How to identify global trends from local decisions? Event region detection on mobile networks

Andreas Loukas; Marco Zuniga; Ioannis Protonotarios; Jie Gao

doi:10.1109/INFOCOM.2014.6848049

How to identify global trends from local decisions? Event region detection on mobile networks

Andreas Loukas
, Marco Zuniga
, Ioannis Protonotarios
, Jie Gao

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

16 Scopus citations

Abstract

The decentralized detection of event regions is a fundamental building block for monitoring and reasoning about spatial phenomena. However, so far the problem has been studied almost exclusively for static networks. This study proposes a theoretical framework with which we can analyze event detection algorithms suitable for large-scale mobile networks. Our analysis builds on the following insight: the inherent trends of spatial events are well captured by the spectral domain of the network graph. Using this framework, we propose novel local algorithms that are location-free; that work with mobile nodes and dynamic events; that operate on 3D topologies; and that are simple to implement. We are not aware of event detection algorithms possessing all these traits. Simulations based on complex oil spill traces showcase the resilience and robustness of our methods. Additionally, we demonstrate their validity for practical scenarios by evaluating them on a 105 node testbed.

Original language	English
Title of host publication	IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
Publisher	Institute of Electrical and Electronics Engineers
Pages	1177-1185
Number of pages	9
ISBN (Print)	9781479933600
DOIs	https://doi.org/10.1109/INFOCOM.2014.6848049
State	Published - 1 Jan 2014
Externally published	Yes
Event	33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014 - Toronto, ON, Canada Duration: 27 Apr 2014 → 2 May 2014

Publication series

Name	Proceedings - IEEE INFOCOM
ISSN (Print)	0743-166X

Conference

Conference	33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
Country/Territory	Canada
City	Toronto, ON
Period	27/04/14 → 2/05/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 14 Life Below Water

ASJC Scopus subject areas

General Computer Science
Electrical and Electronic Engineering

Access to Document

10.1109/INFOCOM.2014.6848049

Cite this

Loukas, A., Zuniga, M., Protonotarios, I., & Gao, J. (2014). How to identify global trends from local decisions? Event region detection on mobile networks. In IEEE INFOCOM 2014 - IEEE Conference on Computer Communications (pp. 1177-1185). Article 6848049 (Proceedings - IEEE INFOCOM). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/INFOCOM.2014.6848049

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abstract = "The decentralized detection of event regions is a fundamental building block for monitoring and reasoning about spatial phenomena. However, so far the problem has been studied almost exclusively for static networks. This study proposes a theoretical framework with which we can analyze event detection algorithms suitable for large-scale mobile networks. Our analysis builds on the following insight: the inherent trends of spatial events are well captured by the spectral domain of the network graph. Using this framework, we propose novel local algorithms that are location-free; that work with mobile nodes and dynamic events; that operate on 3D topologies; and that are simple to implement. We are not aware of event detection algorithms possessing all these traits. Simulations based on complex oil spill traces showcase the resilience and robustness of our methods. Additionally, we demonstrate their validity for practical scenarios by evaluating them on a 105 node testbed.",

author = "Andreas Loukas and Marco Zuniga and Ioannis Protonotarios and Jie Gao",

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Loukas, A, Zuniga, M, Protonotarios, I & Gao, J 2014, How to identify global trends from local decisions? Event region detection on mobile networks. in IEEE INFOCOM 2014 - IEEE Conference on Computer Communications., 6848049, Proceedings - IEEE INFOCOM, Institute of Electrical and Electronics Engineers, pp. 1177-1185, 33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014, Toronto, ON, Canada, 27/04/14. https://doi.org/10.1109/INFOCOM.2014.6848049

How to identify global trends from local decisions? Event region detection on mobile networks. / Loukas, Andreas; Zuniga, Marco; Protonotarios, Ioannis et al.
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers, 2014. p. 1177-1185 6848049 (Proceedings - IEEE INFOCOM).

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

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AB - The decentralized detection of event regions is a fundamental building block for monitoring and reasoning about spatial phenomena. However, so far the problem has been studied almost exclusively for static networks. This study proposes a theoretical framework with which we can analyze event detection algorithms suitable for large-scale mobile networks. Our analysis builds on the following insight: the inherent trends of spatial events are well captured by the spectral domain of the network graph. Using this framework, we propose novel local algorithms that are location-free; that work with mobile nodes and dynamic events; that operate on 3D topologies; and that are simple to implement. We are not aware of event detection algorithms possessing all these traits. Simulations based on complex oil spill traces showcase the resilience and robustness of our methods. Additionally, we demonstrate their validity for practical scenarios by evaluating them on a 105 node testbed.

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How to identify global trends from local decisions? Event region detection on mobile networks

Abstract

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Conference

UN SDGs

ASJC Scopus subject areas

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