MRI:Development of Energy-Efficient Embedded Systems for Wireless Sensor Networks

MRI：无线传感器网络节能嵌入式系统的开发

• 批准号: 0521227
• 负责人: Anthony Ephremides
• 金额: $ 40万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2009-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0521227&HistoricalAwards=false
• 关键词: MRI; Development; Energy; Efficient; Embedded

This project, developing experimental prototypes of intelligent energy-efficient embedded systems for use in nodes of sensor networks, plans to acquire the hardware equipment that -Builds energy efficient embedded sensor systems;-Characterizes their energy consumption parameters; and-Verifies and evaluates new designs.The goal is to translate ongoing research on energy efficiency to development of advanced sensors that incorporates as many energy-saving features as possible while at the same time remain light, small, inexpensive, and relatively flexible. The investigation covers the spectrum: energy-efficient circuitry, energy-aware architectures, energy-aware embedded systems compilers, energy-efficient system integration, and energy-efficient communication and networking. The research needs to-Compare analog and digital circuit implementations, Modify standard processor architectures,-Develop dynamic memory management schemes, Integrate the components, and-Tailor those (chosen for overall efficiency) to carefully chosen algorithms for processing and transmissionVirtually all wireless networks are crucially dependent on portable finite energy sources. In particular, sensor networks for a large number of applications (such as event detection, monitoring, and data collection) depend on non-renewable energy sources. Both dominant forms of energy used in sensor networks, RF Transmission and Processing, exhibit expenditure modes that depend on a large number of factors, from the bottom layer up to the network protocol stack. Clearly, there is a fundamental tradeoff between energy spent at transmission and energy spent for processing. For example, data collected by sensors can undergo complex compression that reduces the number of transmitted bits and hence saves transmission energy at the expense of increases processing energy; thus the component of the sensor that includes the communication system must also be optimized with respect to energy efficiency. Hence, this work experiments with different scenarios of network communication. Through both simulation and prototype implementation, two particular issues related to communication and networking are studied: To-Integrate communication functions such as modulation and coding with hardware design (e.g., power amplifier) -Evaluate power consumption of transmission vs. processing and longer vs. shorter hops with actual physical tests-To calculate the energy consumption tradeoffs, measurements and display equipment are necessary. Specific research projects include-Energy-efficient circuit design; Micro-controller architectures; Memory hierarchies; -Component integration, and Communication protocols.Broader Impact: The project should have a huge educational impact. While training the next generation of researchers, this work contributes a freely available tool for cycle-level simulation to accurately estimate energy consumption of the design. The need for deployment of long-lived sensor networks is well documented and affects directly the commercial and military sectors. An opportunity exists for significant reductions in energy consumption.

该项目开发了用于在传感器网络节点中使用的智能节能嵌入式系统的实验原型，计划获取可构建能源有效嵌入的传感器系统的硬件设备； - 将其能源消耗参数付诸实践；目标是将有关能源效率的持续研究转化为高级传感器的开发，并将其尽可能多的节能功能转化为开发，而同时保持轻度，小，便宜且相对灵活。调查涵盖了频谱：节能电路，能源感知体系结构，能源感知的嵌入式系统编译器，节能系统集成以及节能的通信和网络。这项研究需要进行兼容的模拟和数字电路实现，修改标准处理器架构， - 开发动态内存管理方案，将组件和零件（用于总体效率选择）集成到精心选择的处理算法的构成和售货员，用于处理和输入的所有无线网络，所有无线网络都非常依赖于可移植的有限有限的能源源。特别是，用于大量应用程序（例如事件检测，监视和数据收集）的传感器网络取决于非可再生能源。传感器网络，RF传输和处理中使用的两种主要能量形式都表现出取决于大量因素的支出模式，从底层到网络协议堆栈。显然，在传输上花费的能源与用于处理的能源之间存在基本的权衡。例如，传感器收集的数据可以进行复杂的压缩，从而减少传输位的数量，从而节省传输能量以增加加工能量为代价。因此，还必须针对能源效率优化传感器的组件。因此，这项工作实验了网络通信的不同方案。通过模拟和原型实施，研究了与通信和网络有关的两个特定问题：逐步通信功能，例如使用硬件设计（例如，功率放大器）进行调制和编码 - 评估传输与处理的功率消耗以及处理更长的与较短的啤酒花，从而通过实际的物理测试来计算能源消费量的交易折叠率，并进行了测量。特定的研究项目包括能量效率的电路设计；微控制器架构；内存层次结构； - 组成的集成和通信协议。BRODER的影响：该项目应具有巨大的教育影响。在培训下一代研究人员的同时，这项工作为自行车级模拟提供了免费的工具，可以准确估计设计的能耗。长寿传感器网络的部署需求已充分记录在案，并直接影响商业和军事部门。存在大幅减少能源消耗的机会。