CAREER: Networking Rechargeable Wireless Devices - Modeling and Resource Allocation
CAREER: Networking Rechargeable Wireless Devices - Modeling and Resource Allocation
批准号:
1054856
负责人:
Gil Zussman
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-01-01 至 2015-12-31
中文摘要
该项目的重点是开发和性能评估的资源分配算法的无线网络组成的节点与可充电能源。能量收集和超低功耗无线通信的最新进展将很快实现这种网络,这些网络将用于灾难恢复、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,从而提出了根本性的新问题。为了解决这些问题,正在开发确定能源消耗水平的能源管理模块。它是基于解决新的理论效用最大化问题的各种设置下,由不同的硬件特性(例如,电池和电容器)和不同的收获环境。该模块将为负责睡眠-唤醒、功率控制、路由和调度的协议提供重要的输入。为了使该模块的开发成为可能,该项目的目标是:(i)实验性地表征各种环境中的能量可用性;(ii)为可预测、部分可预测和随机的能量源设计资源分配算法;(iii)为可预测的、部分可预测的和随机的能量源设计资源分配算法。以及(iii)研究算法的通信复杂度和计算复杂度之间的折衷,并通过实验评估它们的性能。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与新兴能量收集领域之间的差距。它将促进自我维持网络的运作,这些网络将在环境监测和灾后恢复等领域产生巨大的社会影响。
英文摘要
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.
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