Dr. I-Hong Hou, electrical and computer engineering professor at Texas A&M University, received the Institute of Electrical and Electronics Engineers (IEEE) Communications Society William R. Bennett Prize for innovations in electronic communication systems.
The Bennett Prize is one of the highest honors in the field of communications and computer networking, honoring a single research paper that has made an exceptional contribution to theory or practice. In particular, the prize recognizes work with the potential to have a lasting influence on the field.
Working alongside Dr. Md Kamran Chowdhury Shisher of Purdue University and Dr. Yin Sun of Auburn University, Hou’s winning paper, “Timely Communications for Remote Inference,” highlights a breakthrough in information technology.
The paper addresses a common obstacle in data collection: when speed is prioritized in electronic communications, it creates technical challenges due to the high volume of information. This often results in data congestion, which can create significant challenges.
“When working with sensors, you want to send the most helpful information to the server,” Hou said. “What is most helpful is not necessarily the newest information; sometimes it's slower or older.”
In response, the team developed a property of information randomness that can identify whether a computer server requires a faster, more challenging collection process, or a slower flow of information that’s easier to manage. This concept also helps decide which information is the most important at any given moment — further streamlining data collection systems and preventing disruptions.
This discovery could have significant implications for information systems relying on real-time data transmission. It also challenges the long-held assumption that faster information delivery always leads to better outcomes.
Hou and his team’s research points to a future where data collection systems can perform better by reevaluating the push for speed and adopting a slower, more efficient approach when appropriate.
“This paper challenges an important assumption that has been commonly used in many remote sensing papers over the last decade,” Hou said. “We hope it can lead to new solutions for data collection challenges, particularly in wireless communication.”