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Ensuring Persistent Content in Opportunistic Networks via Stochastic Stability Analysis
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. Tech Univ Munich, Dept Informat, Munich, Germany.ORCID iD: 0000-0002-7654-6742
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.ORCID iD: 0000-0002-2764-8099
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.ORCID iD: 0000-0002-3704-1338
2018 (English)In: ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), ISSN 2376-3639, Vol. 3, no 4, p. 16:1-16:23, article id 16Article in journal (Refereed) Published
Abstract [en]

The emerging device-to-device communication solutions and the abundance of mobile applications and services make opportunistic networking not only a feasible solution but also an important component of future wireless networks. Specifically, the distribution of locally relevant content could be based on the community of mobile users visiting an area, if long-term content survival can be ensured this way. In this article, we establish the conditions of content survival in such opportunistic networks, considering the user mobility patterns, as well as the time users keep forwarding the content, as the controllable system parameter.

We model the content spreading with an epidemic process, and derive a stochastic differential equations based approximation. By means of stability analysis, we determine the necessary user contribution to ensure content survival. We show that the required contribution from the users depends significantly on the size of the population, that users need to redistribute content only in a short period within their stay, and that they can decrease their contribution significantly in crowded areas. Hence, with the appropriate control of the system parameters, opportunistic content sharing can be both reliable and sustainable.

Place, publisher, year, edition, pages
ACM Digital Library, 2018. Vol. 3, no 4, p. 16:1-16:23, article id 16
Keywords [en]
Opportunistic networks, content sharing, mobility, stochastic epidemic modeling, stochastic differential equations, Markov processes, network performance modeling, network performance analysis, mobile ad hoc networks
National Category
Telecommunications
Research subject
Telecommunication
Identifiers
URN: urn:nbn:se:kth:diva-236081DOI: 10.1145/3232161ISI: 000456551400002Scopus ID: 2-s2.0-85074676469OAI: oai:DiVA.org:kth-236081DiVA, id: diva2:1256030
Note

QC 20181016

Available from: 2018-10-15 Created: 2018-10-15 Last updated: 2020-03-09Bibliographically approved
In thesis
1. Performance Analysis of Opportunistic Content Distribution via Data-Driven Mobility Modeling
Open this publication in new window or tab >>Performance Analysis of Opportunistic Content Distribution via Data-Driven Mobility Modeling
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

An opportunistic network is formed by co-located mobile users in order to exchange data via direct wireless links when their devices are within transmission range, without relying on the use of fixed network infrastructure. In this thesis we investigate the capabilities of opportunistic networks and cover two main areas: data-driven modeling of user mobility and analytic performance evaluation of location-aware opportunistic content distribution.

The first part of the thesis focuses on mobility modeling. We collect a dataset of user associations in the wireless network of the KTH Royal Institute of Technology, and characterize the mobility of users in this dataset both from the network and from the user perspective. From the network perspective, we model the aggregate mobility and access patterns to different parts of the network. To characterize individual mobility, we assess how mobile the users are, and how accurately their movements can be predicted in the near future. Based on these findings, and on the analysis of several other mobility traces, we propose a mobility model for populations with churn, that is specifically tailored for the evaluation of opportunistic content distribution. In the second part of the thesis, we evaluate the performance of opportunistic content distribution in ephemeral, location-aware networks where content is stored only on the user devices within the locale of interest. We develop a framework that allows modeling of the spread of information as a stochastic process and accurate capturing of the stochastic fluctuations in the number of distributed content items. We study the feasibility of opportunistic content distribution and, by means of stochastic stability analysis, assess how the system parameters can be engineered to ensure content persistence. We show that the content persistence strongly depends on the density of users, and that the requirements for user resources are relatively low already for moderate densities.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. vi, 61
Series
TRITA-EECS-AVL ; 2018:76
Keywords
Opportunistic communication, mobility, content distribution, network performance modeling, trace-collection analysis, stochastic models.
National Category
Communication Systems Telecommunications
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-236087 (URN)978-91-7729-980-6 (ISBN)
Public defence
2018-11-21, Hörsal F3, Lindstedtsvägen 26, Stockholm, 09:00 (English)
Opponent
Supervisors
Note

QC 20181016

Available from: 2018-10-16 Created: 2018-10-16 Last updated: 2018-10-29Bibliographically approved

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Pajevic, LjubicaFodor, ViktóriaKarlsson, Gunnar

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