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A Multi-radio Packet Scheduling Algorithm for Real-time Traffic in a Heterogeneous Wireless Network Environment

机译：异构无线网络环境下实时流量的多无线分组调度算法

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摘要

The integration of heterogeneous wireless network has become an overwhelming tendency. So, it is a huge challenge for the network designers that how to manage resource in these access networks with different Radio Access Technologies (RATs) in a cooperative mode. As a feasible scheme, Generic Link Layer (GLL) is introduced. In this study, a novel multi-radio packet scheduling algorithm, is proposed for real-time traffic. There are four outstanding contributions in QU. First, in order to guarantee Quality of Service (QoS) of real-time traffic and avoid wasting resource, a scheduling utility function is developed to represent the degree of satisfaction of performing a packet scheduling in term of avoiding wasting resource provided that guaranteeing QoS. Second, using this utility function, a packet scheduling model, which in fact is a NP problem, is designed and analyzed based on joint consideration of fairness. Third, for improving execution rate, Hopfield Neural Network (HNN) is used to fast find an optimal solution for the scheduling model. Final, simulation is set up and is compared with M-LWDF and PLR algorithms to evaluate performance of QU algorithm. Simulation results show that under high load QU algorithm has lower packet loss ratio and higher spectrum efficiency while offers allowable average packet delay.
机译：异构无线网络的集成已成为一种压倒性的趋势。因此，对于网络设计人员来说，如何在协作模式下使用不同的无线接入技术（RAT）管理这些接入网络中的资源是一个巨大的挑战。作为一种可行的方案，引入了通用链路层（Generic Link Layer，GLL）。在这项研究中，提出了一种新颖的多无线分组调度算法，用于实时流量。 QU中有四个杰出的贡献。首先，为了保证实时业务的服务质量（QoS）并避免浪费资源，开发了一种调度实用程序功能来表示执行包调度的满意度，即在保证QoS的情况下避免浪费资源。其次，使用此效用函数，基于公平性的共同考虑，设计并分析了实际上是NP问题的分组调度模型。第三，为了提高执行速度，使用Hopfield神经网络（HNN）快速找到调度模型的最佳解决方案。最后，建立仿真，并与M-LWDF和PLR算法进行比较，以评估QU算法的性能。仿真结果表明，在高负载情况下，QU算法具有较低的丢包率和较高的频谱效率，同时具有允许的平均分组时延。

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