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On the credit evolution of credit-based incentive protocols in wireless mesh networks

机译:无线网状网络中基于信用的激励协议的信用演化

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In designing wireless mesh networks (WMNs), incentive mechanisms are often needed so to encourage nodes to relay or forward packets for other nodes. However, there is a tack of fundamental understanding on the interactions between the incentive mechanisms and the underlying protocols (e.g.. shortest-path routing, ETX routing or back-pressure scheduling), and whether integration of these protocols will lead to a robust network, i.e., networks can sustain a given traffic workload. The objective of this paper is to present a general mathematical framework via stochastic difference equations to model the interaction of incentive mechanisms and various underlying protocols. We first present a credit evolution model to quantify the expected credit variation of each node in WMN, then use the norm of the expected credits variation to quantify the credit disparity. We also propose the use of differentiated pricing and show how it can achieve credit equality among nodes, resulting in a more robust network under different traffic loading. Our analytical framework can help researchers to model other incentive/routing protocols so to analyze the robustness of the underlying networks.
机译:在设计无线网状网络(WMN)时,通常需要激励机制,以鼓励节点为其他节点中继或转发数据包。但是,对于激励机制与底层协议(例如,最短路径路由,ETX路由或背压调度)之间的相互作用,以及这些协议的集成是否会带来健壮的网络,有基本的了解也就是说,网络可以承受给定的流量工作量。本文的目的是通过随机差分方程提供一个通用的数学框架,以对激励机制和各种基础协议之间的相互作用进行建模。我们首先提出一个信用演化模型,以量化WMN中每个节点的预期信用变化,然后使用预期信用变化的范数来量化信用差异。我们还建议使用差异化定价,并展示其如何在节点之间实现信用平等,从而在不同的流量负载下实现更强大的网络。我们的分析框架可以帮助研究人员对其他激励/路由协议建模,从而分析基础网络的健壮性。

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