As multi-hop wireless networks are attracting more attention, the need to evaluate their performance becomes essential. In order to evaluate the performance metrics of multi-hop wireless networks, including sending and receiving rates of a node as well as the collision probability, a model based on Stochastic Reward Nets (SRNs) is proposed. The proposed SRN models a typical node in such networks, considered as a general template to be applied to any wireless node. The SRN model of a single node is designed to take transmission effects of all neighboring nodes into account, while ignoring the ones whose transmission has no effect on the node under-study. Applying the proposed SRN to each node in a multi-hop wireless network, we can model any arbitrary topology and evaluate the mean queue size, collision probability, sending and receiving rates of the nodes. Common issues related to Medium Access Control (MAC) and physical layer of wireless networks, e.g. hidden and exposed node problems, collision, transmission, interference and carrier sense ranges, are considered in the proposed SRN model. The results obtained by the proposed model, in two different scenarios, are validated with the results obtained from the discrete-event simulation conducted in ns-2 simulator to show the applicability and accuracy of the proposed SRN model.

中文翻译：

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使用SRN的多跳无线网络建模和评估

随着多跳无线网络越来越受到关注，评估其性能的需求变得至关重要。为了评估多跳无线网络的性能指标，包括节点的发送和接收速率以及冲突概率，提出了一种基于随机奖励网络的模型。所提出的SRN对这种网络中的典型节点进行建模，被认为是要应用于任何无线节点的通用模板。设计单个节点的SRN模型时，要考虑到所有相邻节点的传输效果，而忽略那些传输对正在研究的节点没有影响的节点。将建议的SRN应用于多跳无线网络中的每个节点，我们可以对任意拓扑进行建模并评估平均队列大小，冲突概率，节点的发送和接收速率。在提议的SRN模型中考虑了与媒体访问控制（MAC）和无线网络的物理层相关的常见问题，例如隐藏和暴露的节点问题，冲突，传输，干扰和载波侦听范围。通过在ns-2模拟器中进行的离散事件模拟获得的结果，验证了在两种不同情况下由所提出的模型获得的结果，从而证明了所提出的SRN模型的适用性和准确性。