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首页> 外文期刊>IEEE Journal on Selected Areas in Communications >Multi-Objective Optimization for Edge Device Placement and Reliable Broadcasting in 5G NFV-Based Small Cell Networks
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Multi-Objective Optimization for Edge Device Placement and Reliable Broadcasting in 5G NFV-Based Small Cell Networks

机译:基于5G NFV的小型蜂窝网络中边缘设备放置和可靠广播的多目标优化

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摘要

This paper investigates the problem of locating edge devices in ultra-dense 5G network function virtualization-based small cell networks for the provisioning of reliable broadcasting services. The problem is formulated as a capacitated reliable facility location problem (CRFLP) with failure probability. The solution aims at placing the VNFs of broadcast transmissions optimally on selected edge devices in order to ensure high reliability and minimize the cost of providing broadcast services as well as the probability of loss of service requests. The CRFLP is a non-linear NP-hard problem and it is evaluated by using a multi-objective evolutionary algorithm. Two multi-objective metaheuristics are compared: the multi-objective particle swarm optimization and the nondominated sorting genetic algorithm. Results demonstrate that the proposed solution achieves high levels of reliability as well as low latency.
机译:本文研究了在基于超密集5G网络功能虚拟化的小型蜂窝网络中定位边缘设备的问题,以提供可靠的广播服务。该问题被表述为具有故障概率的能力有限的可靠设施位置问题(CRFLP)。该解决方案旨在将广播传输的VNF最佳地放置在选定的边缘设备上,以确保高可靠性并最小化提供广播服务的成本以及服务请求丢失的可能性。 CRFLP是一个非线性NP难题,通过使用多目标进化算法进行评估。比较了两种多目标元启发式算法:多目标粒子群优化算法和非支配排序遗传算法。结果表明,所提出的解决方案实现了高水平的可靠性以及低延迟。

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