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QoS multicast routing protocol oriented to cognitive network using competitive coevolutionary algorithm

Wang, X, Cheng, H and Huang, M (2014) QoS multicast routing protocol oriented to cognitive network using competitive coevolutionary algorithm. EXPERT SYSTEMS WITH APPLICATIONS, 41 (10). pp. 4513-4528. ISSN 0957-4174

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The human intervention in the network management and maintenance should be reduced to alleviate the ever-increasing spatial and temporal complexity. By mimicking the cognitive behaviors of human being, the cognitive network improves the scalability, self-adaptation, self-organization, and self-protection in the network. To implement the cognitive network, the cognitive behaviors for the network nodes need to be carefully designed. Quality of service (QoS) multicast is an important network problem. Therefore, it is appealing to develop an effective QoS multicast routing protocol oriented to cognitive network.

In this paper, we design the cognitive behaviors summarized in the cognitive science for the network nodes. Based on the cognitive behaviors, we propose a QoS multicast routing protocol oriented to cognitive network, named as CogMRT. It is a distributed protocol where each node only maintains local information. The routing search is in a hop by hop way. Inspired by the small-world phenomenon, the cognitive behaviors help to accumulate the experiential route information. Since the QoS multicast routing is a typical combinatorial optimization problem and it is proved to be NP-Complete, we have applied the competitive coevolutionary algorithm (CCA) for the multicast tree construction. The CCA adopts novel encoding method and genetic operations which leverage the characteristics of the problem. We implement and evaluate CogMRT and other two promising alternative protocols in NS2 platform. The results show that CogMRT has remarkable advantages over the counterpart traditional protocols by exploiting the cognitive favors.

Item Type: Article
Uncontrolled Keywords: 01 Mathematical Sciences, 08 Information And Computing Sciences
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
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Date Deposited: 14 Mar 2016 12:42
Last Modified: 17 May 2022 14:37
DOI or ID number: 10.1016/j.eswa.2014.01.020
URI: https://researchonline.ljmu.ac.uk/id/eprint/3188
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