Article ID Journal Published Year Pages File Type
445831 Ad Hoc Networks 2012 20 Pages PDF
Abstract

Use of multiple orthogonal channels can significantly improve network throughput of multi-hop wireless mesh networks (WMNs). In these WMNs where multiple channels are available, channel assignment is done either in a centralized manner, which unfortunately shows a poor scalability with respect to the increase of network size, or in a distributed manner, where at least one channel has to be dedicated for exchanging necessary control messages or time synchronization has to be utilized for managing the duration of data packet transmission, causing excessive system overhead and waste of bandwidth resource. In this paper, we first formulate multi-channel assignment as a NP-hard optimization problem. Then a distributed, heuristic temporal–spatial multi-channel assignment and routing scheme is proposed, assuming every wireless node in the network is equipped with a single-radio interface. Here the gateway node is set to use all the channels sequentially in a round-robin fashion. This temporal scheme ensures all the nodes that need to directly communicate with the gateway node shall have a fair access to it. For those non-gateway nodes, a spatial scheme where channels are assigned based on their neighbors’ channel usage is adopted to exploit parallel communications and avoid channel interference among nodes. Furthermore, since the routing factors, including channel usage of neighbor nodes, node hop count, node memory size, and node communication history, are all considered along with the channel assignment, network performance, measured by packet delivery latency, channel usage ratio, and memory usage ratio, tends to be considerably enhanced. The simulation results have confirmed that, compared with a couple of well-known multi-channel assignment schemes, such as LCM [21] and ROMA [15], the proposed scheme shows substantial improvement in network throughput with a very modest collision level. In addition, the proposed scheme is highly scalable as the algorithm complexity is only linearly dependent on the total number of channels that are available in the network and the number of neighbors that a network node directly connects to.

Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
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