Reactive Failure Mitigation through Seamless Migration in Telecom Infrastructure Networks

TL;DR

This paper proposes a cost-effective, reactive failure mitigation approach in telecom networks by seamlessly migrating additive functions within a time limit, using a novel optimization model and heuristic algorithms.

Contribution

It introduces a new model for reactive failure mitigation dividing functions into core and additive, and develops heuristic algorithms for cost-efficient migration within TAT constraints.

Findings

The proposed algorithms effectively minimize migration costs.

The model ensures additive functions are migrated within their TAT.

Numerical results validate the efficiency of the heuristic solutions.

Abstract

Various methods are proposed in the literature to mitigate the failures in an infrastructure network. Failure mitigation can be carried out in an active or passive manner. In active manner, live backups provide the required reliability. Due to the high cost of active backups, failures can be mitigated in a reactive manner where mitigation starts when a function fails. In this paper, network functions are divided into two classes of essential (i.e., core) functions and additive (i.e., service) functions. Core functions need active backups and cannot tolerate any failure. However, additive functions do not require backups and their absence is tolerable in short periods. Maximum tolerable (function) absence time (TAT) is a measure used for their reliability level. In our model and within the mitigation process, first, the backup host to migrate the failed function is selected. Then, the state of the function is migrated. The process should be carried out in less than TAT. An optimization problem is formulated investigating cost-effective failure mitigation of additive functions. The problem is of mixed integer non convex form. To tackle the computational complexity, it is bisected into two back-to-back leader-follower parts. The leader selects the migration destinations and the follower divides network resources among functions for migration. These problems are both NP-hard. For the leader problem, a central heuristic based on the Viterbi algorithm suggested. The follower problem is converted into two convex sub-problems. The validity of the proposed algorithms is proved via extensive numerical results.