Identifying Propagation Sources in Networks: State-of-the-Art and Comparative Studies

Jiang, J; Wen, S; Yu, S; Xiang, Y; Zhou, W

Identifying Propagation Sources in Networks: State-of-the-Art and Comparative Studies

Jiang, J Wen, S Yu, S

Xiang, Y Zhou, W

Permalink

Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Communications Surveys and Tutorials, 2017, 19, (1), pp. 465-481
Issue Date:: 2017-01-01

Closed Access

	Filename	Description	Size
	Identifying_Propagation_Sources_in_Networks_State-of-the-Art_and_Comparative_Studies.pdf		3.59 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Jiang, J
dc.contributor.author	Wen, S
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.contributor.author	Xiang, Y
dc.contributor.author	Zhou, W https://orcid.org/0000-0002-1680-2521
dc.date.accessioned	2022-07-28T03:35:43Z
dc.date.available	2022-07-28T03:35:43Z
dc.date.issued	2017-01-01
dc.identifier.citation	IEEE Communications Surveys and Tutorials, 2017, 19, (1), pp. 465-481
dc.identifier.issn	1553-877X
dc.identifier.issn	1553-877X
dc.identifier.uri	http://hdl.handle.net/10453/159280
dc.description.abstract	It has long been a significant but difficult problem to identify propagation sources based on limited knowledge of network structures and the varying states of network nodes. In practice, real cases can be locating the sources of rumors in online social networks and finding origins of a rolling blackout in smart grids. This paper reviews the state-of-the-art in source identification techniques and discusses the pros and cons of current methods in this field. Furthermore, in order to gain a quantitative understanding of current methods, we provide a series of experiments and comparisons based on various environment settings. Especially, our observation reveals considerable differences in performance by employing different network topologies, various propagation schemes, and diverse propagation probabilities. We therefore reach the following points for future work. First, current methods remain far from practice as their accuracy in terms of error distance (δ) is normally larger than three in most scenarios. Second, the majority of current methods are too time consuming to quickly locate the origins of propagation. In addition, we list five open issues of current methods exposed by the analysis, from the perspectives of topology, number of sources, number of networks, temporal dynamics, and complexity and scalability. Solutions to these open issues are of great academic and practical significance.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Communications Surveys and Tutorials
dc.relation.isbasedon	10.1109/COMST.2016.2615098
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.title	Identifying Propagation Sources in Networks: State-of-the-Art and Comparative Studies
dc.type	Journal Article
utslib.citation.volume	19
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-07-28T03:35:42Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	19
utslib.citation.issue	1

Abstract:

It has long been a significant but difficult problem to identify propagation sources based on limited knowledge of network structures and the varying states of network nodes. In practice, real cases can be locating the sources of rumors in online social networks and finding origins of a rolling blackout in smart grids. This paper reviews the state-of-the-art in source identification techniques and discusses the pros and cons of current methods in this field. Furthermore, in order to gain a quantitative understanding of current methods, we provide a series of experiments and comparisons based on various environment settings. Especially, our observation reveals considerable differences in performance by employing different network topologies, various propagation schemes, and diverse propagation probabilities. We therefore reach the following points for future work. First, current methods remain far from practice as their accuracy in terms of error distance (δ) is normally larger than three in most scenarios. Second, the majority of current methods are too time consuming to quickly locate the origins of propagation. In addition, we list five open issues of current methods exposed by the analysis, from the perspectives of topology, number of sources, number of networks, temporal dynamics, and complexity and scalability. Solutions to these open issues are of great academic and practical significance.

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

http://hdl.handle.net/10453/159280