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Group Mobility-Based Optimization of Cache Content in Wireless Device-to-Device Networks

机译:基于组移动性的无线设备到设备网络中的缓存内容优化

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Content caching in Device-to-Device (D2D) wireless cellular network can be considered an attractive solution to decrease network load during peak time hence improve network performance. In such network, predicting users' movement pattern allows proactive caching to alleviate its congestion leading to load decrease. Optimizing caching process is one important issue to enhance network performance and thus increase offloading probability. In this work, a caching policy strategy is introduced where the network jointly recognizes group mobility and user preferences to solve the caching optimization problem. Particle Swarm Optimization (PSO) algorithm is used to minimize the overall network load by optimizing the amount of data cached in users devices. Simulations are carried out to evaluate performance of presented optimal caching policy. Numerical results in terms of network gain show that the proposed caching scheme optimized by PSO outperforms both baseline scenario and random mobility-based schemes.
机译:设备到设备(D2D)无线蜂窝网络中的内容缓存可以被认为是一种有吸引力的解决方案,可以减少高峰时间的网络负载,从而提高网络性能。在这样的网络中,预测用户的移动模式允许主动缓存以减轻其拥塞,从而导致负载减少。优化缓存过程是提高网络性能从而增加卸载概率的重要问题之一。在这项工作中,引入了一种缓存策略策略,其中网络可以共同识别组移动性和用户偏好来解决缓存优化问题。粒子群优化(PSO)算法用于通过优化用户设备中缓存的数据量来最大程度地降低整体网络负载。进行仿真以评估所提出的最佳缓存策略的性能。在网络增益方面的数值结果表明,由PSO优化的拟议缓存方案优于基线方案和基于随机移动性的方案。

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