Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Update or Wait: How to Keep Your Data Fresh
Date
2017-11-01
Author
Sun, Yin
Uysal, Elif
Yates, Roy D.
Koksal, C. Emre
Shroff, Ness B.
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
232
views
0
downloads
Cite This
In this paper, we study how to optimally manage the freshness of infimmation updates sent from a source node to a destination via a channel. A proper metric for data freshness at the destination is the age-of-information, or simply age, which is defined as how old the freshest received update is, since the moment that this update was generated at the source node (e.g., a sensor). A reasonable update policy is the zero wait policy, i.e., the source node submits a fresh update once the previous update is delivered, which achieves the maximum throughput and the minimum delay. Surprisingly, this zero wait policy does not always minimize the age. This counter-intuitive phenomenon motivates us to study how to optimally control information updates to keep the data fresh and to understand when the zero-wait policy is optimal. We introduce a general age penalty function to characterize the level of dissatisfaction on data staleness and formulate the average age penalty minimization problem as a constrained semi-Markov decision problem with an uncountable state space. We develop efficient algorithms to find the optimal update policy among all causal policies and establish sufficient and necessary conditions for the optimality of the zero-wait policy. Our investigation shows that the zero-wait policy is far from the optimum if: 1) the age penalty function grows quickly with respect to the age; 2) the packet transmission times over the channel are positively correlated over time; or 3) the packet transmission times are highly random (e.g., following a heavy-tail distribution).
Subject Keywords
Terms Age-of-information
,
Status information update
,
Constrained semi-Markov decision process
,
Date freshness
URI
https://hdl.handle.net/11511/35629
Journal
IEEE TRANSACTIONS ON INFORMATION THEORY
DOI
https://doi.org/10.1109/tit.2017.2735804
Collections
Department of Electrical and Electronics Engineering, Article
Suggestions
OpenMETU
Core
QUERY AGE OF INFORMATION IN COMMUNICATION NETWORKS
Ildız, Muhammed Emrullah; Uysal, Elif; Department of Electrical and Electronics Engineering (2002-8-22)
We study a pull-based status update communication model where a source node submits update packets to a channel with random transmission delay, at times requested by a remote destination node. The objective is to minimize the average query-age-of-information (QAoI), defined as the age of information (AoI) measured at query instants that occur at the destination side according to a stochastic arrival process. In reference to a push-based problem formulation defined in the literature where the source decides ...
An Inequality for Query Age of Information and Age of Information Sorgu Ani Bilgi Yaşi (QAoI) ve Ortalama Bilgi Yaşi (AoI) Arasinda bir Eşitsizlik
Ildiz, M. Emrullah; Avsar, Semanur; Uysal, Elif (2022-01-01)
We study a status update system where a destination node requests from a source node to submit update packets to a channel. The update packets incur a constant transmission delay in the channel. The update packets sent from the source node will be utilized by the destination node at certain query instants generated toward a computation. The query instants are modeled as a stochastic arrival process. The Age of Information (AoI) at the query instants is called as the Query Age of Information (QAoI). The pull...
Optimizing Information Freshness in Random Access Channels
Yavaşcan, Orhan Tahir; Uysal, Elif; Department of Electrical and Electronics Engineering (2022-8-31)
In this work, a number of transmission strategies aimed at optimizing information freshness in random access channels are developed and studied. Threshold-ALOHA, an age-aware modification of slotted ALOHA, suggests a fixed age threshold on the terminals before they can become active and attempt transmissions with a constant probability. Threshold ALOHA nearly halves the average Age of Information (AoI) whilst the loss of throughput compared to slotted ALOHA is less than one percent. Mumista, multiple mini s...
Age-Optimal Updates of Multiple Information Flows
Sun, Yin; Uysal, Elif; Kompella, Sastry (2018-04-19)
In this paper, we study an age of information minimization problem, where multiple flows of update packets are sent over multiple servers to their destinations. Two online scheduling policies are proposed. When the packet generation and arrival times are synchronized across the flows, the proposed policies are shown to be (near) optimal for minimizing any time-dependent, symmetric, and non-decreasing penalty function of the ages of the flows over time in a stochastic ordering sense.
Delay and Peak-Age Violation Probability in Short-Packet Transmissions
Devassy, Rahul; Durisi, Giuseppe; Ferrante, Guido Carlo; Simeone, Osvaldo; Uysal, Elif (2018-06-22)
This paper investigates the distribution of delay and peak age of information in a communication system where packets, generated according to an independent and identically distributed Bernoulli process, are placed in a single-server queue with first-come first-served discipline and transmitted over an additive white Gaussian noise (AWGN) channel. When a packet is correctly decoded, the sender receives an instantaneous error-free positive acknowledgment, upon which it removes the packet from the buffer. In ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Y. Sun, E. Uysal, R. D. Yates, C. E. Koksal, and N. B. Shroff, “Update or Wait: How to Keep Your Data Fresh,”
IEEE TRANSACTIONS ON INFORMATION THEORY
, pp. 7492–7508, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35629.