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

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与日俱增，设计下一代无线网络体系结构至关重要，该体系结构能够同时支持更好的服务，同时适应部署的急剧指数增长速度，远远超过新增加的可用带宽。该项目将基于这样一个关键概念设计和分析新的近乎最佳的机器到机器(M2M)网络协议，即基于机器的流量的服务质量在很大程度上取决于将信息传递到目的地的及时性或新鲜度，而不是所传递的消息的绝对数量。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、能效和低复杂性的自主分布式解决方案方面。研究结果将显著促进对M2M无线网络架构的最先进知识，并通过最大限度地减少电池消耗、增加网络容量和改善智能设备之间的临时“连接性”，推动M2M应用的强劲和持续发展，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，该项目将实施多种包容性机制，增加妇女和代表性不足群体的领导力和参与正在俄亥俄州立大学举行的全国知名年度研究研讨会(IMACCS)。本项目将解决M2M信息新鲜度优化的几个重要技术挑战，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，这导致网络操作的各个方面的命令响应延迟。(Ii)缺乏分布知识。由于实际网络中的时延分布很难估计，并且随着时间的推移不断变化，任何实际可行的解决方案都必须自动适应潜在的未知时延分布。(三)能源效率。许多智能设备电池有限，这就需要以能源为中心、低复杂性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，从而产生可证明有效的完全分布式算法和协议，这些算法和协议将在莱斯大学测试的大规模完全可编程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优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.