Age-of-Information (AoI)
Age-of-information (AoI) is a metric used to assess the freshness of data by measuring latency from receivers’ perspectives. It is simply defined as the time elapsed since the latest useful piece of information that reached its intended destination has been generated at its source.
AoI is very relevant in applications in which information is time-varying, such as in vehicular monitoring systems, industrial sensor networks and surveillance videos, among others.
Techniques used to optimize other latency metrics, such as rate (throughput) and transmission delay, are often not optimal in AoI-centric frameworks. It is therefore necessary to develop new methodologies to optimize and analyze systems that use AoI, or more generally any functional of AoI, as their performance metric.
One main research goal of our group is to study the fundamental nature of AoI, and how useful it can be in communications, networks and control applications.
Below are some examples of the landscape that we cover in this regard (sorted by topic name alphabetically).
Channel Coding
Cloud Computing
Age and Value of Information Optimization for Systems with Multi-Class Updates
A. Arafa and Roy D. Yates
IEEE International Conference on Communications (ICC), Denver, Colorado, June 2024.
Timely Cloud Computing: Preemption and Waiting
A. Arafa, R. D. Yates, and H. V. Poor
Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, September 2019.
Economics and Data Markets
Economics of Fresh Data Trading
M. Zhang, A. Arafa, J. Huang, and H. V. Poor
Chapter 17 in Age of Information: Foundations and Applications, B. Zhou, W. Saad, H. Dhillon, N. Pappas and M. A. Abd-Elmagid, Eds., Cambridge University Press, Cambridge, UK, 2023, pp. 429–455.
Optimal and Quantized Mechanism Design for Fresh Data Acquisition
M. Zhang, A. Arafa, E. Wei, and R. A. Berry
IEEE Journal on Selected Areas in Communications, 39(5): 1226–1239, May 2021.
Pricing Fresh Data
M. Zhang, A. Arafa, J. Huang, and H. V. Poor
IEEE Journal on Selected Areas in Communications, 39(5): 1211–1225, May 2021.
Optimal Mechanism Design for Fresh Data Acquisition
M. Zhang, A. Arafa, E. Wei, and R. A. Berry
IEEE International Symposium on Information Theory (ISIT), Melbourne, Australia, July 2021.
How to Price Fresh Data
M. Zhang, A. Arafa, J. Huang, and H. V. Poor
International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Avignon, France, June 2019.
Energy Harvesting Communications
Age Minimization in Energy Harvesting Communications
A. Arafa, S. Fang, J. Yang, S. Ulukus, and H. V. Poor
Chapter 8 in Green Communications for Energy-Efficient Wireless Systems and Networks, H. A. Suraweera, J. Yang, A. Zappone, J. S. Thompson, Eds., The Institution of Engineering and Technology (IET) Press, London, 2020, pp. 203–230.
Timely Status Updating Over Erasure Channels Using an Energy Harvesting Sensor: Single and Multiple Sources
A. Arafa, J. Yang, S. Ulukus, and H. V. Poor
IEEE Transactions on Green Communications and Networking, 6(1): 6–19, March 2022.
Age-Minimal Transmission for Energy Harvesting Sensors with Finite Batteries: Online Policies
A. Arafa, J. Yang, S. Ulukus, and H. V. Poor
IEEE Transactions on Information Theory, 66(1): 534–556, January 2020.
Timely Updates in Energy Harvesting Two-Hop Networks: Offline and Online Policies
A. Arafa and S. Ulukus
IEEE Transactions on Wireless Communications, 18(8): 4017–4030, August 2019.
Timely Updating with Intermittent Energy and Data for Multiple Sources over Erasure Channels
C. Daniel Jr. and A. Arafa
IEEE International Symposium on Wireless Communication Systems (ISWCS), Berlin, Germany, September 2021.
Using Erasure Feedback for Online Timely Updating with an Energy Harvesting Sensor
A. Arafa, J. Yang, S. Ulukus, and H. V. Poor
IEEE International Symposium on Information Theory (ISIT), Paris, France, July 2019.
Online Timely Status Updates with Erasures for Energy Harvesting Sensors
A. Arafa, J. Yang, S. Ulukus, and H. V. Poor
Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, October 2018.
Age-Minimal Online Policies for Energy Harvesting Sensors with Radom Battery Recharges
A. Arafa, J. Yang, and S. Ulukus
IEEE International Conference on Communications (ICC), Kansas City, Missouri, May 2018.
Age-Minimal Online Policies for Energy Harvesting Sensors with Incremental Battery Recharges
A. Arafa, J. Yang, S. Ulukus, and H. V. Poor
Information Theory and Applications (ITA) Workshop, San Diego, California, February 2018.
Age-Minimal Transmission in Energy Harvesting Two-Hop Networks
A. Arafa and S. Ulukus
IEEE Global Communications Conference (Globecom), Singapore, December 2017.
Age Minimization in Energy Harvesting Communications: Energy-Controlled Delays
A. Arafa and S. Ulukus
Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, California, October 2017.
Fundamentals
Age of Information in Mobile Networks: Fundamental Limits and Tradeoffs
M. Zhang, H. H. Yang, A. Arafa, and H. V. Poor
ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc), Athens, Greece, October 2024.
Large-Scale Networking
Spatiotemporal Analysis for Age of Information in Random Access Networks Under Last-Come First-Serve With Replacement Protocol
H. H. Yang, A. Arafa, T. Q. S. Quek, and H. V. Poor
IEEE Transactions on Wireless Communications, 21(4): 2813–2829, April 2022.
Optimizing Information Freshness in Wireless Networks: A Stochastic Geometry Approach
H. H. Yang, A. Arafa, T. Q. S. Quek, and H. V. Poor
IEEE Transactions on Mobile Computing, 20(6): 2269–2280, June 2021.
Age of Information in Random Access Networks: A Spatiotemporal Study
H. H. Yang, A. Arafa, T. Q. S. Quek, and H. V. Poor
IEEE Global Communications Conference (Globecom), Taipei, Taiwan, December 2020.
Locally Adaptive Scheduling Policy for Optimizing Information Freshness in Wireless Networks
H. H. Yang, A. Arafa, T. Q. S. Quek, and H. V. Poor
IEEE Global Communications Conference (Globecom), Waikoloa, Hawaii, December 2019.
Machine Learning
Towards Understanding Federated Learning over Unreliable Networks
C. Feng, A. Arafa, Z. Chen, M. Zhao, T. Q. S. Quek, and H. H. Yang
Submitted.
Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networks
H. H. Yang, A. Arafa, T. Q. S. Quek, and H. V. Poor
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.
Privacy-Preserving Systems
Remote Estimation and Tracking
Timely Multi-Process Estimation Over Erasure Channels With and Without Feedback: Signal Independent Policies
K. Banawan, A. Arafa, and K. G. Seddik
IEEE Journal on Selected Areas in Information Theory, 4: 607–623, November 2023.
Short Blocklength Process Monitoring and Scheduling: Resolution and Data Freshness
S. Roth, A. Arafa, A. Sezgin, and H. V. Poor
IEEE Transactions on Wireless Communications, 21(7): 4669–4681, July 2022.
Sample, Quantize and Encode: Timely Estimation Over Noisy Channels
A. Arafa, K. Banawan, K. G. Seddik, and H. V. Poor
IEEE Transactions on Communications, 69(10): 6485–6499, October 2021.
Timely Multi-Process Estimation with Erasures
K. Banawan, A. Arafa, and K. G. Seddik
Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, California, October 2022.
Timely Estimation Using Coded Quantized Samples
A. Arafa, K. Banawan, K. G. Seddik, and H. V. Poor
IEEE International Symposium on Information Theory (ISIT), Los Angeles, California, June 2020.
Remote Short Blocklength Process Monitoring: Trade-off Between Resolution and Data Freshness
S. Roth, A. Arafa, H. V. Poor, and A. Sezgin
IEEE International Conference on Communications (ICC), Dublin, Ireland, June 2020.
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