Simultaneous routing and flow rate optimization in energy–aware computer networks

Abstract

The issue of energy-aware traffic engineering has become prominent in telecommunications industry in the last years. This paper presents a two-criteria network optimization problem, in which routing and bandwidth allocation are determined jointly, so as to minimize the amount of energy consumed by a telecommunication infrastructure and to satisfy given demands represented by a traffic matrix. A scalarization of the criteria is proposed and the choice of model parameters is discussed in detail. The model of power dissipation as a function of carried traffic in a typical software router is introduced. Then the problem is expressed in a form suitable for the mixed integer quadratic programming (MIQP) solver. The paper is concluded with a set of small, illustrative computational examples. Computed solutions are implemented in a testbed to validate the accuracy of energy consumption models and the correctness of the proposed traffic engineering algorithm.

Solution of the Simultaneous Routing and Bandwidth Allocation Problem in Energy-Aware Networks Using Augmented Lagrangian-Based Algorithms and Decomposition

“…Instances of the problem were created for all network topologies. (a) For γ = 1, 2; δ = 1 (b) For γ = 1, 2; δ = 2 In most cases, all algorithms based on the augmented Lagrangian method dealt very well with the duality gap (the biggest value of the gap was less than 5%; in most cases, it was below 0.5%), which is a serious issue when Lagrangian relaxation is applied to MINLP problems, such as simultaneous optimization of routing and bandwidth allocation [3,4,7]. Among the algorithms tested, the standard Augmented Lagrangian method achieved the objective value with the least relative error for medium and large-sized problems.…”

“…In paper [3], an approach to solve such a simultaneous routing and flow rate optimization problem in energy-aware computer networks has been presented. The formulation considered two criteria.…”

Exact and approximation algorithms for joint routing and flow rate optimization

“…The experiments were conducted on five types of networks. The first network Net7 with 7 nodes and 10 links [9]. The second network Net22 with 22 nodes and 40 links [2].…”

“…In all the networks above each link had a capacity equal to 1. 1) Verification of algorithm performance for different network structure and size: The experiment parameters were as follows: S1 -Net7, 10 pairs as given in [9]; S2 -Net22, 10 users randomly selected 1 ; S3/4 -Net22, 20 users randomly selected 1 , S5 -Net22, 50 users randomly selected 1 ; S6 -Net64, 20 users: 10 x (1,64) and 10 x (8,57); S7/8 -Net64, 20 users randomly selected; S9/10 -Net64, 20 users randomly selected 2 ; S11 -Net42, 20 users (1,42).…”

Energy saving in carrier-grade networks: A survey

“…To avoid the complexity of frequent configuration, in their next proposal [149], the authors devise a distributed solution based only on current topology configuration and the knowledge of traffic load on links. In [150], the power consumption is reduced making use optimisation modelling for simultaneous routing and bandwidth allocation. The major benefit of this proposal is that it does not rely on the assumption that traffic matrix is known, because its cost prediction.…”