An Algorithm for Optimal Route Selection in SNA Networks

Gavish, Bezalel; Hantler, S. L.

doi:10.1109/tcom.1983.1095752

Cited by 110 publications

(39 citation statements)

References 19 publications

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“…Complexity of AFA problem is a result of huge solution space. Accordingly to [3] we transform the AFA1 problem into an equivalent formulation called AFA2, which is better suited for a Lagrangean relaxation procedure. Since the objective function (1) is not decreasing with f a , we can replace equality (2) with an inequality leading to the following problem …”

Section: T Total Arrive Rate Of Messages In the Networkmentioning

confidence: 99%

“…Therefore, a suitable constraint set is chosen to be relaxed. In our case we use the approach proposed in [3] and relax the constraint (9) using a vector of positive Lagrangean multipliers λ a , a∈A. Consequently, the following Lagrangean relaxation of problem AFA2, called LR_AFA is formulated as…”

Section: Lagrangean Relaxationmentioning

confidence: 99%

“…It means that the subproblem 2 consists of a number of shortest path problems. Comparing to the unicast version of considered problem addressed in [3], in the anycast flow problem to find a shortest path we must take into account all content servers. Another modification is the coupling between upstream and downstream connections given by (5).…”

Section: Lagrangean Relaxationmentioning

confidence: 99%

“…In this paper we propose a Lagrangean relaxation method combined with subgradient optimization to iteratively solve the problem by a heuristic algorithm ANBFD [9] using as initial solutions results given solving dual problems. Lagrangean relaxation with subgradient optimization has been used successfully for solving various communication network routing problems [3], [7]. Our starting point is the algorithm proposed in [3].…”

Section: Introductionmentioning

confidence: 99%

“…Lagrangean relaxation with subgradient optimization has been used successfully for solving various communication network routing problems [3], [7]. Our starting point is the algorithm proposed in [3]. However, we modified this approach according to anycast flow constraints.…”

Section: Introductionmentioning

confidence: 99%

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Lagrangean Heuristic for Anycast Flow Assignment in Connection-Oriented Networks

Walkowiak

2006

Computational Science – ICCS 2006

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Abstract. In this work we address the problem of anycast flow assignment. Anycast is a one-to-one-of-many delivery technique that allows a client to choose a content server of a set of replicated servers. We formulate an optimization problem of anycast flows assignment in a connection-oriented network, which is 0/1 and NP-complete. Thus, we propose a new effective heuristic algorithm based on Lagrangean relaxation technique. To our best survey, this is the first study that applies the Lagrangean relaxation to anycast flow problem. We evaluate the performance of the proposed scheme by making a comparison with its counterpart using a sample network topology and different scenarios of traffic demand patterns and replica location. Obtained results show advantage of the Lagrangean heuristic over a previously proposed algorithm.

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Section: T Total Arrive Rate Of Messages In the Networkmentioning

confidence: 99%

Section: Lagrangean Relaxationmentioning

confidence: 99%

Section: Lagrangean Relaxationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Lagrangean Heuristic for Anycast Flow Assignment in Connection-Oriented Networks

Walkowiak

2006

Computational Science – ICCS 2006

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Routing in packet-switched communication networks with different criticality classes of communicating node pairs

Amiri

Pirkul

1997

Naval Research Logistics

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A survey of applications of mathematical programming to circuit‐switched network planning problems

Craveirinha

Clímaco

1992

Trans Emerging Tel Tech

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In the planning of circuit‐switched networks the decisions regarding the capacity of transmission and switching equipments, the location of exchanges and the routing principles are of primary importance. Traditionally planning methods were based on heuristic type algorithms using sometimes simple mathematical programming algorithms for particular sub‐problems. However in the 70's and 80's, new approaches based on mathematical programming algorithms (namely non‐linear programming, integer programming and dynamic programming algorithms) have been put forward for solving some key telecommunication network planning problems. The main objective of the paper is to identify the main characteristics of problems where mathematical programming has been applied (in the context of circuit‐switched network planning) and referring to relevant works in these areas. A system of taxonomic classification of circuit‐switched network planning problems is proposed and applied to an extensive list of relevant publications complemented with a list of correlated papers and other publications. The core of the overview of contributions, presented in the paper, will be limited to models of operational planning of circuit‐switched networks. Finally the authors, based on their own experience in specific problems, will try to put forward some general conclusions of a broad methodological nature.

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An Algorithm for Optimal Route Selection in SNA Networks

Cited by 110 publications

References 19 publications

Lagrangean Heuristic for Anycast Flow Assignment in Connection-Oriented Networks

Lagrangean Heuristic for Anycast Flow Assignment in Connection-Oriented Networks

Routing in packet-switched communication networks with different criticality classes of communicating node pairs

A survey of applications of mathematical programming to circuit‐switched network planning problems

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