Virtual machines pre-copy live migration cost modeling and prediction: a survey

• Published in: Distributed and parallel databases : an international journal 2022-09, Vol.40 (2-3), p.441-474
• Main Authors: Elsaid, Mohamed Esam, Abbas, Hazem M., Meinel, Christoph
• Format: Article
• Language: English
• Subjects: Algorithms; Classification; Cloud computing; Computer Science; Cost analysis; Data centers; Data Structures; Database Management; Information Systems Applications (incl.Internet); Mathematical models; Memory Structures; Modelling; Operating Systems; Parameters; Prediction models; Resource allocation; Scientific papers; Virtual environments
• ISSN: 0926-8782; 1573-7578
• DOI: 10.1007/s10619-021-07387-2

Live migration is an essential feature in virtual infrastructure and cloud computing datacenters. Using live migration, virtual machines can be online migrated from a physical machine to another with negligible service interruption. Load balance, power saving, dynamic resource allocation, and high availability algorithms in virtual data-centers and cloud computing environments are dependent on live migration. Live migration process has six phases that result in live migration cost. Several papers analyze and model live migration costs for different hypervisors, different kinds of workloads and different models of analysis. In addition, there are also many other papers that provide prediction techniques for live migration costs. It is a challenge for the reader to organize, classify, and compare live migration overhead research papers due to the broad focus of the papers in this domain. In this survey paper, we classify, analyze, and compare different papers that cover pre-copy live migration cost analysis and prediction from different angels to show the contributions and the drawbacks of each study. Papers classification helps the readers to get different studies details about a specific live migration cost parameter. The classification of the paper considers the papers’ research focus, methodology, the hypervisors, and the cost parameters. Papers analysis helps the readers to know which model can be used for which hypervisor and to know the techniques used for live migration cost analysis and prediction. Papers comparison shows the contributions, drawbacks, and the modeling differences by each paper in a table format that simplifies the comparison. Virtualized Data-center and cloud computing clusters admins can also make use of this paper to know which live migration cost prediction model can fit for their environments.