virtual network interfaces dynamically in proportion to the bandwidth demands of the virtual machines.

Facing practical limits to increasing processor frequencies, manufacturers have resorted to multi-core designs in their commercial products. In multi-core implementations, cores in a physical package share the last-level caches to improve inter-core communication. To efficiently exploit this facility, operating systems must employ cache-aware schedulers. Unfortunately, virtualization software, which is a foundation technology of cloud computing, is not yet cache-aware or does not fully exploit the locality of the last-level caches. In this paper, we propose a cache-aware virtual machine scheduler for multi-core architectures. The proposed scheduler exploits the locality of the last-level caches to improve the performance of concurrent applications running on virtual machines. For this purpose, we provide a space-partitioning algorithm that migrates and clusters communicating virtual CPUs (VCPUs) in the same cache domain. Second, we provide a time-partitioning algorithm that co-schedules or schedules in sequence clustered VCPUs. Finally, we present a theoretical analysis that proves our scheduling algorithm is more efficient in supporting concurrent applications than the default credit scheduler in Xen. We implemented our virtual machine scheduler in the recent Xen hypervisor with para-virtualized Linux-based operating systems. We show that our approach can improve performance of concurrent virtual machines by up to 19% compared to the credit scheduler.