Live migration is widely used in cloud platforms to transfer Virtual Machines (VMs) from one physical machine to another. Live migration is useful for workload consolidation, load balancing, failure management, and energy savings. Copy-on-write (COW) page sharing allows identical pages to be shared both within a VM and across co-located VMs to reduce their collective memory footprint. Current live migration techniques are not aware of such page sharing; thus they do not preserve pre-existing page sharing when migrating VMs to a common destination machine. Consequently, each shared page is replicated at the destination multiple times as if they were separate pages. This expansion of the memory footprint of VMs during migration can lead to problems such as migration failure, increased network traffic, and longer migration times. We propose Sharing-aware Live Migration (SLM), which preserves pre-existing COW page sharing within and across VMs that are migrated to a common destination machine. The key idea is to identify guest pages that are mapped to the same physical page at the source machine and to map them to the same physical page at the destination. We present SLM technique for both pre-copy and post-copy live migration of multiple VMs and describe its implementation on the KVM/QEMU virtualization platform. Our evaluations show that SLM successfully preserves pre-existing COW page sharing during migration, eliminates the risk of migration failure due to memory expansion, and reduces total migration time and network traffic overhead.

One of the key challenges of edge computing is managing the limited resources available at the edge, especially memory and network bandwidth. Virtual machines (VMs) can ensure both isolation and efficient resource utilization within the edge computing infrastructure.Live migration is a crucial technique in edge computing infrastructure to transfer running VMs from one physical node to another. This can occur either within the same host (Intra-host) or between different hosts (Inter-host). Current live migration techniques face challenges, such as lack of awareness of duplicated pages for inter-host migration and inefficient handling of co-located memory for intra-host migration.In this paper, we describe our work on three efficient ways to incorporate sharing-awareness in live migration of multiple VMs while avoiding memory and network resource contention. For inter-host migration, our techniques rely on existing Copy-On-Write (COW) optimization performed by the host/hypervisor. This enables the transfer of a copy of the page only once and preserves existing COW sharing by remapping them at the destination. For intra-host migration, our technique implements a mechanism to identify shared pages and transfer their ownership (via a userfaultfd-based mechanism) instead of copying them. Besides reducing network traffic and memory footprint by eliminating unwanted copying, our techniques also result in a shorter total migration time, thereby freeing additional resources involved in migration as quickly as possible.

One of the key challenges of edge computing is working with a limited amount of resources available at the edge, especially memory and bandwidth. Virtual Machine (VM) Templating is a technique to start multiple VM instances quickly from a shared pre-configured read-only image (or template). The new VM instances share the memory of the template in a copy-on-write (COW) manner. In edge computing platforms, VM templating can help to reduce the collective memory footprint and deployment time of multiple VMs. Live migration of VMs can also improve task placement on edge nodes for latency reduction, service availability, and cost-effectiveness. However, existing live migration techniques fail to maintain memory sharing among multiple templated VMs that are migrated to a common destination. Consequently, identical pages at the source are replicated several times at the destination, increasing memory pressure on the destination node, network traffic during migration, and total migration time. Lack of templating awareness can also trigger migration failure if the destination lacks sufficient memory to accommodate the increased memory footprint. To address this shortcoming of live migration, we introduce Template-aware Live Migration (TLM), which preserves preexisting COW memory sharing between templated VMs that are migrated to a common destination machine. Specifically, TLM ensures that multiple virtual pages from different VMs that are mapped to the same template page at the source are mapped to the same page at the destination. We implement TLM on the QEMU/KVM virtualization platform and demonstrate a significant reduction in memory footprint, shorter migration time, and reduced network traffic.

A Confidential Virtual Machine (CVM) is a virtual machine (VM) whose memory is encrypted using trusted hardware support to prevent unauthorized access to its contents, including by the hypervisor. AMD Secure Encrypted Virtualization (SEV) provides hardware support for CVMs on AMD processors and has been used by several cloud operators to provide trusted execution environments to cloud users. In this paper, we examine the performance overheads of CVMs across three generations of AMD SEV using a number of CPU, memory, and I/O benchmarks. Our findings indicate that CPU -intensive workloads running on a CVM do not experience significant performance difference compared to a non-confidential VM. However, we observe that some workloads that are sensitive to cache/memory latency may experience a performance drop of up to 2.5%. Pure memory-intensive workloads are observed to experience up to 4.3% overhead. Disk I/O from CVMs experiences a significant performance impact when using SEV, with up to a 56% performance penalty. Network I/O, on the other hand, experiences up to a 36% overhead. Workloads with a mix of memory and I/O accesses experience an overhead of up to 14%. Our work complements and extends the existing understanding of the performance of this important and rapidly evolving technology.