Online Strategies for Intra and Inter Provider Service Migration in Virtual Networks

TL;DR

This paper explores online algorithms for service migration in virtual networks, balancing QoS improvements with migration costs, supported by simulations and competitive analysis.

Contribution

It introduces new online algorithms with provable guarantees for intra- and inter-provider service migration in virtual networks.

Findings

Proposed algorithms achieve good tradeoffs between QoS and migration costs.

Simulation results validate the effectiveness of the algorithms.

Constructed an optimal offline algorithm for benchmarking.

Abstract

Network virtualization allows one to build dynamic distributed systems in which resources can be dynamically allocated at locations where they are most useful. In order to fully exploit the benefits of this new technology, protocols need to be devised which react efficiently to changes in the demand. This paper argues that the field of online algorithms and competitive analysis provides useful tools to deal with and reason about the uncertainty in the request dynamics, and to design algorithms with provable performance guarantees. As a case study, we describe a system (e.g., a gaming application) where network virtualization is used to support thin client applications for mobile devices to improve their QoS. By decoupling the service from the underlying resource infrastructure, it can be migrated closer to the current client locations while taking into account migration cost. This paper identifies the major cost factors in such a system, and formalizes the corresponding optimization problem. Both randomized and deterministic, gravity center based online algorithms are presented which achieve a good tradeoff between improved QoS and migration cost in the worst-case, both for service migration within an infrastructure provider as well as for networks supporting cross-provider migration. The paper reports on our simulation results and also presents an explicit construction of an optimal offline algorithm which allows, e.g., to evaluate the competitive ratio empirically.