Age of Information

A New Metric for Information Freshness
Erscheinungsjahr 2019
ISBN: 978-3-031-79292-2
Verlag: Springer International Publishing

Buch, Englisch, 204 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 435 g

Reihe: Synthesis Lectures on Learning, Networks, and Algorithms

Information usually has the highest value when it is fresh. For example, real-time knowledge about the location, orientation, and speed of motor vehicles is imperative in autonomous driving, and the access to timely information about stock prices and interest rate movements is essential for developing trading strategies on the stock market. The Age of Information (AoI) concept, together with its recent extensions, provides a means of quantifying the freshness of information and an opportunity to improve the performance of real-time systems and networks. Recent research advances on AoI suggest that many well-known design principles of traditional data networks (for, e.g., providing high throughput and low delay) need to be re-examined for enhancing information freshness in rapidly emerging real-time applications. This book provides a suite of analytical tools and insightful results on the generation of information-update packets at the source nodes and the design of network protocols forwarding the packets to their destinations. The book also points out interesting connections between AoI concept and information theory, signal processing, and control theory, which are worthy of future investigation.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Sun, Yin

Modiano, Eytan

Kadota, Igor

Talak, Rajat

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme

Inhaltsverzeichnis

List of Figures.- List of Tables.- Preface.- Introduction.- Age of Information in Queueing Networks.- Age of Information in Broadcast Wireless Networks.- Age of Information in General Wireless Networks.- Age of Information and Sampling.- Bibliography.- Authors' Biographies.

Über Autor(innen)

Yin Sun is an assistant professor in the Department of Electrical and Computer Engineering at Auburn University, Alabama. He received his B.Eng. and Ph.D. degrees in Electronic Engineering from Tsinghua University, in 2006 and 2011, respectively. He was a postdoctoral scholar and research associate at the Ohio State University from 2011-2017. His research interests include wireless communications, communication networks, information freshness, information theory, and machine learning. He is a co-founder of the Age of Information Workshop. Papers that he co-authored received the best student paper award at IEEE WiOpt 2013 and the bestpaper award at IEEE WiOpt 2019. Igor Kadota received the B.S. degree in electronic engineering from the Technological Institute of Aeronautics (ITA), Brazil, in 2010, the S.M. degree in telecommunication from ITA in 2013, and the S.M. degree in communication networks from Massachusetts Institute of Technology (MIT) in 2016, where he is currently working toward the Ph.D. degree at the Laboratory for Information and Decision Systems (LIDS). His research is on modeling, analysis, and design of communication networks, with an emphasis on wireless networks and real-time traffic. Igor received the IEEE INFOCOM 2018 best paper award for his work on age of information. Rajat Talak is a Ph.D. student in the Laboratory of Information and Decision Systems (LIDS) at Massachusetts Institute of Technology. He received a Master of Science degree from the Department of Electrical Communication Engineering at the Indian Institute of Science, Bangalore, India, in 2013. He was awarded the prestigious Prof. F. M. Mowdawalla medal for his master’s thesis. His research inclination is toward modeling, analysis, and design of algorithms for networked systems. His current focus has been toward studying age of information and guaranteeing information freshness in wireless networks. He is the recipient of the best paper award at MobiHoc 2018. His other notable work includes developing a new theoretical framework for machine learning and robotic perception. Eytan Modiano is a Professor in the Department of Aeronautics and Astronautics and Associate Director of the Laboratory for Information and Decision Systems (LIDS) at MIT. Prior to joining the faculty at MIT in 1999, he was a Naval Research Laboratory Fellow between 1987-1992, a National Research Council Postdoctoral Fellow from 1992-1993, and a member of the technical staff at MIT Lincoln Laboratory between 1993–1999. Eytan Modiano received his B.S. degree in Electrical Engineering and Computer Science from the University of Connecticut at Storrs in 1986 and his M.S. and Ph.D. degrees, both in Electrical Engineering, from the University of Maryland, College Park, in 1989 and 1992 respectively. His research is on the modeling, analysis, and design of communication networks and protocols. He is the co-recipient of best paper awards from Infocom 2018, MobiHoc 2018, MobiHoc 2016, Wiopt 2013, andSigmetrics 2006. He is the Editor-in-Chief for IEEE/ACMTransactions on Networking and served as Associate Editor for IEEE Transactions on Information Theory and IEEE/ACM Transactions on Networking. He was the Technical Program co-chair for IEEE Wiopt 2006, IEEE Infocom 2007, ACM MobiHoc 2007, and DRCN 2015. He had served on the IEEE Fellows committee in 2014 and 2015, and he is a Fellow of the IEEE and an Associate Fellow of the AIAA.