Energy-Efficiency vs. Resilience

Publication

Here, the information related to our paper on energy-efficient optimized design of resilient optical network with risk-awareness is given. The paper entitled “Energy-efficiency vs. resilience. Risk-awareness perspective on dimensioning of optical networks with a sleep mode”, authored by Piotr Chołda and Piotr Jaglarz, has been published in Photonic Network Communications journal (by Springer) in August 2015.

When using or inspiring by the given configuration files (either changed or not), please properly reference the way you obtained the files, preferably by citing the related paper.

 

Details of the optimization algorithms

Exact optimization is realized with CPLEX (the problems are written in OPL). The formulations are quite typical for convex programming-based resilient network design inspired by the Pioro & Medhi book:

  • Network data for the German network (Ge) for NR: .DAT file.
  • Network data for the German network (Ge) for DP/SP: (please contact me).
  • Network data for the German network (Ge) for DL/SL: (please contact me).

MATLAB algorithm uses heuristic based on the Yaged’s approach. MATLAB code supporting optimization : .M files.

Results for the coarse-grained case

The results are grouped on the basis of the used optimization method (where in the first case we base on the optimization of working paths only and in the second case also on the joint optiomization of both working and protection paths) and on the applied compensation policy (either availability-based [cumulative downtime], Av, or continuity-based [number of outages], Co).

MATLAB code supporting simulations: .M files.

The following results have been obtained:

  • PL network, Av compensation policy: .XLS file.
  • PL network, Co compensation policy: .XLS file.
  • Ge network, Av compensation policy: .XLS file.
  • Ge network, Co compensation policy: .XLS file.

Optimization for the fine-grained case

Here, we optimized the mixed combination of recovery methods for selected risk mitigation strategies.

Optimization is again realized with CPLEX. The formulation is given in the paper:

Formulation of the problem if the budget is based on energy usage: .MOD file.

Network data for the Poland network (PL) if the budget is based on energy usage: .DAT file.

Formulation of the problem if the budget is based on reserved capacity: .MOD file.

Network data for the Poland network (PL) if the budget is based on reserved capacity: .DAT file.

 

Results for the f+p energy profiles

The following results have been obtained:

Updated version

In recent months, we have elaborted a new iterative optimization-simulation method to find the fine-grained selection of recovery options. It can be found here.