Multi-copy data dissemination with probabilistic delay constraint in mobile opportunistic device-to-device networks

Yang Liu, A. Bashar, Fan Li, Yu Wang, Kun Liu
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引用次数: 38

Abstract

Device-to-device (D2D) is a new paradigm that enhances network performance by offering a wide variety of advantages over traditional cellular networks, e.g., efficient spectral usage and extended network coverage. Efficient data dissemination is indispensable for supporting many D2D applications such as content distribution and location-aware advertisement. In this work, we study the problem of multi-copy data dissemination with probabilistic delay constraint in mobile opportunistic D2D networks. We first formally formulate the problem and introduce a centralized heuristic algorithm which aims to discover a graph for multicasting, in order to meet delay constraint and achieve low communication cost. While the centralized solution can be adapted to a distributed implementation, it is inefficient in a mobile opportunistic D2D network, since it intends to apply a deterministic transmission strategy in a nondeterministic network by delivering all data packets via a predetermined route. Based on such observation, we develop a distributed online algorithm based on the optimal stopping strategy that makes an efficient decision on every transmission opportunity. Extensive simulations under real-world traces and random walk mobility model are carried out to learn the performance trend of the proposed schemes under various network settings.
移动机会设备对设备网络中具有概率延迟约束的多副本数据传播
设备对设备(D2D)是一种新的范例,通过提供比传统蜂窝网络更广泛的优势来增强网络性能,例如,高效的频谱使用和扩展的网络覆盖。高效的数据传播对于支持许多D2D应用程序(如内容分发和位置感知广告)是必不可少的。本文研究了移动机会D2D网络中具有概率延迟约束的多副本数据传播问题。我们首先将问题形式化,并引入了一种中心化的启发式算法,该算法的目标是发现用于多播的图,以满足延迟约束和实现低通信成本。虽然集中式解决方案可以适应分布式实现,但它在移动机会D2D网络中效率低下,因为它打算通过预先确定的路由传递所有数据包,从而在不确定网络中应用确定性传输策略。基于这种观察,我们开发了一种基于最优停止策略的分布式在线算法,该算法对每个传输机会都做出了有效的决策。在实际轨迹和随机行走移动模型下进行了大量仿真,以了解所提出方案在不同网络设置下的性能趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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