论文标题
具有异质流量的时间关键网络的动态功率控制
Dynamic Power Control for Time-Critical Networking with Heterogeneous Traffic
论文作者
论文摘要
未来的无线网络将以异质的流量要求为特征。这样的要求可以是低延迟或最低征收。因此，网络必须适应不同的需求。通常，具有低延迟要求的用户必须在特定的时间范围内（即在截止日期之前）提供需求，并且与面向吞吐量的用户共存。此外，用户是移动设备，他们共享相同的无线频道。因此，他们必须调整电力传输才能实现可靠的沟通。但是，由于无线移动设备的功率预算有限，网络需要采取强力调度方案。在这项工作中，我们提出了一个随机网络优化问题，以最大程度地降低数据包的降低率，同时保证最小的吞吐量并考虑到用户的有限功率功能。我们应用Lyapunov优化理论中的工具，以提供一种名为Dynamic Power Control（DPC）算法的算法，该算法可以实时解决配方问题。事实证明，DPC算法给出了一个任意接近最佳的解决方案。仿真结果表明，我们的算法的表现优于基线最大的debt-First（LDF）算法，用于短期和多个用户。
Future wireless networks will be characterized by heterogeneous traffic requirements. Such requirements can be low-latency or minimum-throughput. Therefore, the network has to adjust to different needs. Usually, users with low-latency requirements have to deliver their demand within a specific time frame, i.e., before a deadline, and they co-exist with throughput oriented users. In addition, the users are mobile and they share the same wireless channel. Therefore, they have to adjust their power transmission to achieve reliable communication. However, due to the limited power budget of wireless mobile devices, a power-efficient scheduling scheme is required by the network. In this work, we cast a stochastic network optimization problem for minimizing the packet drop rate while guaranteeing a minimum throughput and taking into account the limited-power capabilities of the users. We apply tools from Lyapunov optimization theory in order to provide an algorithm, named Dynamic Power Control (DPC) algorithm, that solves the formulated problem in realtime. It is proved that the DPC algorithm gives a solution arbitrarily close to the optimal one. Simulation results show that our algorithm outperforms the baseline Largest-Debt-First (LDF) algorithm for short deadlines and multiple users.
