CAREER: Networking Rechargeable Wireless Devices - Modeling and Resource Allocation

该项目重点研究可充电能源节点组成的无线网络资源分配算法的开发和性能评估。能量收集和超低功耗无线通信方面的最新进展将很快使这种网络得以实现，用于灾难恢复、供应链管理、工业控制和医疗保健应用。能量收集将资源分配的本质从延长设备的有限寿命转变为实现永久寿命，从而带来了根本性的新问题。为了解决这些问题，正在开发一个确定能耗水平的能源管理模块。它基于在不同硬件特性（如电池和电容器）和不同采集环境下产生的各种设置下新的理论效用最大化问题的解决方案。它将为负责睡眠-觉醒、电源控制、路由和调度的协议提供重要的输入。为了实现模块的开发，该项目的目标是：(i)实验表征各种环境下的能源可用性；（ii）为可预测、部分可预测和随机能源设计资源分配算法；（iii）研究算法的通信和计算复杂性之间的权衡，并实验评估其性能。该项目将提供对可充电设备网络设计权衡的基本理解，并将弥合分布式算法和无线网络优化之间的差距，以及新兴的能量收集领域。它将促进自我可持续网络的运作，这将在环境监测和灾难恢复等领域产生巨大的社会影响。

The project focuses on the development and performance evaluation of resource allocation algorithms for wireless networks composed of nodes with rechargeable energy sources. Recent advances in energy harvesting and ultra-low-power wireless communications will soon enable the realization of such networks that will be used in disaster recovery, supply chain management, industrial control, and health care applications. Energy harvesting shifts the essence of resource allocation from prolonging the finite lifespan of a device to enabling perpetual life, thereby posing fundamentally new problems. To solve these problems, an energy management module that determines the energy consumption level is being developed. It is based on solutions to new theoretical utility maximization problems under various settings resulting from different hardware characteristics (e.g., battery and capacitor) and different harvesting environments. It will provide important inputs to protocols responsible for sleep-wake, power control, routing, and scheduling.To enable the development of the module, the goals of the project are: (i) experimentally characterize energy availability in various environments; (ii) design resource allocation algorithms for predictable, partially-predictable, and random energy sources; and (iii) study the tradeoffs between the communication and computation complexities of the algorithms, and experimentally evaluate their performance. The project will provide fundamental understanding of the design tradeoffs in networks of rechargeable devices and will bridge the gap between distributed algorithms and wireless network optimization, and the emerging field of energy harvesting. It will facilitate the operation of self sustainable networks that will have tremendous societal impacts in areas such as environmental monitoring and disaster recovery.