COMPLEX OPTIMIZATION METHOD OF ROUTING INFORMATION FLOWS IN SELF-ORGANIZED NETWORKS

Abstract

Modified routing algorithms are presented based on basic meta-heuristic algorithms: ant colony optimization, genetic and simulated annealing to determine the best route for information flows in self-organized networks. An ant colony optimization is based on the use of the probability parameter for the transition between the nodes located between the source node and the receiving node. To solve the problem of optimization of routing in a simulated annealing, its modification is proposed by adding or removing a transit node based on the coverage of the reaching range of neighboring nodes. As a target function for estimating a route, the QoS parameter is considered – the time of data delivery from the source node to the receiving node. For the first time, a routing algorithm is proposed based on a combination of proposed modified algorithms, where, from a set of best routes, formed by a modified annealing simulation algorithm, the choice of the best route according to the criterion of the time of data transmission is made by using a modified ant algorithm. For simulation an algorithm for generating traffic of a self-organized network is presented. The considered algorithms of routing allow to reduce the time of data transmission between the source node and the receiving node, which increases the efficiency of routing information flows in selforganized networks. It is shown that an important condition for efficient routing in selforganized networks is the reduction of the number of transit nodes between the source node and the node-coordinator.

Authors and Affiliations

Yulia Klymash, Olha Shpur, Mykola Kaidan

Keywords

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  • EP ID EP456378
  • DOI -
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How To Cite

Yulia Klymash, Olha Shpur, Mykola Kaidan (2017). COMPLEX OPTIMIZATION METHOD OF ROUTING INFORMATION FLOWS IN SELF-ORGANIZED NETWORKS. Вісник Національного університету "Львівська політехніка", серія "Радіоелектроніка та телекомунікації", 885(2017), 76-87. https://europub.co.uk/articles/-A-456378