6533b854fe1ef96bd12af489

RESEARCH PRODUCT

Evaluation of Structural and Temporal Properties of Ego Networks for Data Availability in DOSNs

Andrea De SalveLaura RicciBarbara Guidi

subject

Computer Networks and CommunicationsComputer scienceCommunity detection; Data availability; DOSN; P2P; Social networks; Temporal affinity; Software; Information Systems; Hardware and Architecture; Computer Networks and CommunicationsControl (management)Information System02 engineering and technologySocial networksField (computer science)Task (project management)Order (exchange)0202 electrical engineering electronic engineering information engineeringDOSNSocial networkStructure (mathematical logic)P2PCommunity detectionSocial networkbusiness.industry020206 networking & telecommunicationsData scienceData availabilityData availabilityHardware and ArchitectureCellular network020201 artificial intelligence & image processingTemporal affinitybusinessSoftwareInformation SystemsComputer network

description

The large diffusion of Online Social Networks (OSNs) has influenced the way people interact with each other. OSNs present several drawbacks, one of the most important is the problem of privacy disclosures. Distributed Online Social Networks (DOSNs) have been proposed as a valid alternative solution to solve this problem. DOSNs are Online Social Networks implemented on a distributed platform, such as a P2P system or a mobile network. However, the decentralization of the control presents several challenges, one of the main ones is guaranteeing data availability without relying on a central server. To this aim, users’ data allocation strategies have to be defined and this requires the knowledge of both structural and temporal characteristics of ego networks which is a difficult task due to the lack of real datasets limiting the research in this field. The goal of this paper is the study of the behaviour of users in a real social network in order to define proper strategies to allocate the users’ data on the DOSN nodes. In particular, we present an analysis of the temporal affinity and the structure of communities and their evolution over the time by using a real Facebook dataset.

yearjournalcountryeditionlanguage
2017-02-25Mobile Networks and Applications
https://doi.org/10.1007/s11036-017-0830-0