An Incremental Procedure for Improving Path Assignment in a Telecommunications Network

Allen, Diane E.; Ismail, I.; Kennington, Jeffery L.; Olinick, Eli V.

doi:10.1023/b:heur.0000004811.65073.d3

Cited by 11 publications

(19 citation statements)

References 19 publications

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“…The quantities to be transported can either be of a material nature such as power or goods, or of a non-material nature such as information packets, which are transported on the Internet, or influence, which is transported on social networks [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]. Optimization of network transport is thus an important problem for a variety of fields in science and technology.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, a series of algorithms have also been proposed for network traffic optimization. These algorithms are aimed at reducing link [3,4,5,6,7] or node [8,9,10,11,12] loads by a judicious link weight assignment. They have the effect of improving network transport capacity, which is defined as the rate of particle insertion at which the network becomes jammed.…”

Section: Introductionmentioning

confidence: 99%

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Transport optimization on complex networks

Danila

Marsh

et al. 2007

Chaos: An Interdisciplinary Journal of Nonlinear Science

101

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We present a comparative study of the application of a recently introduced heuristic algorithm to the optimization of transport on three major types of complex networks. The algorithm balances network traffic iteratively by minimizing the maximum node betweenness with as little path lengthening as possible. We show that by using this optimal routing, a network can sustain significantly higher traffic without jamming than in the case of shortest path routing. A formula is proved that allows quick computation of the average number of hops along the path and of the average travel times once the betweennesses of the nodes are computed. Using this formula, we show that routing optimization preserves the small-world character exhibited by networks under shortest path routing, and that it significantly reduces the average travel time on congested networks with only a negligible increase in the average travel time at low loads. Finally, we study the correlation between the weights of the links in the case of optimal routing and the betweennesses of the nodes connected by them.Keywords: complex networks, scaling laws, transport * dbogdan@mail.uh.edu † marshj@ainfosec.com ‡ bassler@uh.edu 1 One of the most important problems in the study of complex networks is how to best route transport on the networks. This problem is important because transport is the main function of many natural and human-made networks. Often, the transport routes used on networks are the so-called shortest-path routes, which are the routes with the minimum number of hops between any two nodes. However, this approach, which is currently used to route transport of information packets on the Internet, typically leads to congestion and eventually jamming of highly connected nodes of the networks called hubs. For this reason and in light of recent research, interest has developed in finding the routing rules that allow a given network to bear the maximum possible traffic. Specifically, the problem can be stated as follows. Given a complex network and a set of processing power and traffic demand constraints for its nodes, find the set of routing rules which allow the network to bear the highest possible amount of traffic without jamming. This problem is known to be NP -hard, meaning that the time required for the computation of an exact solution increases with the number of nodes faster than any polynomial. In this paper we argue that a heuristic transport routing optimization algorithm recently published by us achieves near-optimal transport routing in polynomial time and show this to be true for three important types of complex networks. Of course, any optimized routing when compared to shortest-path routing occurs at the expense of increasing the average number of hops between the nodes. We show that with our algorithm the average number of hops after optimization increases with the number of nodes no faster than logarithmically and that optimization significantly decreases the average travel time on congested networks.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transport optimization on complex networks

Danila

Marsh

et al. 2007

Chaos: An Interdisciplinary Journal of Nonlinear Science

101

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“…In the case of the Internet, link weights are typically assigned manually by operators according to simple rules based on experience [1]. Recently, a series of heuristic algorithms have also been proposed for network traffic optimization [1,2,3,4,5]. These rules and algorithms are aimed at avoiding or reducing link overload by a judicious link weight assignment.…”

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confidence: 99%

Optimal transport on complex networks

Danila

Marsh³

et al. 2006

Phys. Rev. E

222

187

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We present a novel heuristic algorithm for routing optimization on complex networks. Previously proposed routing optimization algorithms aim at avoiding or reducing link overload. Our algorithm balances traffic on a network by minimizing the maximum node betweenness with as little path lengthening as possible, thus being useful in cases when networks are jamming due to queuing overload. By using the resulting routing table, a network can sustain significantly higher traffic without jamming than in the case of traditional shortest path routing.

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“…In particular, this investigation addresses an important and difficult combinatorial optimization problem in the design and management of telecommunication systems known as the path assignment problem. The path assignment problem is described by Allen et al [1] as follows.…”

Section: Introductionmentioning

confidence: 99%

“…Allen et al [1] present a fast heuristic that produces a sequence of demand re-routings that can be used to modify a poor path assignment to a near-optimal one where the objective is to minimize the cost of the path assignment as measured by hop count. Józsa and Magyar [11] propose heuristics for the reroute sequence planning (RSP) problem for multi-protocol label switching (MPLS) networks.…”

Section: Introductionmentioning

confidence: 99%

Incremental demand rerouting: optimization models and algorithms

Olinick

Rahman²

2010

Telecommun Syst

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This investigation addresses an important and difficult combinatorial optimization problem in the design and management of telecommunication systems known as the path assignment problem. The path assignment problem is specified by a set of demands on a network with given link capacities. Each demand must be assigned to exactly one routing path in such a way that the total amount of traffic routed over any link does not exceed that link's capacity. Given a network and a path assignment, the problem of interest is to maximize the available bandwidth (throughput) for a new demand. Network managers are concerned with the quality of service provided by their networks, and so they are reluctant to make major changes to an operating network that may inadvertently result in service disruptions for numerous clients simultaneously. Therefore, the objective of this investigation is to develop and test optimization models and algorithms that produce a series of throughputimproving modifications to the original path assignment. This allows network managers to implement the improved routing in stages with minimal changes to the overall routing plan between any two consecutive stages. Although the procedure may only reroute a few demands at each stage, the routing after the last stage should be as close as possible to an optimal routing. That is, it must maximize the throughput for the new demand. We present integer programming models and associated solution algorithms to maximize the throughput with a sequence of incremental path modifications. The algorithms were implemented with the AMPL modeling language and the CPLEX ILP solver, and tested on a family of five different data sets based on a European network widely studied in the literature. Empirical results show that the incremental approach finds near-optimal results within reasonable limits on CPU time.

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An Incremental Procedure for Improving Path Assignment in a Telecommunications Network

Cited by 11 publications

References 19 publications

Transport optimization on complex networks

Transport optimization on complex networks

Optimal transport on complex networks

Incremental demand rerouting: optimization models and algorithms

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