Green and resilient design of telecom networks with shared backup resources

Abstract Backbone telecommunication network infrastructures are deployed with redundant resources taking into account the backup capacity for protection in order to be resilient against link failures, and serving extremely large amount of data transmission resulting in increasing power consumption. In this study, the interplay between green and resilient network design, and flow routing mechanisms is analyzed. We propose Mixed Integer Linear Programming (MILP) models to obtain optimum solutions under various objectives: Minimizing consumption of (I) Capacity, (II) Capacity+Power, and (III) Power. Two different shared backup protection (SBP) schemes (1) SBP-ind (failure independent) and (2) SBP-dep (failure dependent) are compared with dedicated path protection (DPP). It is assumed that network links utilized by only backup paths can be put into sleep mode. It is observed that when power consumption is minimized, the backup sharing decreases in SBP and, in the extreme case, it behaves similar to DPP. The models are generalized and valid for both IP traffic flow routing and lightpath routing. It is shown that for a sample network topology, to save e.g., 32.33% power, capacity consumption increases significantly, e.g., in SBP-ind up to 127.53%. In order to achieve a compromise between power and capacity consumption, we propose a multi-objective approach. All the MILP models are run and results are presented for a small scale European network topology as well as a larger scale sample US network topology. For larger problem instances ILP solutions are not scalable. Therefore, a novel energy efficient and survivable routing and network design algorithm, called energy-aware shared path protection (EASPP), addressing the trade-off caused by conflicting objectives of green and resilient network planning is proposed. Moreover this study presents a complete picture of various survivability mechanisms when power consumption is minimized together with the capacity consumption.

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