Queuing Model with Customer Class Movement across Server Groups for Analyzing Virtual Machine Migration in Cloud Computing

Anna Kushchazli, Anastasia Safargalieva, Irina Kochetkova () and Andrey Gorshenin
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Anna Kushchazli: Institute of Computer Science and Telecommunications, RUDN University, 6 Miklukho-Maklaya St., 117198 Moscow, Russia
Anastasia Safargalieva: Institute of Computer Science and Telecommunications, RUDN University, 6 Miklukho-Maklaya St., 117198 Moscow, Russia
Irina Kochetkova: Institute of Computer Science and Telecommunications, RUDN University, 6 Miklukho-Maklaya St., 117198 Moscow, Russia
Andrey Gorshenin: Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilova St., 119333 Moscow, Russia

Mathematics, 2024, vol. 12, issue 3, 1-20

Abstract: The advancement of cloud computing technologies has positioned virtual machine (VM) migration as a critical area of research, essential for optimizing resource management, bolstering fault tolerance, and ensuring uninterrupted service delivery. This paper offers an exhaustive analysis of VM migration processes within cloud infrastructures, examining various migration types, server load assessment methods, VM selection strategies, ideal migration timing, and target server determination criteria. We introduce a queuing theory-based model to scrutinize VM migration dynamics between servers in a cloud environment. By reinterpreting resource-centric migration mechanisms into a task-processing paradigm, we accommodate the stochastic nature of resource demands, characterized by random task arrivals and variable processing times. The model is specifically tailored to scenarios with two servers and three VMs. Through numerical examples, we elucidate several performance metrics: task blocking probability, average tasks processed by VMs, and average tasks managed by servers. Additionally, we examine the influence of task arrival rates and average task duration on these performance measures.

Keywords: cloud computing; virtual machine migration; overloaded server; queuing system; continuous-time Markov chain; blocking probability; virtual machine load; server load (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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