Modelling and Predicting the Data Availability in Decentralized Online Social Networks

2014 ◽  
Author(s):  
Songling Fu ◽  
Ligang He ◽  
Xiangke Liao ◽  
Chenlin Huang ◽  
Kenli Li ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Data Availability ◽  
Decentralized Online Social Networks

scholarly journals Analyzing the Impact of Storage Shortage on Data Availability in Decentralized Online Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Songling Fu ◽  
Ligang He ◽  
Xiangke Liao ◽  
Kenli Li ◽  
Chenlin Huang
Keyword(s):  
Social Networks ◽  
Mobile Devices ◽  
Online Social Networks ◽  
Storage Capacity ◽  
Data Availability ◽  
Novel Method ◽  
Smart Mobile ◽  
The Impact ◽  
Availability Model ◽  
Decentralized Online Social Networks

Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs). The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today’s online social networks (OSNs) due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction.

Analyzing and Boosting the Data Availability in Decentralized Online Social Networks

2015 ◽  
Vol 12 (2) ◽  
pp. 47-72
Author(s):  
Songling Fu ◽  
Ligang He ◽  
Xiangke Liao ◽  
Chenlin Huang ◽  
Kenli Li ◽  
...  
Keyword(s):  
Social Networks ◽  
Quantitative Analysis ◽  
Online Social Networks ◽  
Storage Capacity ◽  
Critical Factor ◽  
Data Availability ◽  
Simulation Experiments ◽  
Extensive Simulation ◽  
Novel Method ◽  
Decentralized Online Social Networks

Maintaining Data Availability (DA) is a big challenge in Decentralized Online Social Networks (DOSN). Nowadays, the limitation of the storage capacity in DOSN becomes a critical factor that jeopardizes the DA. Therefore, it is desired to determine the relation between the storage capacity of DOSN and the level of DA, and develop an approach to mitigating the limitation of storage capacity. This paper addresses these issues. In this paper, a probabilistic DA model over storage capacity is established. A novel method is then proposed to predict the DA on the fly. Further, a Cloud-assisted DOSN (CDOSN) framework is proposed to enhance the storage capacity and the DA in DOSN. This paper conducts the detailed quantitative analysis about the storage capacity and the DA in CDOSN. Extensive simulation experiments have been conducted to evaluate the effectiveness of the DA model, the on-the-fly prediction and the CDOSN framework.

scholarly journals Decentralized Online Social Networks

2010 ◽  
pp. 349-378 ◽  
Author(s):  
Anwitaman Datta ◽  
Sonja Buchegger ◽  
Le-Hung Vu ◽  
Thorsten Strufe ◽  
Krzysztof Rzadca
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Decentralized Online Social Networks

scholarly journals Modeling geo-homopholy in online social networks for population distribution projection

2017 ◽  
Vol 1 (3) ◽  
pp. 249-269 ◽  
Author(s):  
Yuanxing Zhang ◽  
Zhuqi Li ◽  
Kaigui Bian ◽  
Yichong Bai ◽  
Zhi Yang ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Dirichlet Process ◽  
Prediction Models ◽  
Population Distribution ◽  
Data Availability ◽  
Floating Population ◽  
Trajectory Data ◽  
Content Type ◽  
Geographical Regions

Purpose Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks. Design/methodology/approach In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions. Findings By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time. Originality/value This paper tries to project population distribution by modeling geo-homophily in OSNs.

scholarly journals Data availability improvement in peer-to-peer online social networks

2020 ◽  
Vol 14 (3) ◽  
pp. 332-341
Author(s):  
Fariba Khazaei Koohpar ◽  
Afsaneh Fatemi ◽  
Fatemeh Raji
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Peer To Peer ◽  
Data Availability
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