Live migration of virtual machine memory content in networked systems

Enterprises are increasingly outsourcing their computing needs to cloud computing. This dependency on cloud services requires uninterrupted and high availability of services. However, achieving the availability of services is not always possible because cloud services may need to be temporarily suspended for several reasons. These include real-time maintenance of cloud infrastructure, load balancing of services, deployment of countermeasures against cyber attacks, power management, proactive fault tolerance, or resource utilization, etc. The unavailability of critical cloud services may negatively impact the business model of cloud providers because clients would likely be unhappy with frequent service interruptions. One solution to this service interruption is real-time Live Machine Migration (LVM) - a virtualization technique in network-based systems involving migrating virtual machines (VMs) from one host to another. The key objective of LVM is to avoid or minimize the interruption of application services running on a VM during the migration from a source to a destination host server. To achieve this objective, some challenges need to be tackled. An optimal LVM approach first needs to address the challenge of simultaneously minimizing downtime, network resource usage for migration, and total migration time. Several optimization techniques have been proposed for enhancing the performance of LVM. This paper provides a comprehensive review of the LVM challenges particularly focusing on memory content migration and the proposed solutions to overcome the identified challenges and their limitations. The paper also points out some open research issues and future directions towards optimizing LVM.

Automated summary

As enterprises outsource their computing needs to cloud computing, the availability of cloud services becomes increasingly important. One solution to service interruption is real-time Live Machine Migration (LVM), which aims to minimize downtime during the migration of virtual machines. This paper reviews the challenges of LVM, particularly focusing on memory content migration, and discusses proposed solutions to overcome these challenges and optimize LVM.