Intra-domain traffic engineering with shortest path routing protocols

In this paper we address unbalanced spatial distribution of hub-level flows in an optimal hub-and-spoke network structure of median-type models. Our study is based on a rather general variant of the multiple allocation hub location problems with fixed setup costs for hub nodes and hub edges in both capacitated and uncapacitated variants wherein the number of hub nodes traversed along origin-destination pairs is not constrained to one or two as in the classical models.. From the perspective of an infrastructure owner, we want to make sure that there exists a choice of design for the hub-level sub-network (hubs and hub edges) that considers both objectives of minimizing cost of transportation and balancing spatial distribution of flow across the hub-level network. We propose a bi-objective (transportation cost and hub-level flow variance) mixed integer non-linear programming formulation and handle the bi-objective model via a compromise programming framework. We exploit the structure of the problem and propose a second-order conic reformulation of the model along with a very efficient matheuristics algorithm for larger size instances.

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“…The general form of such a load balancing objective function for the hub edges (Ü kl ) follows (Altın et al 2009):…”

Section: Uncapacitated De-stressed Fixed Cardinality Hub Location Promentioning

confidence: 99%

Bi-objective load balancing multiple allocation hub location: a compromise programming approach

et al. 2020

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“…As an example, some studies conducted in this area focus on the configuration optimization of commonly used routing 1845-6421/09/8474 © 2016 CCIS protocols (e.g. [6], [7]) while others propose new routing approaches to attain more efficient traffic distribution (e.g. [22]) in ISP networks.…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, other approaches also focus on the use of a single shortest path between a given network source and destination [17] or, based in the work present in [18], also tackle such TE problem assuming that non-shortest paths may also be used to improve load-balancing levels and achieve a better distribution of traffic within the network infrastructure [19]. In a global perspective, in [20] the authors presents an extensive study overviewing several TE optimization techniques and approaches that have been deployed for managing intradomain routing in networks operated with shortest path routing protocols.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Improving Routing Configurations using Multi-Objective Optimization Mechanisms

Sousa

Pereira

Cortez

et al. 2017

JCOMSS

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IP networks are nowadays well established technologiesbeing used to support a myriad of applications and services,thus assuming a crucial role in todays telecommunication systems. Nevertheless, such infrastructures usually require network administrators to perform a wide set of complex planning and management tasks trying to attain adequate network configurations. Many of such management tasks can be mathematically formulated as NP-hard optimization problems, sometimes involving several objective functions. In this context, this work explores and demonstrates the potential of using computational intelligence methods as optimization engines to tackle complex network optimization problems. In particular, Multi-objective Evolutionary Algorithms (MOEAs) are used to attain near-optimal link state routing configurations robust to distinct operational conditions. As result, network administrators will be provided with a set of alternative routing configurations representing distinct tradeoffs between the considered optimization goals. The robustness of the proposed methods is illustrated by presenting several multiobjective optimization examples able to improve the performance and resilience levels of a network infrastructure. In this perspective, this work presents a contribution for this research area by proposing specific MOEAs based optimization methods able to improve network routing configurations. Furthermore, the devised methods are also integrated in a freely available Traffic Engineering optimization framework able to be used by network administrators interested in improving the routing configurations of their network infrastructures.

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“…This paper provides a survey of meta‐heuristics techniques for the OSPF weight setting problem and some of its extensions. Another recent survey by Altın et al (2009) also discusses in more detail the origins of the problem, the possible choices of objective functions, and exact methods for the problem. In , we survey meta‐heuristics that have been proposed to solve the basic version of the problem.…”

Section: Introductionmentioning

confidence: 99%

Applications of meta-heuristics to traffic engineering in IP networks

Fortz

2010

International Transactions in Operational Research

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Intra-domain routing protocols are based on shortest path first (SPF) routing, where shortest paths are calculated between each pair of nodes (routers) using pre-assigned link weights, also referred to as link metric. These link weights can be modified by network administrators in accordance with the routing policies of the network operator. The operator's objective is usually to minimize traffic congestion or minimize total routing cost subject to the traffic demands and the protocol constraints. However, determining a link weights combination that best suits the network operator's requirements is a difficult task.This paper provides a survey of meta-heuristic approaches to traffic engineering, focusing on local search approaches and extensions to the basic problem taking into account changing demands and robustness issues with respect to network failures.

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Intra-domain traffic engineering with shortest path routing protocols

Cited by 27 publications

References 43 publications

Bi-objective load balancing multiple allocation hub location: a compromise programming approach

Bi-objective load balancing multiple allocation hub location: a compromise programming approach

A Framework for Improving Routing Configurations using Multi-Objective Optimization Mechanisms

Applications of meta-heuristics to traffic engineering in IP networks

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