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The Ant Colony Optimization (ACO) metaheuristic is a versatile algorithmic optimization approach based on the observation of the behaviour of ants. As a result of numerous analyses, ACO has been applied to solving various combinatorial problems. The ant colony metaheuristic proves itself to be efficient in solving NP-hard problems, often generating the best solution in the shortest amount of time. However, not enough attention has been paid to ACO as a means of solving problems that have optimal solutions which can be found using other methods. The shortest path problem is undoubtedly one of the aspects of great significance to navigation and telecommunications. It is used, amongst others, for determining the shortest route between two geographical locations, for routing in packet networks, and to balance and optimize network utilization. Thus, this article introduces ShortestPathACO, an Ant Colony Optimization based algorithm designed to find the shortest path in a graph. The algorithm consists of several subproblems that are presented successively. Each subproblem is discussed from many points of view to enable researchers to find the most suitable solutions to the problems they investigate.

SUMMARYThis paper presents an approximate calculation methodology of the occupancy distribution and the blocking probability in a virtual circuit switching node with multi-rate unicast and multicast traffic streams. Particular traffic streams are generated by an infinite as well as by a finite population of traffic sources. The model enables calculations of any structure of the groups forming the outgoing directions of the node. Additionally, bandwidth reservation algorithms are also proposed in order to improve traffic characteristics of different traffic classes. The results of the analytical calculations have been compared with the simulation results of a switching node carrying multicast and unicast traffic streams.