Optimal design of signaling networks for Internet telephony

Srinivasan, Aravind; Ramakrishnan, K. G.; Kumaran, K.; Aravamudan, M.; Naqvi, Syed Aon Ali

doi:10.1109/infcom.2000.832245

Cited by 9 publications

(7 citation statements)

References 12 publications

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“…There were several sequential algorithms for generating random regular graphs [24], [25], [26]. Random graphs constructed by centralized algorithms were also used for communication networks [27], [28].…”

Section: Related Workmentioning

confidence: 99%

Distributed construction of random expander networks

Law

Siu

IEEE INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37

126

193

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Section: Related Workmentioning

confidence: 99%

Distributed construction of random expander networks

Law

Siu

IEEE INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37

126

193

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“…It is a powerful metaheuristic to address hard combinatorial optimization problems, and has been succesfully implemented in particular to several telecommunications problems, such as Internet Telephony (Srinivasan et al, 2000), Cellular Systems (Amaldi et al, 2003a;Amaldi et al, 2003b), Cooperative Systems (Romero, 2012), Connectivity (Canuto et al, 2001) and Wide Area Network design (Robledo Amoza, 2005). Here we will sketch the GRASP metaheuristic based on the work from Mauricio Resende and Celso Ribeiro, which is useful as a template to solve a wide family of combinatorial problems (Resende and Ribeiro, 2003; Resende and Ribeiro, 2014).…”

Section: Graspmentioning

confidence: 99%

Graph Fragmentation Problem

Piccini

Robledo

Romero

2016

Proceedings of 5th the International Conference on Operations Research and Enterprise Systems

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A combinatorial optimization problem called Graph Fragmentation Problem (GFP) is introduced. The decision variable is a set of protected nodes, which are deleted from the graph. An attacker picks a non-protected node uniformly at random from the resulting subgraph, and it completely affects the corresponding connected component. The goal is to minimize the expected number of affected nodes S. The GFP finds applications in fire fighting, epidemiology and robust network design among others. A Greedy notion for the GFP is presented. Then, we develop a GRASP heuristic enriched with a Path-Relinking post-optimization phase. Both heuristics are compared on the lights of graphs inspired by a real-world application.

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“…Another interesting application of GRASP is due to Srinivasan et al [137], who in 2000 described an approach for efficient design of a signaling network for a network of software switches supporting Internet telephony. Optimal load balancing for given demand forecast is formulated as a quadratic assignment problem, which is solved with a GRASP.…”

Section: Grasp In Telecommunication Systemsmentioning

confidence: 99%

“…(a) manufacturing [9,26,27,33,83,101]; (b) transportation [21,25,48,136]; (c) telecommunications [13,15,40,81,93,110,114,137]; (d) graph and map drawing [58,59,88,94,118]; (e) power systems [30,31,46]; (f) computational biology [54,70,77]; (g) VLSI [18,19], among other areas of application.…”

Section: Introductionmentioning

confidence: 99%

GRASP: basic components and enhancements

Festa

Resende

2010

Telecommun Syst

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GRASP (Greedy Randomized Adaptive Search Procedures) is a multistart metaheuristic for producing good-quality solutions of combinatorial optimization problems. Each GRASP iteration is usually made up of a construction phase, where a feasible solution is constructed, and a local search phase which starts at the constructed solution and applies iterative improvement until a locally optimal solution is found. While, in general, the construction phase of GRASP is a randomized greedy algorithm, other types of construction procedures have been proposed. Repeated applications of a construction procedure yields diverse starting solutions for the local search. This paper gives an overview of GRASP describing its basic components and enhancements to the basic procedure, including reactive GRASP and intensification strategies

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Optimal design of signaling networks for Internet telephony

Cited by 9 publications

References 12 publications

Distributed construction of random expander networks

Distributed construction of random expander networks

Graph Fragmentation Problem

GRASP: basic components and enhancements

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