Multi-Flow Optimization Model for Design of a Shared Backup Path Protected Network

Abstract

Designing optimal shared backup path protected networks is a difficult and time-consuming task, and considerable research has been done to develop near optimal heuristics and algorithms that will solve the SBPP model without extensive computing power, but by definition, such methods are suboptimal. This paper introduces a slight modification to the SBPP problem that allows it to be optimally solved using conventional ILP techniques. By allowing working and backup paths to follow multiple routes, the new SBPP model eliminates the numerous 1/0 variables in the conventional model. The fundamental characteristics of SBPP remain intact, with the problem altering only slightly but it allows ILP solvers to find an optimal solution in a time measured in seconds to minutes compared to the days or longer needed for conventional models.

Algebraic connectivity metric for spare capacity allocation problem in survivable networks

“…In the case of a given network topology with bi-directional links, the average node degree d is defined as the quotient of double the number of links and the number of nodes. The case studies presented in [3][4][5][6][7][8] have concentrated on showing how the working and spare capacity requirements of networks with various topologies vary with the average node degree. Despite wide adoption of the average node degree as the numerical measure of a network's potential immunity to failures, we argue that it is only a coarse indicator of how sparse or dense a given topology is, and so it carries insufficient information on network topological structure.…”

“…Most studies [3][4][5][6][7][8] use the average node degree for quantifying the relationship between spare capacity allocation and network connectivity. In the case of a given network topology with bi-directional links, the average node degree d is defined as the quotient of double the number of links and the number of nodes.…”

A new topological index for capacity allocation problem in survivable networks

“…Most studies [3][4][5][6][7] use the average nodal degree index for quantifying the relationship between capacity allocation and network connectivity. For a given network topology with bidirectional links, the average nodal degree d is defined as the ratio of twice the number of links to the number of nodes.…”

“…For a given network topology with bidirectional links, the average nodal degree d is defined as the ratio of twice the number of links to the number of nodes. The simulation studies presented in [3][4][5][6][7] have concentrated on showing how the working and spare capacity requirements of networks with various topologies vary with the average nodal degree index. Despite of the wide adoption of the average nodal degree index in these studies, we argue that this index is only a coarse indicator of how sparse or dense a given topology is.…”

Utility of algebraic connectivity metric in topology design of survivable networks

“…Most previous studies [1][2][3][4][5][6] generally use the average nodal degree to reflect the effect of the network connectivity in determining the spare capacity allocation. The average nodal degree d is obtained by multiplying the number of links by two and dividing it by the number of nodes in a given network topology.…”