Tunable QoS-Aware Network Survivability

TL;DR

This paper introduces a flexible approach to network survivability that allows specifying desired protection levels and optimizes routing for additive QoS criteria, significantly improving performance with minimal survivability trade-offs.

Contribution

It develops efficient algorithms for tunable survivability considering additive QoS metrics and demonstrates substantial QoS improvements through simulations and network design applications.

Findings

Up to 2x improvement in end-to-end QoS performance.

Negligible reduction in survivability level.

Effective algorithms for additive QoS criteria optimization.

Abstract

Coping with network failures has been recognized as an issue of major importance in terms of social security, stability and prosperity. It has become clear that current networking standards fall short of coping with the complex challenge of surviving failures. The need to address this challenge has become a focal point of networking research. In particular, the concept of \textbf{\emph{tunable survivability}} offers major performance improvements over traditional approaches. Indeed, while the traditional approach aims at providing full (100\%) protection against network failures through disjoint paths, it was realized that this requirement is too restrictive in practice. Tunable survivability provides a quantitative measure for specifying the desired level (0\%-100\%) of survivability and offers flexibility in the choice of the routing paths. Previous work focused on the simpler class of "bottleneck" criteria, such as bandwidth. In this study, we focus on the important and much more complex class of \emph{additive} criteria, such as delay and cost. First, we establish some (in part, counter-intuitive) properties of the optimal solution. Then, we establish efficient algorithmic schemes for optimizing the level of survivability under additive end-to-end QoS bounds. Subsequently, through extensive simulations, we show that, at the price of \emph{negligible} reduction in the level of survivability, a major improvement (up to a factor of $2$) is obtained in terms of end-to-end QoS performance. Finally, we exploit the above findings in the context of a network design problem, in which, for a given investment budget, we aim to improve the survivability of the network links.