research-article

Minimizing the Age of Information in broadcast wireless networks

Authors:

Elif Uysal-Biyikoglu,

Eytan ModianoAuthors Info & Claims

2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

Pages 844 - 851

https://doi.org/10.1109/ALLERTON.2016.7852321

Published: 27 September 2016 Publication History

Abstract

We consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients. The Age of Information (AoI), namely the amount of time that elapsed since the most recently delivered packet was generated, captures the freshness of the information. We formulate a discrete-time decision problem to find a scheduling policy that minimizes the expected weighted sum AoI of the clients in the network. To the best of our knowledge, this is the first work to provide a scheduling policy that optimizes AoI in a wireless network with unreliable channels. The results are twofold: first, we show that a Greedy Policy, which transmits the packet with highest current age, is optimal for the case of symmetric networks. Then, for the general network case, we establish that the problem is indexable and obtain the Whittle Index in closed-form. Numerical results are presented to demonstrate the performance of the policies.

References

[1]

S. Kaul, R. Yates, and M. Gruteser, “Real-time status: How often should one update?” in Proceedings of IEEE INFOCOM mini-conference, 2012.

[2]

L. Huang and E. Modiano, “Optimizing age-of-information in a multi-class queueing system”, in IEEE International Symposium on Information Theory (ISIT), 2015.

[3]

M. Costa, M. Codreanu, and A. Ephremides, “On the age of information in status update systems with packet management”, IEEE Transactions on Information Theory, vol. 62, no. 4, Apr. 2016.

[4]

B. T. Bacinoglu, E. T. Ceran, and E. Uysal-Biyikoglu, “Age of information under energy replenishment constraints”, in Information Theory and Applications Workshop at UCSD, 2015.

[5]

Y. Sun, E. Uysal-Biyikoglu, R. Yates, C. E. Koksal, and N. Shroff, “Update or wait: How to keep your data fresh”, in Proceedings of IEEE INFOCOM, 2016.

[6]

Q. He, D. Yuan, and A. Ephremides, “Optimizing freshness of information: On minimum age link scheduling in wireless systems”, in International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, May 2016, pp. 1–8.

[7]

P. P. Bhattacharya and A. Ephremides, “Optimal scheduling with strict deadlines”, IEEE Transactions on Automatic Control, vol. 34, pp. 721–728, July 1989.

[8]

I.-H. Hou, V. Borkar, and P. R. Kumar, “A theory of QoS for wireless”, in Proceedings of IEEEINFOCOM, Apr. 2009, pp. 486–494.

[9]

K. S. Kim, C.-P. Li, I. Kadota, and E. Modiano, “Optimal scheduling of real-time traffic in wireless networks with delayed feedback”, in Proceedings of IEEE Allerton Conference on Communication, Control and Computing, Oct. 2015, pp. 1143–1149.

[10]

V. Raghunathan, V. Borkar, M. Cao, and P. R. Kumar, “Index policies for real-time multicast scheduling for wireless broadcast systems”, in Proceedings of IEEE INFOCOM, Apr. 2008.

[11]

B. Li, R. Li, and A. Eryilmaz, “Throughput-optimal scheduling design with regular service guarantees in wireless networks” IEEE/ACM Transactions on Networking, vol. 23, no. 5, pp. 1542–1552, Oct. 2015.

Digital Library

[12]

R. Singh, X. Guo, and P. Kumar, “Index policies for optimal mean-variance trade-off of inter-delivery times in real-time sensor networks”, in Proceedings of IEEE INFOCOM, Jan. 2015.

[13]

D. Stoyan, Comparison Methods for Queues and Other Stochastic Models, ser. Wiley Series in Probability and Statistics. Wiley, 1983.

[14]

A. Ganti, E. Modiano, and J. N. Tsitsiklis, “Optimal transmission scheduling in symmetric communication models with intermittent connectivity”, IEEE Transactions on Information Theory, vol. 53, no. 3, Mar. 2007.

[15]

D. Bertsekas, Dynamic Programming and Optimal Control, 3rd ed. Athena Scientific 2005, vol. 1.

[16]

P. Whittle, “Restless bandits: Activity allocation in a changing world”, Journal of Applied Probability, vol. 25, pp. 287–298, 1988.

[17]

P. Mansourifard, T. Javidi, and B. Krishnamachari, “Optimality of myopic policy for a class of monotone affine restless multi-armed bandits”, in Proceedings of IEEE Conference on Decision and Control, Dec. 2012, pp. 877–882.

[18]

K. Liu and Q. Zhao, “Indexability of restless bandit problems and optimality of whittle index for dynamic multichannel access”, IEEE Transactions on Information Theory, vol. 56, pp. 5547–5567, Nov. 2010.

Digital Library

[19]

R. R. Weber and G. Weiss, “On an index policy for restless bandits”, Journal of Applied Probability, vol. 27, no. 3, pp. 637–648, 1990.

[20]

J. Gittins, K. Glazebrook, and R. Weber, Multi-armed Bandit Allocation Indices, 2nd ed. Wiley, Mar. 2011.

Cited By

Danassis PVerma SKillian JTaneja ATambe MElkind E(2023)Limited resource allocation in a non-Markovian worldProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/660(5950-5958)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/660

Index Terms

Minimizing the Age of Information in broadcast wireless networks
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
      1. Scheduling algorithms
    2. Online algorithms
      1. Online learning algorithms
        Scheduling algorithms
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning
        Sequential decision making

Index terms have been assigned to the content through auto-classification.

Recommendations

Scheduling Policies for Minimizing Age of Information in Broadcast Wireless Networks

In this paper, we consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients through unreliable channels. The Age of Information AoI, namely the amount of time that elapsed since the most recently ...
Broadcast Analysis for Extended Cooperative Wireless Networks

The capability of nodes to broadcast their message to the entire wireless network when nodes employ cooperation is considered. We employ an asymptotic analysis using an extended random network setting under an additive white Gaussian channel model with ...
Minimizing the Age of Information in Wireless Networks with Stochastic Arrivals
Mobihoc '19: Proceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing

We consider a wireless network with a base station serving multiple traffic streams to different destinations. Packets from each stream arrive to the base station according to a stochastic process and are enqueued in a separate (per stream) queue. The ...

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings

2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

Sep 2016

1347 pages

Copyright © 2016.

Publisher

IEEE Press

Publication History

Published: 27 September 2016

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Danassis PVerma SKillian JTaneja ATambe MElkind E(2023)Limited resource allocation in a non-Markovian worldProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/660(5950-5958)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/660

View Options

View options

Figures

Tables

Media

View Table of Conten