Content Placement Learning for Success Probability Maximization in Wireless Edge Caching Networks

Navneet Garg; Mathini Sellathurai; Tharmalingam Ratnarajah

doi:10.1109/ICASSP.2019.8682841

Content Placement Learning for Success Probability Maximization in Wireless Edge Caching Networks

Navneet Garg, Mathini Sellathurai, Tharmalingam Ratnarajah

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

36 Downloads (Pure)

Abstract

To meet increasing demands of wireless multimedia communications, caching of important contents in advance is one of the key solutions. Optimal caching depends on content popularity in future which is unknown in advance. In this paper, modeling content popularity as a finite state Markov chain, reinforcement Q-learning is employed to learn optimal content placement strategy in homogeneous Poisson point process (PPP) distributed caching network. Given a set of available placement strategies, simulations show that the presented framework successfully learns and provides the best content placement to maximize the average success probability.

Original language	English
Title of host publication	2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Publisher	IEEE
Pages	3092-3096
Number of pages	5
ISBN (Electronic)	9781479981311
DOIs	https://doi.org/10.1109/ICASSP.2019.8682841
Publication status	Published - 17 Apr 2019
Event	44th IEEE International Conference on Acoustics, Speech, and Signal Processing 2019 - Brighton, United Kingdom Duration: 12 May 2019 → 17 May 2019

Publication series

Name	IEEE International Conference on Acoustics, Speech, and Signal Processing
ISSN (Electronic)	2379-190X

Conference

Conference	44th IEEE International Conference on Acoustics, Speech, and Signal Processing 2019
Abbreviated title	ICASSP 2019
Country/Territory	United Kingdom
City	Brighton
Period	12/05/19 → 17/05/19

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.2019.8682841

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Garg, N., Sellathurai, M., & Ratnarajah, T. (2019). Content Placement Learning for Success Probability Maximization in Wireless Edge Caching Networks. In 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (pp. 3092-3096). (IEEE International Conference on Acoustics, Speech, and Signal Processing). IEEE. https://doi.org/10.1109/ICASSP.2019.8682841

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title = "Content Placement Learning for Success Probability Maximization in Wireless Edge Caching Networks",

abstract = "To meet increasing demands of wireless multimedia communications, caching of important contents in advance is one of the key solutions. Optimal caching depends on content popularity in future which is unknown in advance. In this paper, modeling content popularity as a finite state Markov chain, reinforcement Q-learning is employed to learn optimal content placement strategy in homogeneous Poisson point process (PPP) distributed caching network. Given a set of available placement strategies, simulations show that the presented framework successfully learns and provides the best content placement to maximize the average success probability.",

author = "Navneet Garg and Mathini Sellathurai and Tharmalingam Ratnarajah",

year = "2019",

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doi = "10.1109/ICASSP.2019.8682841",

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booktitle = "2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)",

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note = "44th IEEE International Conference on Acoustics, Speech, and Signal Processing 2019, ICASSP 2019 ; Conference date: 12-05-2019 Through 17-05-2019",

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Garg, N, Sellathurai, M & Ratnarajah, T 2019, Content Placement Learning for Success Probability Maximization in Wireless Edge Caching Networks. in 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, pp. 3092-3096, 44th IEEE International Conference on Acoustics, Speech, and Signal Processing 2019, Brighton, United Kingdom, 12/05/19. https://doi.org/10.1109/ICASSP.2019.8682841

Content Placement Learning for Success Probability Maximization in Wireless Edge Caching Networks. / Garg, Navneet; Sellathurai, Mathini; Ratnarajah, Tharmalingam.
2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE, 2019. p. 3092-3096 (IEEE International Conference on Acoustics, Speech, and Signal Processing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Sellathurai, Mathini

AU - Ratnarajah, Tharmalingam

PY - 2019/4/17

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N2 - To meet increasing demands of wireless multimedia communications, caching of important contents in advance is one of the key solutions. Optimal caching depends on content popularity in future which is unknown in advance. In this paper, modeling content popularity as a finite state Markov chain, reinforcement Q-learning is employed to learn optimal content placement strategy in homogeneous Poisson point process (PPP) distributed caching network. Given a set of available placement strategies, simulations show that the presented framework successfully learns and provides the best content placement to maximize the average success probability.

AB - To meet increasing demands of wireless multimedia communications, caching of important contents in advance is one of the key solutions. Optimal caching depends on content popularity in future which is unknown in advance. In this paper, modeling content popularity as a finite state Markov chain, reinforcement Q-learning is employed to learn optimal content placement strategy in homogeneous Poisson point process (PPP) distributed caching network. Given a set of available placement strategies, simulations show that the presented framework successfully learns and provides the best content placement to maximize the average success probability.

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Content Placement Learning for Success Probability Maximization in Wireless Edge Caching Networks

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