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

NETS-NECO：一种新的能源替代传感器网络资源管理模式(主要研究人员：Ness B.Shroff，Emre Koksal和Prasun Sinha)传感器网络的最新进展导致了一种独特的远程感知环境的能力。这些网络可用于感知自然和人为现象(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，此类网络在无人值守的情况下长时间运行至关重要。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增加了可再生能源的维度，使得管理这些网络的问题具有挑战性，并且与非补给网络有很大的不同。该项目的目标是通过补充了解传感器网络的性能极限，开发接近这些极限的简单分布式算法和协议，并基于实验验证和微调结果。这一雄心勃勃的努力将由一个团队完成，该团队将带来横跨物理层通信、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：鉴于带有补给的传感器节点是一项新兴技术，该项目开发的技术有可能对新兴工业部门产生重大影响。督导人员会积极分享成果，举办学术和工业研讨会，并为学生实习提供便利。这个项目的学生将学习广泛的理论和实验方法，为他们的工作做好准备。督学将继续努力招收和培训人数不足的学生。

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.