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Collaborative Research: CNS Core: Medium: Information Freshness in Scalable and Energy Constrained Machine to Machine Wireless Networks

合作研究：CNS 核心：中：可扩展且能量受限的机器对机器无线网络中的信息新鲜度

基本信息

批准号：
2106427
负责人：
Bo Ji
金额：
$ 25万
依托单位：
Virginia Polytechnic Institute and State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2025-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106427&HistoricalAwards=false
关键词：
Collaborative Research CNS Core Medium

项目摘要

With the ever increasing importance of connected devices in smart home, digital healthcare, precision agriculture, smart city, environment and natural disaster monitoring, etc., it is of paramount interest to design the next generation wireless network architecture that can simultaneously support better services while accommodating sharply exponential growth rates of deployment far exceeding the addition of newly available bandwidth. This project will design and analyze new near-optimal machine-to-machine (M2M) network protocols based on the key concept that the quality of service of the machine-based traffic is largely determined by how timely or how fresh the information can be delivered to the destination, instead of the sheer quantity of the delivered messages. With this new shift of design paradigm to information freshness optimization, this project develops novel tools and techniques to quantify and improve the information freshness while meeting the practical requirements of wireless M2M networks, especially on the scalability, energy efficiency, and low-complexity autonomous distributed solutions. The results would significantly advance the state-of-the-art knowledge on M2M wireless network architectures, and propel robust and continuous development of M2M applications by minimizing the battery consumption, increasing the network capacity, and improving the temporal “connectedness” among the smart devices, a critical step forward when realizing the societal impact of Internet-of-Things. To further broaden the participation in network science and computing, the project will implement multiple inclusive mechanisms that increase leadership and participation from women and under-represented groups in a national high-profile annual research workshop (IMACCS) that is being held at the Ohio State University. Several important technical challenges of M2M information freshness optimization will be addressed in this project, including (i) Optimal network coordination when any back and forth message always experiences some random delay, which results in delayed command-&-response in every aspect of the network operations. (ii) Lack of distributional knowledge. Since the delay distributions in practical networks are difficult to estimate and constantly change over time, any practically viable solution must automatically adapt to the underlying unknown delay distributions. (iii) Energy efficiency. Many smart devices are battery limited, which prompts the need for energy-centric, low-complexity distributed network protocol designs. This project will address the above key challenges and develop the analytical foundations for controlling and optimizing information freshness in wireless M2M networks, resulting in fully distributed provably efficient algorithms and protocols that will be extensively evaluated on a large-scale fully programmable 5G wireless network testbed at Rice University.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

随着互联设备在智能家居、数字医疗、精准农业、智慧城市、环境和自然灾害监测等领域的重要性日益增加，设计下一代无线网络体系结构是最重要的，该体系结构可以同时支持更好的服务，同时适应远远超过新增可用带宽的急剧指数增长率的部署。该项目将设计和分析新的接近最优的机器对机器（M2M）网络协议，其关键概念是基于机器的流量的服务质量在很大程度上取决于信息可以交付到目的地的及时性或新鲜度，而不是交付消息的绝对数量。随着设计范式向信息新鲜度优化的新转变，该项目开发了新的工具和技术来量化和提高信息新鲜度，同时满足无线M2M网络的实际需求，特别是在可扩展性，能源效率和低复杂度的自主分布式解决方案上。研究结果将大大推进M2M无线网络架构的最新知识，并通过最小化电池消耗，增加网络容量和改善智能设备之间的时间“连通性”来推动M2M应用的稳健和持续发展，这是实现物联网社会影响的关键一步。为了进一步扩大对网络科学和计算的参与，该项目将实施多个包容性机制，以提高妇女和代表性不足的群体在俄亥俄州州立大学举行的全国高知名度年度研究研讨会（IMACCS）中的领导力和参与度。M2M信息新鲜度优化的几个重要技术挑战将在该项目中解决，包括（i）当任何来回消息总是经历一些随机延迟时的最佳网络协调，这导致在网络操作的每个方面延迟命令-响应。(ii)缺乏分布知识。由于实际网络中的延迟分布很难估计，并且随着时间的推移不断变化，因此任何实际可行的解决方案都必须自动适应潜在的未知延迟分布。(iii)能源效率许多智能设备都是电池有限的，这就需要以能源为中心，低复杂度的分布式网络协议设计。该项目将解决上述关键挑战，并为控制和优化无线M2M网络中的信息新鲜度开发分析基础，从而产生完全分布式的可证明有效的算法和协议，这些算法和协议将在大型Rice大学的大规模完全可编程5G无线网络试验台。该奖项反映了NSF的法定使命，并通过使用基金会的学术价值和更广泛的影响审查标准。