Jiang Part of National Institute Exploring the Synergies Between Networking and AI

7/29/2021 10:13:45 AM Colin Robertson, Illinois CS

Illinois CS professor Nan Jiang will collaborate with researchers from 10 other universities as part of the new AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE).

Written by Colin Robertson, Illinois CS

Illinois CS professor Nan Jiang will collaborate with researchers from 10 other universities as part of the new AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE). The institute is one of 11 new National Artificial Intelligence (AI) Research Institutes announced today by the National Science Foundation, building on the first round of seven institutes funded in 2020.

AI-EDGE will leverage the synergies between networking and AI to design future generations of wireless edge networks that are highly efficient, reliable, robust and secure and facilitate solving long-standing distributed AI challenges. The project, led by The Ohio State University, will receive $20 million over five years.

Nan Jiang
Nan Jiang

Jiang, who is an expert in reinforcement learning, will focus his efforts on exploring how AI can help optimize computer network operations. Reinforcement learning (RL) is a category of machine learning where algorithms learn to perform tasks by maximizing the rewards received for their actions.

“Computer networks are inherently complex dynamical systems, where decisions made often have delayed consequences. RL is a promising paradigm for controlling and optimizing such dynamical systems in a data-driven manner,” said Jiang.

He believes that the theoretical and practical real-world challenges posed by computer networks will help expand the current scope of RL research, with applications to other domains. “Success in controlling and optimizing such systems using machine-learning approaches will transfer to other complex networks, including social networks, power grid, and so on,” said Jiang.

“I am excited to develop novel RL algorithms that take into consideration real-world constraints and structures embedded in the network applications,” Jiang said. “In particular, the control of networks is in its nature multi-agent, decentralized, and multi-timescale. Investigating RL for network control will significantly push forward the boundary of RL research.”

Due to the proliferation of wireless devices, services, and applications, most network growth is expected to happen at the network edge rather than the traditional network core. AI-EDGE will develop new AI tools and techniques to ensure that wireless edge networks are self-healing and self-optimized. These networks will make AI more efficient, interactive, and privacy-preserving for applications in sectors such as intelligent transportation, remote health care, distributed robotics and smart aerospace.

According to Jiang, AI has been previously applied to wireless edge networks, but applications have been typically restricted to limited scenarios where the rest of the network is affected in a simple and well-understood manner.

“It is the scale and the complexity of the network that makes the difference, which the project will address,” Jiang said. “Most control decisions in the network impact the rest of the network in more complicated and intertwined ways: the consequences can be delayed and intertwined, the decisions made at different network entities can happen at different time scales, and we may want to coordinate the decisions across a large number of entities.”

“These technologies, AI and networking, are critical for a number of things that we do. They are critical for economic health, they are critical for technological development, and they are critical for national defense and national safety,” said AI-EDGE principal investigator Ness Shroff, a professor of electrical and computer engineering and computer science and engineering at Ohio State, in a press release. “It’s extremely important that the U.S. regain its competitive edge in these technologies, and part of the work of these AI institutes is to help make that happen.”

AI-EDGE includes collaborators from Carnegie Mellon University, Northeastern University, The Ohio State University, Purdue University, University of Wisconsin-Madison, University of Michigan, University of Texas-Austin, University of Washington, University of Massachusetts-Amherst, University of Illinois-Urbana-Champaign and University of Illinois-Chicago. It will also work with industrial partners including AT&T, IBM, Microsoft and Qualcomm and the Air Force Research Lab, Army Research Lab and Naval Research Lab to translate the research so that it is widely adopted.

About the National AI Research Institutes
Led by NSF, and in partnership with the U.S. Department of Agriculture National Institute of Food and Agriculture, U.S. Department of Homeland Security, Google, Amazon, Intel and Accenture, the National AI Research Institutes will act as connections in a broader nationwide network to pursue transformational advances in a range of economic sectors, and science and engineering fields — from food system security to next-generation edge networks.

Read more:
National Science Foundation press release
Ohio State press release

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This story was published July 29, 2021.