Ant-based survivable routing in dynamic WDM networks with shared backup paths

Abstract

Abstract. In this paper, we consider the problem of survivable routing in dynamic WDM networks with single link failure model. Our work mainly concerns in how to dynamically determine a protection cycle (i.e., two link-disjoint paths between a node pair) to establish a dependable lightpath with backup paths sharing. This problem is identified as NP-complete, thus a heuristic for finding near optimal solution with reasonable computation time is usually preferred. Inspired from the principle of ant colony optimization, we propose in this paper an ant-based mobile agents algorithm for this problem with improved blocking performance. To enable the new ant-based algorithm, we propose to use on each network node both a routing table that contains a set of feasible protection cycles between source destination nodes and also a pheromone table for mobile agents. By keeping a suitable number of mobile agents in a network to continually and proactively update the routing tables based on the current network congestion state, the routing solution of a connection request can be obtained with a reasonable computation time. Extensive simulation results upon the ns-2 network simulator and two typical network topologies show that our new algorithm can achieve a significantly lower blocking probability than the promising algorithm for dynamic lightpath protection proposed in [11] with a comparable computation complexity.

Principles and applications of swarm intelligence for adaptive routing in telecommunications networks

“…The work described in [77] and other papers by the same authors addresses the problem of setting up a primary path between a source and a destination and one or more disjoint backup paths. The authors specifically consider the case of wavelength-division multiplexing (WDM) networks.…”

Performance Analysis of Nature Inspired Heuristics for Survivable Virtual Topology Mapping

“…Ant colony optimization is applied to the static [10] and dynamic [11], [12] RWA problem without the survivability constraint. The only study using ACO considering back-up paths on the physical layer is [13]. Particle swarm optimization is applied to the RWA problem in only [14], in which the survivability constraint is not considered.…”

Ant colony optimization for survivable virtual topology mapping in optical WDM networks

“…Ant colony optimization is applied to the static [10] and dynamic [11], [12] RWA problem without the survivability constraint. The only study using ACO considering back-up paths on the physical layer is [13]. Particle swarm optimization is applied to the RWA problem in only [14], in which the survivability constraint is not considered.…”