Joint Channel Assignment and Multicast Routing in MultiChannel MultiRadio Wireless Mesh Networks Based on QLearning Recently, importance of wireless networks increased significantly. Wireless Mesh Networks (WMNs) are receiving growing attention and offer many advantages in terms of connectivity and reliability. Multicast communication is an important technology for wireless networks in which the same content of data should be delivered to a group of receiver nodes simultaneously. So multicast routing provides efficient data distribution among a group of nodes rather than other traditional unicast routing strategies. Here we focus on the Channel Allocation (CA) scheme which efficiently utilizes multiple wireless interfaces to achieve better throughput and improving the radio interference. This kind of problem has been proved to be NPhard. Hence, solving the multicast channel assignment problem in MCMR WMNs will be more complicated than that of traditional networks. The research in this paper is aimed at improving the network performance for efficient joint channel assignment and multicast routing problem in MCMR WMNs by using the Qlearning scheme. We also implement our proposed channel assignment algorithm, and evaluate and compare its performance with LAMR. Simulations and experimental results demonstrate that QLMR outperforms the previous works in terms of achieved average throughput, average endtoend delay, average packet delivery ratio and so on. We will evaluate the performance of the proposed scheme.

On a Coexisting Scheme for Multiple Flows in Multiradio Multichannel Wireless Mesh Networks Multiradio multichannel (MRMC) wireless mesh networks (WMNs) hold the promise to become the nextgeneration networks to provide the service of ubiquitous computing, access to the Internet, and support for a large number of data flows. Many applications in WMNs can be modeled as a multiflow coexistence problem. Assembling links distributed in orthogonal channels to support multiple flows is essentially a combinatorial optimization problem, which concerns channel assignment, path finding, and link scheduling. To make full use of network resources, links in different channel layers should be concatenated to compose data transfer paths for multiple flows with awareness of nodesxe2x80x99 free interfaces and available channels. Based on the analysis of traffic behaviors, this paper designs a coexisting algorithm to maximize the number of flows. Simulations are conducted in combinatorial cases with various traffic requests of multiple pairs, and the results show the efficacy of the proposed algorithm over a random network topology. This scheme can be used to develop routing and scheduling solutions for multiflow network tasks through prior computing.