Wireless Edge Caching for Mobile Social Networks

Saputra, Y; Dinh, H; Nguyen, D; Dutkiewicz, E; Niyato, D

Wireless Edge Caching for Mobile Social Networks

Saputra, Y

Dinh, H

Nguyen, D

Dutkiewicz, E

Niyato, D

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Publisher:: Cambridge University Press
Publication Type:: Chapter
Citation:: Wireless Edge Caching Modeling, Analysis, and Optimization, 2020, pp. 146-172
Issue Date:: 2020-10-01

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Field	Value	Language
dc.contributor.author	Saputra, Y https://orcid.org/0000-0001-8862-2004
dc.contributor.author	Dinh, H https://orcid.org/0000-0002-9528-0863
dc.contributor.author	Nguyen, D https://orcid.org/0000-0003-2659-8648
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286
dc.contributor.author	Niyato, D
dc.contributor.editor	Vu, T
dc.contributor.editor	Chatzinotas, S
dc.contributor.editor	Baştuğ, E
dc.contributor.editor	Quek, TQS
dc.date.accessioned	2021-02-28T04:26:11Z
dc.date.available	2021-02-28T04:26:11Z
dc.date.issued	2020-10-01
dc.identifier.citation	Wireless Edge Caching Modeling, Analysis, and Optimization, 2020, pp. 146-172
dc.identifier.isbn	9781108480833
dc.identifier.uri	http://hdl.handle.net/10453/146523
dc.description.abstract	Wireless edge caching for mobile social networks (MSNs) has emerged as one of the prospective solutions to provide reliable and low-latency communication services for mobile users on social networking. In this chapter, we first give an overview of MSNs, including their development and challenges. We then discuss mobile edge caching (MEC) paradigms to address emerging issues for MSNs, e.g., service delay, users’ experience, and economic efficiency. In addition to the advantages, the development of MEC networks also places some key challenges’ such as hierarchical architecture of MEC networks, proactive caching, privacy, and security issues. The framework can authenticate MSN users based on public-key cryptography and predict their content demands utilizing a matrix factorization method. Based on the prediction, an optimal content caching policy for an MEC node is presented to minimize the average latency of all MSN users under the MEC nodes’ storage capacity constraints. Furthermore, this framework provides an optimal business model to maximize the revenue for MSN service providers based on the demands of the MSN users and the obtained optimal caching policy.
dc.format.extent	19
dc.language	en
dc.publisher	Cambridge University Press
dc.relation.ispartof	Wireless Edge Caching Modeling, Analysis, and Optimization
dc.relation.isbasedon	10.1017/9781108691277.009
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	Wireless Edge Caching for Mobile Social Networks
dc.type	Chapter
utslib.for	0805 Distributed Computing
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	recently_added	*
pubs.consider-herdc	true
dc.date.updated	2021-02-28T04:26:10Z
pubs.place-of-publication	UK
pubs.publication-status	Published online
dc.location	UK

Abstract:

Wireless edge caching for mobile social networks (MSNs) has emerged as one of the prospective solutions to provide reliable and low-latency communication services for mobile users on social networking. In this chapter, we first give an overview of MSNs, including their development and challenges. We then discuss mobile edge caching (MEC) paradigms to address emerging issues for MSNs, e.g., service delay, users’ experience, and economic efficiency. In addition to the advantages, the development of MEC networks also places some key challenges’ such as hierarchical architecture of MEC networks, proactive caching, privacy, and security issues. The framework can authenticate MSN users based on public-key cryptography and predict their content demands utilizing a matrix factorization method. Based on the prediction, an optimal content caching policy for an MEC node is presented to minimize the average latency of all MSN users under the MEC nodes’ storage capacity constraints. Furthermore, this framework provides an optimal business model to maximize the revenue for MSN service providers based on the demands of the MSN users and the obtained optimal caching policy.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/146523