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Offloading Cellular Traffic Through Opportunistic Communications: Analysis and Optimization

机译:通过机会通信卸载蜂窝流量:分析和优化

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摘要

Offloading traffic through opportunistic communications has been recently proposed as a way to relieve the current overload of cellular networks. Opportunistic communication can occur when mobile device users are (temporarily) in each other's proximity, such that the devices can establish a local peer-to-peer connection (e.g., via WLAN or Bluetooth). Since opportunistic communication is based on the spontaneous mobility of the participants, it is inherently unreliable. This poses a serious challenge to the design of any cellular offloading solutions, that must meet the applications' requirements. In this paper, we address this challenge from an perspective, in contrast to the existing solutions. We first model the dissemination of content (injected through the cellular interface) in an opportunistic network with heterogeneous node mobility. Then, based on this model, we derive the optimal content injection strategy, which minimizes the load of the cellular network while meeting the applications' constraints. Finally, we propose an adaptive algorithm based on control theory that implements this optimal strategy without requiring any data on the mobility patterns or the mobile nodes' contact rates. The proposed approach is extensively evaluated with both a heterogeneous mobility model as well as real-world contact traces, showing that it substantially outperforms previous approaches proposed in the literature.
机译:最近已经提出通过机会通信卸载业务,以减轻当前蜂窝网络的过载。当移动设备用户(暂时)彼此接近时,机会通信会发生,使得设备可以建立本地对等连接(例如,经由WLAN或蓝牙)。由于机会主义沟通是基于参与者的自发性,因此它本质上是不可靠的。这对必须满足应用要求的任何蜂窝式卸载解决方案的设计提出了严峻的挑战。与现有解决方案相比,本文从一个角度解决了这一挑战。我们首先对具有异构节点移动性的机会网络中的内容(通过蜂窝接口注入)的分发进行建模。然后,基于此模型,我们得出了最佳的内容注入策略,该策略可以在满足应用程序约束的同时最大程度地降低蜂窝网络的负载。最后,我们提出了一种基于控制理论的自适应算法,该算法可实现该最佳策略,而无需任何有关移动性模式或移动节点接触率的数据。所提出的方法在异构迁移模型以及真实世界中的接触痕迹中得到了广泛的评估,表明其性能大大优于文献中提出的先前方法。

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