Simple Destination-Swap Strategies for Adaptive Intra- and Inter-Tenant VM Migration

TL;DR

This paper presents simple, adaptive VM migration strategies that optimize communication costs by dynamically relocating VMs within and across tenants, balancing efficiency and locality in virtualized environments.

Contribution

It introduces a formal model for online VM migration and proposes Destination-Swap algorithms inspired by splay structures, with variants for different migration scenarios.

Findings

Inter-tenant migration offers greater optimization potential.

Locality-aware indirect strategies perform well under skewed communication.

Algorithms react quickly to load changes with minimal local information.

Abstract

This paper investigates the opportunities and limitations of adaptive virtual machine (VM) migration to reduce communication costs in a virtualized environment. We introduce a new formal model for the problem of online VM migration in two scenarios: (1) VMs can be migrated arbitrarily in the substrate network; e.g., a private cloud provider may have an incentive to reduce the overall communication cost in the network. (2) VMs can only be migrated within a given tenant; e.g., a user that was assigned a set of physical machines may exchange the functionality of the VMs on these machines. We propose a simple class of Destination-Swap algorithms which are based on an aggressive collocation strategy (inspired by splay datastructures) and which maintain a minimal and local amount of per-node (amortized cost) information to decide where to migrate a VM and how; thus, the algorithms react quickly to changes in the load. The algorithms come in two main flavors, an indirect and distributed variant which keeps existing VM placements local, and a direct variant which keeps the number of affected VMs small. We show that naturally, inter-tenant optimizations yield a larger potential for optimization, but generally also a tenant itself can improve its embedding. Moreover, there exists an interesting tradeoff between direct and indirect strategies: indirect variants are preferable under skewed and sparse communication patterns due to their locality properties.