Title

A Load-Balanced Multicast Routing Algorithm Using Diversity Rate in CWMNs

Abstract

Cognitive wireless mesh networks (CWMNs) were developed to improve the utilization ratio of licensed spectrum. Since the spectrum opportunities for users vary over time and location, enhancing the spectrum effectiveness is a goal and also a challenge for CWMNs. Multimedia applications have recently generated much interest in CWMNs supporting quality-of-service (QoS) communications. Multicast routing and spectrum allocation is an important challenge in CWMNs. In this paper, we study to design an effective multicast routing algorithm based on diversity rate with respect to load balancing and the number of transmissions for CWMNs. In this paper, a load balancing wireless links weight computing function and computing algorithm based on diversity rate (DRLB) are proposed, and a load balancing channel and rate allocating algorithm based on diversity rate (DR2CS) is proposed. On this basis, a load balancing joint multicast routing, channel and rate allocation algorithm based on diversity rate with QoS constraints for CWMNs (LMR2D) is proposed. Balancing the load of node and channel, and minimizing the number of transmissions of multicast tree are the objectives of LMR2D. Firstly, LMR2D computes the weight of wireless links using DRLB and Dijkstra for constructing the load balancing multicast tree step by step. Secondly, LMR2D uses DR2CS to allocate channel and rate of channel to links which is based on the wireless broadcast advantage. Simulation results show that LMR2D can achieve the expected goal. It can not only balance the load of node and channel, but also need lower number of transmissions for multicast tree.

Department(s)

Computer Science

Document Type

Article

DOI

https://doi.org/10.1007/s11277-017-4393-y

Keywords

Cognitive wireless mesh networks, Diversity rate, Load balanced, Multicast routing, Spectrum allocation

Publication Date

10-1-2017

Journal Title

Wireless Personal Communications

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