Upgrading service availability of optical networks: A labor force perspective

Abstract

Service availability is an important issue in optical networks. Much research attention has been drawn to the provisioning of reliable connections achieved by approaches such as routing and wavelength assignment and by protection and restoration mechanisms. In contrast, the research on upgrading networks to meet new or dynamic demands of service availability based on network upgrading process has been comparatively lacking. In this paper, we address this issue by upgrading service availability from the perspective of labor forces for network maintenance. Our approach is premised on the assumption that the time period for fixing an optical link can be reduced by using more network resources of labor forces. To model this concept, we conduct Amdahl's law, a well-known theorem in parallel computing, to describe human teamwork. To show the effectiveness of this concept, we propose mixed integer linear programming aiming at either maximizing service availability under limited labor forces or minimizing labor forces for predetermined service availability. In addition, a heuristic algorithm for upgrading service availability is presented.Our experimental results show that our network upgrading process can improve service availability optimally with a fixed number of forces and the proposed heuristic algorithm can effectively save computation time.

A centrality-based heuristic for network design to support availability differentiation

“…In order to achieve the desired availability values, some of the edges may have their availability upgraded while others may eventually have their availability downgraded, if it is deemed too high for the established availability goals. Therefore, it is possible to transfer some maintenance and repair capabilities between edges, which may be interesting for a company to explore [5].…”

Embedded network design to support availability differentiation

“…However, operators are constrained by the CAPEX/OPEX allocated for modifications, operations and maintenance, leaving the methods adopted subject to their efficiency (expected gain) and cost. Here, we study the scenario where each link in a network, can be purposely strengthened so that its MTBF is increased, for example by modifying the cabling (e.g., burying an aerial cable) [26,27] or adding physical protection [15,16] or the MTTR is reduced by focused maintenance and repair efforts [26,28,29]. For each link, the possible options to increase their availability can be collected and each one will result in different levels of availability and cost.…”

“…To remove the nonlinearity of the INLP, we reformulate the availability constraints following the approach in [32]: constraints set (20) can be replaced with constraint sets eqs. (26) to (28). The three constraints provide the same function as (20).…”

FRADIR: A Novel Framework for Disaster Resilience

“…Several works address how to improve the availability or reliability of transport networks against certain failure events (e.g., single link failures), such as reducing the mean time to repair (MTTR) of the links by optimized labor force allocation [9], while others use network design tools [10]- [13]. The spine concept was first presented in [14] to denote a highly available part of the network at the physical layer.…”