Incremental Versus Optimized Network Design

2012

Refining a network topology is an important network management technique. Nevertheless, determining the appropriate steps to transform a network from one topology to another, in a way that minimizes service disruptions, has received little attention. This is a critical problem since service disruptions can be particularly harmful and costly for networks hosting mission-critical services. In this paper, we introduce the incremental network transformation (INT) problem and explore this problem in the context of automated planning. We define two metrics to measure the quality of generated transformation plans, one of which is amenable to classical propositional planning. We find that while state-of-the-art domainindependent planning techniques are effective at finding highquality solutions for small problem instances, they cannot scale to solve realistically sized INT instances. To address the shortcomings of existing approaches, we developed a number of domain-dependent planners that use novel domain-specific heuristics. We empirically evaluated our planners on a wide range of synthetic network topologies. Our results illustrate that our automated planning inspired techniques are effective on realistically sized INT problems. We envision that our approach could eventually provide a compelling addition to the arsenal of techniques employed by network practitioners to support network refinement with minimal disruption to running services.

European Journal of Operational Research, 2014

We introduce a class of incremental network design problems focused on investigating the optimal choice and timing of network expansions. We concentrate on an incremental network design problem with shortest paths. We investigate structural properties of optimal solutions, we show that the simplest variant is NP-hard, we analyze the worst-case performance of natural greedy heuristics, and we derive a 4-approximation algorithm.

2008

Following the traffic of a backbone increase near to the capacity of the network, the evolution of backbone topology takes place. In this paper, three main types of evolution methods: link upgrading only method, node upgrading method, and the combination of previous two are explored. To shunt the saturated traffic efficiently, we propose several node upgrading algorithms, Traffic Adaptive Topology gEnerators (TATEs), based on the condition of current traffic distribution and node burden. TATEs choose the congested link as the main shunting object. The difference among TATEs lies that they have diverse strategies to choose a node in the congested link as the second shunting aim. Simulation shows that: the type of TATEs that picks the burdened node in the saturated link as the second shunting object has the most effective shunting result. Compare with most of current topology generators such as [BRITE] in which consider little about traffic increase distribution, TATEs are more efficient to satisfy traffic increase.

Sixth International Conference on Networking (ICN'07), 2007

Following the traffic of a backbone increase near to the capacity of the network, the evolution of backbone topology takes place. In this paper, three main types of evolution methods: link upgrading only method, node upgrading method, and the combination of previous two are explored. To shunt the saturated traffic efficiently, we propose several node upgrading algorithms, Traffic Adaptive Topology gEnerators (TATEs), based on the condition of current traffic distribution and node burden. TATEs choose the congested link as the main shunting object. The difference among TATEs lies that they have diverse strategies to choose a node in the congested link as the second shunting aim. Simulation shows that: the type of TATEs that picks the burdened node in the saturated link as the second shunting object has the most effective shunting result. Compare with most of current topology generators such as [BRITE] in [1] which consider little about traffic increase distribution, TATEs are more efficient to satisfy traffic increase.

Annals of Operations Research, 1991

We describe an implementation of the tabu search metaheuristic that effectively finds a low-cost topology for a communications network to provide a cenlialized new service. Our results are compared to those of a greedy algorithm which ^jplies corresponding decision rules, but widioul the guidance of the tabu search framework. These problems are difficult computationally, representing integer programs thai can involve as many as 10,000 integer variables and 2000 constraints in practical applications. The tabu search results approach succeeded in obtaining significant improvements over the greedy approach, yielding optimal solutions to problems small enough to allow independent verification of optimality status and, more generally, yielding both absolute and percentage cost improvements that did not deteriorate with increasing problem size.

arXiv (Cornell University), 2023

The need for reliable and low-cost infrastructure is crucial in today's world. However, achieving both at the same time is often challenging. Traditionally, infrastructure networks are designed with a radial topology lacking redundancy, which makes them vulnerable to disruptions. As a result, network topologies have evolved towards a ring topology with only one redundant edge and, from there, to more complex mesh networks. However, we prove that large rings are unreliable. Our research shows that a sparse mesh network with a small number of redundant edges that follow some design rules can significantly improve reliability while remaining cost-effective. Moreover, we have identified key areas where adding redundant edges can impact network reliability the most by using the SAIDI index, which measures the expected number of consumers disconnected from the source node. These findings offer network planners a valuable tool for quickly identifying and addressing reliability issues without the need for complex simulations. Properly planned sparse mesh networks can thus provide a reliable and a cost-effective solution to modern infrastructure challenges.

IEEE Transactions on Evolutionary Computation, 2001

This paper deals with the application of evolutionary computation to telecommunication network design. Design of a two-layer network is considered, where the upper-layer (UL) network uses resources of the lower-layer (LL) network. UL links determine demands for the LL and are implemented using LL paths (admissible paths). Within a fixed LL network topology, given the demands and admissible paths, we aim to find the LL link capacities for implementing the UL links, minimizing the cost of the LL. Robust design issues are also taken into consideration, allowing for failure of a certain part of the LL and postulating that after some reallocation in the LL, demands are still realized to an assumed extent. An algorithm based on an evolutionary technique is introduced, with problem-specific genetic operators to improve computing efficiency. A theoretical study of properties of the operators is made and several experiments are performed to tune the parameters of the algorithm. Finally, its performance is compared with other design techniques, including integer programming.

Engineering Applications of Artificial Intelligence, 2002

The topology design of switched enterprise networks (SENs) is a hard constrained combinatorial optimization problem. The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. Several conflicting objectives such as monetary cost, network delay, and maximum number of hops have to be optimized to achieve a desirable solution. Further, many of the desirable features of a network topology can best be expressed in linguistic terms, which is the basis of fuzzy logic. In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. The overall cost function has been developed using fuzzy logic. Several variants of the algorithm are proposed and compared together via simulation and experimental results are provided.

2005

Adequately supporting applications with Quality-of-service (QoS) requirements is a challenging task, particularly in the Internet. In great part, this is due to the fact that the provisioning of end-toend QoS to traffic that traverses multiple autonomous systems (ASes) requires a level of cooperation between ASes that is difficult to achieve in the current architecture. Recently, service overlay networks have been considered as an approach to QoS deployment that avoids these difficulties. In this study, the problem of the topological synthesis of a service overlay network is addressed. Endsystems and nodes of the overlay network are connected through ISPs that supports bandwidth reservations. The topology design problem is expressed as an optimization problem. Even though the design problem is related to the (in general NP-hard) quadratic assignment problem, it is shown that relatively simple heuristic algorithms can deliver results that are sometimes close to the optimal solution with little overhead.

2004

The topological design of distributed computer networks essentially consists in finding a topology that minimizes the communication costs by taking into account a certain number of constraints such as delay and reliability. Under several aspects, it appears a very hard optimization problem. Therefore no exact solving approach can guarantee an optimal solution in realistic computation times, that militates in favor of heuristic methods capable of providing good feasible solutions. This paper uses a genetic algorithm for generating low cost network topologies which satisfy quality of service and reliability constraints. Computational results convince us this algorithm provides solutions of as much better quality as the size of the network is great.