Delay Optimal Scheduling of Arbitrarily Bursty Traffic over Multi-State Time-Varying Channels
Delay Optimal Scheduling of Arbitrarily Bursty Traffic over Multi-State Time-Varying Channels
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DOI：
10.1109/glocomw.2016.7848871
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发表时间：
2016-06
期刊：
影响因子：
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通讯作者：
M. Wang;Juan Liu;Wei Chen-
中科院分区：
文献类型：
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作者：
M. Wang;Juan Liu;Wei Chen-
物联网（IoT）的一个重要挑战是在低能耗设备上提供实时服务。本文研究了多状态时变信道上任意突发业务的联合调度问题，从跨层的角度综合考虑了网络层的突发分组到达、数据链路层的积压队列和物理层的固定调制功率自适应传输.为了在功率约束条件下实现最小调度时延，提出了一种概率跨层调度策略，并利用马尔可夫链模型对其进行了描述。为了描述延迟功率权衡，我们制定了一个非线性优化问题，然而，这是非常具有挑战性的解决。为了处理这个问题，我们将优化问题转化为一个等价的线性规划（LP）问题，这使我们能够获得最佳的基于阈值的调度策略，根据每个信道状态的队列长度施加一个最佳阈值。
An important challenge in the Internet of Things (IoT) is to provide real-time services on low-energy-supply devices. In this paper, we study joint queue-aware and channel-aware scheduling of arbitrarily bursty traffic over multi-state time-varying channels, where the bursty packet arrival in the network layer, the backlogged queue in the data link layer, and the power adaptive transmission with fixed modulation in the physical layer are jointly considered from a cross-layer perspective. To achieve minimum queueing delay given a power constraint, a probabilistic cross-layer scheduling policy is proposed, and characterized by a Markov chain model. To describe the delay-power tradeoff, we formulate a non-linear optimization problem, which however is very challenging to solve. To handle with this issue, we convert the optimization problem into an equivalent Linear Programming (LP) problem, which allows us to obtain the optimal threshold-based scheduling policy with an optimal threshold imposed on the queue length in accordance with each channel state.