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Using a History-Based Approach to Predict Topology Control Information in Mobile Ad Hoc Networks

机译:使用基于历史的方法预测移动自组织网络中的拓扑控制信息

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Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors' previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.
机译:几种社交计算参与策略(例如,人群感知和众包)使用移动即席或机会网络来支持用户活动。这些通信链路的不可靠性和动态性使路由协议成为在物理环境中实现有效和可靠的数据通信的关键组件。通常,这些路由功能是以大量的拓扑控制信息(TCI)泛洪网络为代价的,这可能会使通信链路超载,并显着增加参与设备的能耗。在先前的工作中,作者表明,在这些工作场景中预测网络拓扑有助于减少通过网络传递的控制数据包的数量。这样可以节省能源并增加可用带宽。本文提出了一项研究,通过确定预测这些网络中路由协议生成的TCI的影响,扩展了作者以前的工作。遵循基于历史的方法来完成预测过程,该方法使用节点过去的行为的信息。本文还确定了该策略的可预测性限制,假设如果过去至少出现一次,则可以正确预测TCI消息。结果表明,基于历史的预测方法的上限很高,并且现实的预测机制可以实现很高的准确率。使用移动自组织网络或机会网络的移动协作应用程序和路由协议可以利用这种预测方法来减少网络流量,从而减少其设备的能耗。

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