能量收集网络的效用最优调度
Utility Optimal Scheduling in Energy Harvesting Networks
摘要：
在本文中，我们展示了如何在只有有限容量能量存储设备的能量收集网络中实现接近最优的效用性能。在这些网络中，节点能够从环境中收集能量。可以收集的能量的量是随时间变化的，并且根据某种概率定律而演变。我们开发了一个\emph{online}算法，称为能量有限的调度算法（ESA），它共同管理的能量，并作出功率分配决定的数据包传输。ESA只需要跟踪网络节点处剩余的能量的量和可收获能量过程的\emph{does not require any knowledge}。我们表明，ESA实现了一个实用程序，是在$O(ε)$的最佳，对于任何$ε>0$，同时确保网络拥塞和所需的能量存储设备的容量是\emph{deterministically}上限的大小$O(1/ε)$。然后，我们还开发了改进的ESA算法（MESA），以实现相同的$O(ε)$接近实用程序的性能，平均网络拥塞和所需的能量存储设备的容量只有$O([\log(1/ε)]^2)$。
英文摘要：
In this paper, we show how to achieve close-to-optimal utility performance in energy harvesting networks with only finite capacity energy storage devices. In these networks, nodes are capable of harvesting energy from the environment. The amount of energy that can be harvested is time varying and evolves according to some probability law. We develop an \emph{online} algorithm, called the Energy-limited Scheduling Algorithm (ESA), which jointly manages the energy and makes power allocation decisions for packet transmissions. ESA only has to keep track of the amount of energy left at the network nodes and \emph{does not require any knowledge} of the harvestable energy process. We show that ESA achieves a utility that is within $O(ε)$ of the optimal, for any $ε>0$, while ensuring that the network congestion and the required capacity of the energy storage devices are \emph{deterministically} upper bounded by bounds of size $O(1/ε)$. We then also develop the Modified-ESA algorithm (MESA) to achieve the same $O(ε)$ close-to-utility performance, with the average network congestion and the required capacity of the energy storage devices being only $O([\log(1/ε)]^2)$.
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