NeTS-NECO: A New Resource Management Paradigm for Sensor Networks with Energy Replenishment

NeTS-NECO：一种新的传感器网络资源管理模式与能源替代（主要研究者：Ness B。Shroff，Emre Koksal和Prasun Sinha）传感器网络的最新进展导致了远程感知环境的独特能力。这些网络可用于感测自然以及人类创造的现象（例如，地震、火灾、部队调动、放射性物质）。这些系统可以部署在偏远或难以到达的地区，因此，这种网络长时间无人值守至关重要。为此，可再生能源领域的新发展表明，这是可行的。然而，传感器网络的设计和控制与可再生能源的附加维度使得管理这些网络的问题具有挑战性，并且与非补给对应物有很大不同。该项目的目标是了解补充传感器网络的性能限制，开发简单的分布式算法和协议，接近这些限制，并验证和微调基于实验的结果。这一雄心勃勃的奋进将由一个团队完成，该团队将带来跨越物理层通信、分布式算法、控制理论、资源分配、传感器网络和实施的专业知识。更广泛的影响：鉴于补充传感器节点是一种新兴技术，本项目中开发的技术有可能对新兴工业部门产生重大影响。PI将通过举办学术和工业研讨会以及促进学生实习来积极分享他们的成果。该项目的学生将学习广泛的理论和实验方法，为他们的劳动力做好准备。私人机构将继续努力招收和培训代表性不足的学生。

NeTS-NECO: A New Resource Management Paradigm for Sensor Networks with Energy Replacement(Principal Investigators: Ness B. Shroff, Emre Koksal, and Prasun Sinha)Recent advances in sensor networks have resulted in a unique capability to remotely sense the environment. These networks can be used to sense natural as well as human-created phenomena (e.g., earthquake, fires, troop movements, radioactive substances). These systems could be deployed in remote or hard-to-reach areas, hence, it is critical that such networks operate unattended for long durations. To that end, new developments in the areas of renewable energy sources suggest that this is feasible. However, the design and control of sensor networks with the added dimension of renewable energy makes the problem of managing these networks challenging and substantially different from their non-replenishment counterparts. The goal of the project is to understand the performance limits of sensor networks with replenishment, to develop simple distributed algorithms and protocols that approach these limits, and validate and fine-tune the results based on experimentation. This ambitious endeavor will be accomplished by a team that brings in expertise that spans physical layer communications, distributed algorithms, control theory, resource allocation, sensor networking, and implementation. Broader Impact: Given that sensor nodes with replenishment are an emerging technology, the techniques developed in this project have the potential to make a significant impact on emerging industry sectors. The PIs will actively share their results by giving academic and industrial seminars and facilitating student internships. Students on this project will learn a wide range of theoretical and experimental methodologies to prepare them for the workforce. The PIs will continue their efforts to recruit and train under-represented students.