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：
2107363
负责人：
Chih-Chun Wang
金额：
$ 25万
依托单位：
Purdue 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=2107363&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，设计能够同时支持更好的服务和更好的服务的下一代无线网络架构至关重要。该项目将基于机器服务质量这一关键概念来设计和分析新的近乎最优的机器对机器 (M2M) 网络协议。基础流量很大程度上取决于如何通过将设计范式向信息新鲜度优化的新转变，该项目开发了新颖的工具和技术来量化和提高信息新鲜度。满足无线 M2M 网络的实际要求，特别是在可扩展性、能源效率和低复杂性自主分布式解决方案方面，其结果将显着推进 M2M 无线网络架构的最新知识，并推动稳健和连续的发展。发展M2M 应用通过最大限度地减少电池消耗、增加网络容量并改善智能设备之间的临时“连接性”，这是实现物联网社会影响的关键一步，进一步扩大对网络科学和技术的参与。在计算方面，该项目将实施多种包容性机制，以提高妇女和代表性不足群体在俄亥俄州立大学举办的全国性高调年度研究研讨会 (IMACCS) 中的领导力和参与度。 M2M 信息的几个重要技术挑战。新鲜度优化将得到解决在这个项目中，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，这会导致网络操作各个方面的命令和响应延迟。实际网络中的延迟分布很难估计，并且会随着时间的推移而不断变化，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）许多智能设备的电池有限，这提示需要以能源为中心。、低复杂度分布式网络协议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奠定分析基础，从而产生完全分布式、可证明有效的算法和协议，并将在大规模完全可编程 5G 无线网络上进行广泛评估。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。