ILP Model and Relaxation-Based Decomposition Approach for Incremental Topology Optimization inp-Cycle Networks

Abstract

p-cycle networks have attracted a considerable interest in the network survivability literature in recent years. However, most of the existing work assumes a known network topology upon which to apply p-cycle restoration. In the present work, we develop an incremental topology optimization ILP for p-cycle network design, where a known topology can be amended with new fibre links selected from a set of eligible spans. The ILP proves to be relatively easy to solve for small test case instances but becomes computationally intensive on larger networks. We then follow with a relaxation-based decomposition approach to overcome this challenge. The decomposition approach significantly reduces computational complexity of the problem, allowing the ILP to be solved in reasonable time with no statistically significant impact on solution optimality.

Heurística Escalável Para o Problema de Alocação de vBBU e Comprimento de Onda em Cloud-Fog RAN

“…A literatura apresenta diversos trabalhos que tratam do tempo de execuc ¸ão e da escalabilidade da PLI utilizando a relaxac ¸ão linear. As soluc ¸ões propostas aplicam diversos tipos de abordagens de relaxac ¸ão para obter valores próximos ao ótimo em uma infinidade de aplicac ¸ão de redes e de logística [Noor-E-Alam and Doucette 2012, Zaky Kasem et al 2012, Baruah et al 2019, dos Santos et al 2022. Essas soluc ¸ões mostram a busca por alternativas ou outras abordagens para resolver o problema de escalabilidade do PLI sem grande disparidade em comparac ¸ão ao resultado ótimo.…”