异构M2M上行链路中时延有效的多类分组交换
A Delay Efficient Multiclass Packet Scheduler for Heterogeneous M2M Uplink
摘要：
机器对机器（M2M）通信中的感知业务具有相当异构的服务延迟要求。因此，我们研究的延迟性能的异构M2M上行链路从传感器到M2M应用服务器（AS）通过M2M聚合器（MA）。我们将AS处聚合的异构M2M流量分类为多个定期更新（PU）和事件驱动（ED）类。PU到达是周期性的，需要在预先指定的固定服务截止日期之前处理，而ED到达是随机的，具有固定或软实时或非实时服务要求。我们使用阶梯函数和S形函数分别表示PU和ED分组的服务效用。我们提出了一个延迟有效的多类数据包调度启发式算法，旨在最大限度地提高公平的系统效用度量。具体而言，所提出的调度器优先服务ED数据，同时确保PU数据包满足其服务期限。它还通过惩罚其发生来最大限度地减少关键应用程序的连续PU故障。此外，失败的PU分组被立即从系统中清除，以便减少网络拥塞。使用广泛的模拟，我们表明，所提出的调度器优于流行的分组转发器和性能差距的增加与异质性的延迟要求和更大的惩罚PU故障在关键应用程序。
英文摘要：
The sensory traffic in Machine-to-Machine (M2M) communications has fairly heterogeneous service delay requirements. Therefore, we study the delay-performance of a heterogeneous M2M uplink from the sensors to a M2M application server (AS) via M2M aggregators (MA). We classify the heterogeneous M2M traffic aggregated at AS into multiple Periodic Update (PU) and Event Driven (ED) classes. The PU arrivals are periodic and need to be processed by a prespecified firm service deadline whereas the ED arrivals are random with firm or soft real-time or non real-time service requirements. We use step and sigmoidal functions to represent the service utility for PU and ED packets respectively. We propose a delay efficient multiclass packet scheduling heuristic that aims to maximize a proportionally fair system utility metric. Specifically, the proposed scheduler prioritizes service to ED data while ensuring that the PU packets meet their service deadline. It also minimizes successive PU failures for critical applications by penalizing their occurrences. Furthermore, the failed PU packets are immediately cleared from the system so as to reduce network congestion. Using extensive simulations, we show that the proposed scheduler outperforms popular packet schedulers and the performance gap increases with heterogeneity in latency requirements and with greater penalty for PU failures in critical applications.
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