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首页> 外文期刊>Journal of network and computer applications >Enhanced class based dynamic priority scheduling to support uplink IoT traffic in LTE-A networks
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Enhanced class based dynamic priority scheduling to support uplink IoT traffic in LTE-A networks

机译：基于增强类的动态优先级调度，以支持LTE-A网络中的上行链路IoT流量

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摘要

Internet of Things (IoT) has now become a common term in technological communities. Machine-to-machine communications (M2M) is one of the components of IoT which deals with communication of devices to device and device to the network aspects. LTE-A networks have emerged as one of the preferred underlying communication networks to support IoT or M2M traffic. However, the uplink packet scheduling to optimize the QoS (quality of service) of M2M traffic without affecting or least affecting the QoS of Human-to-human (H2H) traffic (traffic generated by regular users (also called as H2H users) such as smartphone traffic, Internet traffic, voice traffic, etc.) is one of the main challenges in LTE-A networks. As a solution, we propose an uplink packet scheduling algorithm, called as enhanced class based dynamic priority (E-CBDP) algorithm, which ensures the QoS of H2H traffic by giving it priority over M2M traffic but, optimizes the QoS of M2M traffic by pushing the scheduling of H2H traffic to their delay boundaries. Further, a dynamic M2M traffic control threshold is defined to enable the operator for proactive regulation of the huge M2M traffic to avoid network congestion as well as to minimise the impact on H2H traffic. We characterize the proposed scheduling algorithm via a mathematical analysis for the metrics such as average length of the H2H queue, average length of the M2M queue, average waiting time of H2H packets, and average waiting time of M2M packets. We compare the performance of E-CBDP algorithm with some recent solutions in terms of average delay, percentage of packets dropped, aggregate throughput, fairness, and energy consumption. Simulation results show that E-CBDP algorithm demonstrates excellent performance in terms of packet drop rate and fairness while provides satisfactory performance in terms of delay, throughput, and energy consumption.
机译：物联网（IoT）现在已成为技术社区中的通用术语。机器对机器通信（M2M）是IoT的组件之一，它处理设备到设备的通信以及设备到网络的通信。 LTE-A网络已经成为支持IoT或M2M流量的首选基础通信网络之一。但是，上行链路分组调度可优化M2M流量的QoS（服务质量），而不影响或至少不影响人对人（H2H）流量（由常规用户（也称为H2H用户）生成的流量）的QoS。智能手机流量，互联网流量，语音流量等）是LTE-A网络的主要挑战之一。作为解决方案，我们提出了一种上行分组调度算法，称为增强类动态优先级（E-CBDP）算法，该算法通过优先于M2M流量来确保H2H流量的QoS，但通过推送优化M2M流量的QoS。 H2H流量到其延迟边界的调度。此外，定义了动态的M2M流量控制阈值，以使运营商能够主动调节庞大的M2M流量，从而避免网络拥塞并将对H2H流量的影响降至最低。我们通过对度量标准的数学分析来表征所提出的调度算法，例如H2H队列的平均长度，M2M队列的平均长度，H2H数据包的平均等待时间以及M2M数据包的平均等待时间。我们将E-CBDP算法的性能与一些最新解决方案进行了比较，包括平均延迟，丢包百分比，总吞吐量，公平性和能耗。仿真结果表明，E-CBDP算法在丢包率和公平性方面表现出出色的性能，而在延迟，吞吐量和能耗方面则表现出令人满意的性能。

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