Link Failure Recovery Over Large Arbitrary Networks: The Case of Coding

Abstract

Network coding-based link failure recovery techniques provide near-hitless recovery and offer high capacity efficiency. Diversity coding is the first technique to incorporate coding in this field and is easy to implement over small networks. However, the capacity efficiency of this implementation is restricted by its systematic coding and high design complexity despite having lower complexity than the other coding-based recovery techniques. In this paper, we propose a simple column generation-based design algorithm and a novel advanced diversity coding technique to achieve near-hitless recovery over large networks. The traffic matrix, which consists of unicast connection demands, is decomposed into traffic vectors for each destination node. Further, the connection demands in each traffic vector are partitioned into coding groups. The design framework consists of two parts: a main problem and a subproblem. The main problem is solved with Linear Programming (LP) and Integer Linear Programming (ILP), whereas the subproblem can be solved with different methods. Simulation results suggest that the novel design algorithm simplifies the capacity placement problem, which enables implementing diversity coding-based recovery including the novel coding structure on large networks with arbitrary topology. It achieves near-hitless recovery with an almost optimal capacity efficiency for any single destination-based recovery.