Swarm intelligence for routing in communication networks

Kassabalidis, I.; El-Sharkawi, M.A.; Marks, Robert J.; Arabshahi, P.; Gray, Andrew

doi:10.1109/glocom.2001.966355

Cited by 117 publications

(47 citation statements)

References 12 publications

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“…The sixth is parallelism: swarm intelligence systems inherently use parallel computation for problem solving [19].…”

Section: The 'Blessing' Of Emergencementioning

confidence: 99%

“…Examples of swarm intelligence systems relevant to trusted autonomy include swarm robotics [9][10][11][12], control of groups of unmanned aerial vehicles [13][14][15][16], control of autonomous land and underwater vehicles [17,18], network switching [19], economic load dispatch [20], the control of switching networks [21], and the control of chaotic non-linear networks [22].…”

Section: Emergence In Swarm Intelligencementioning

confidence: 99%

“…The fifth is autonomy: swarm intelligence systems operate without external control or supervision, providing the capacity to control systems that are too complex or a require a response beyond the capacity of human involvement [17][18][19].…”

Section: The 'Blessing' Of Emergencementioning

confidence: 99%

See 2 more Smart Citations

The Blessing and Curse of Emergence in Swarm Intelligence Systems

Harvey

2018

Foundations of Trusted Autonomy

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“…The sixth is parallelism: swarm intelligence systems inherently use parallel computation for problem solving [19].…”

Section: The 'Blessing' Of Emergencementioning

confidence: 99%

Section: Emergence In Swarm Intelligencementioning

confidence: 99%

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The Blessing and Curse of Emergence in Swarm Intelligence Systems

Harvey

2018

Foundations of Trusted Autonomy

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“…Inspired from the behaviors of natural ant system, a new class of ant-based algorithms for network routing is currently being developed [15]. These algorithms use artificial ants concurrently and independently, and communicate in an indirect way to build the routing solution.…”

Section: Ant-based Network Routingmentioning

confidence: 99%

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

Ngo

Jiang

et al. 2006

J Supercomput

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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.

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“…Various Ant Colony routing protocols has been defined in the next section [1][2][3][4][5]. Ant colony provides a number of advantages [6] due to the use of mobile agents and stigmergy (a form of indirect communication used by ants in nature to coordinate their problem-solving activities). It provides scalability, i.e.…”

Section: Introductionmentioning

confidence: 99%