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A new quantum-inspired approach to reduce the blocking probability of demands in resource-constrained path computation scenarios

10.15199/59.2016.8-9.5

nr katalogowy: 100730
10.15199/59.2016.8-9.5

This article presents a new approach related with end-toend routing, which, owing to quantum-inspired mechanisms of prediction of availability of network resources, results in improved blocking probability of incoming requests to establish transmission paths. The proposed scheme has been analyzed for three network topologies and several scenarios of network load. Obtained results show a significant (even twofold) reduction of blocking probability in comparison to results characteristic to the reference solution. Key words: routing, blocking probability, optimization.1. INTRODUCTION Graph theory methods are commonly used to find the optimal/ sub-optimal solutions to routing problems in communication networks. In particular, any network can be represented by a graph, in which its nodes are represented by vertices of the graph, while communication links are modeled by the respective unidirectional / bidirectional edges of the graph. Path computation algorithms, e.g., Dijkstra’s approach [1], utilize such network structures to calculate the end-to-end transmission paths of the lowest cost according to the assumed metric (commonly the metric of distance). In particular, Dijkstra’s algorithm is very effective in finding the minimum-cost path between a pair of end nodes of a demand. However, as shown in [2], the task to find the optimal solution with respect to a single demand does not guarantee obtaining the global optimum solution for a set of demands. This is since separate calculation of the shortest paths sequentially for each demand does not take into account future demands, and, as a result, incoming demands may be rejected due to inefficient allocation of network resources with respect to demands being served. In order to decrease the blocking probability of demands, paths may thus be not optimal with respect to their individual characteristics. Therefore, prediction approach seems necessary in path computations [...]

Bibliografia

[1] Dijkstra Edsger. 1959. "A note on two problems in connexion with graphs". Nimerische Mathematik, Springer 1 (1): 269-271.
[2] Pióro Michał, Medhi Deepankar. 2004. Routing, flow, and capacity design in communication and computer networks, Morgan Kaufmann.
[3] Phillips A.C. 2003. Introduction to quantum mechanics. John Willey & Sons.
[4] Binney James, Skinner David. 2008. The physics of quantum mechanics. Cappella Archive.
[5] Cormen Thomas H., Charles E. Leiserson, Ronald L. Rivest, Stein Clifford. 2001. Introduction to algorithms, 2nd Edition. MIT Press and McGraw-Hill.
[6] Rak Jacek. 2010. "k-Penalty: a novel approach to find k-Disjoint paths with differentiated path costs", IEEE Communications Letters 14 (4): 354-356.
[7] http://www.pionier.net.pl/online/en/projects/69/, accessed on April 27, 2016.

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