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An illustration of broadcasting in the conflict-aware multi-channel model. Assume node A is the source and sends the message through channel 1 in the first round. Hence, at the beginning of the second round, A, B, and C have the message. Assume B sends the message through channel 1, and A and C through channel 2. At the end of the round, node D receives the message through both channels, node E receives the message through channel 1 (via B); there is a conflict on channel 2 at node F , which does not receive the message in this round.
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The broadcasting problem asks for the fastest way of transmitting a message to all nodes of a communication network. We consider the problem in conflict-aware multi-channel networks. These networks can be modeled as undirected graphs in which each edge is labeled with a set of available channels to transmit data between its endpoints. Each node can...
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Citations
... So and Vaidya [9] presented the dynamic channel switching scheme with multi-channel to avoid conflicts, especially the hidden terminal problem. Claude et al. [10] proposed a channel assignment scheme for fast broadcasting in multi-channel wireless networks. However, utilizing multiple channels with a single radio interface results in substantial control overhead and necessitates time synchronization for effective communication. ...
This paper proposes a theoretical model-driven channel assignment scheme designed to enhance network performance in multi-radio multi-channel wireless mesh networks. Unlike previous conflict graph-based channel assignments that addressed co-channel interference and hidden terminal problems while overlooking an exposed terminal problem, our proposed approach integrates these problems comprehensively to mitigate network performance degradation. Given a communication graph, we establish a conflict graph based on hop distance for practical implementation. The weighted conflict graph is constructed by analyzing packet collision conditions under the IEEE 802.11 standard with the CSMA/CA protocol, considering not only the transmission range and interference range but also the carrier sensing range simultaneously. Given a weighted conflict graph and available channel lists on each router, we devise a
Weighted Soft List Coloring
problem to address the channel assignment challenge. We prove the NP-hardness of this problem by establishing its dual problem, Max
list
-Cut. We present an approximation algorithm with worst-case performance at most twice the optimal solution while preserving network topology. We substantiate the performance of the proposed channel assignment algorithm through simulations in various topologies. The proposed algorithm, on average, demonstrates a network throughput increase of 162% and 174% compared to the greedy heuristic algorithm with 3 channels and 12 channels, respectively.
