38 research outputs found
Co-evolution of Content Popularity and Delivery in Mobile P2P Networks
Mobile P2P technology provides a scalable approach to content delivery to a
large number of users on their mobile devices. In this work, we study the
dissemination of a \emph{single} content (e.g., an item of news, a song or a
video clip) among a population of mobile nodes. Each node in the population is
either a \emph{destination} (interested in the content) or a potential
\emph{relay} (not yet interested in the content). There is an interest
evolution process by which nodes not yet interested in the content (i.e.,
relays) can become interested (i.e., become destinations) on learning about the
popularity of the content (i.e., the number of already interested nodes). In
our work, the interest in the content evolves under the \emph{linear threshold
model}. The content is copied between nodes when they make random contact. For
this we employ a controlled epidemic spread model. We model the joint evolution
of the copying process and the interest evolution process, and derive the joint
fluid limit ordinary differential equations. We then study the selection of the
parameters under the content provider's control, for the optimization of
various objective functions that aim at maximizing content popularity and
efficient content delivery.Comment: 21 pages, 16 figure
Modeling and Analysis of Scholar Mobility on Scientific Landscape
Scientific literature till date can be thought of as a partially revealed
landscape, where scholars continue to unveil hidden knowledge by exploring
novel research topics. How do scholars explore the scientific landscape , i.e.,
choose research topics to work on? We propose an agent-based model of topic
mobility behavior where scholars migrate across research topics on the space of
science following different strategies, seeking different utilities. We use
this model to study whether strategies widely used in current scientific
community can provide a balance between individual scientific success and the
efficiency and diversity of the whole academic society. Through extensive
simulations, we provide insights into the roles of different strategies, such
as choosing topics according to research potential or the popularity. Our model
provides a conceptual framework and a computational approach to analyze
scholars' behavior and its impact on scientific production. We also discuss how
such an agent-based modeling approach can be integrated with big real-world
scholarly data.Comment: To appear in BigScholar, WWW 201
Competition Over Timeline in Social Networks
International audienceSocial networking sites pervade the World Wide Web and have millions of users worldwide. This provides ample opportunity for brands and organisations to reach out to a large and diverse audience. They do so by creating content and spreading it across the social network. Most popular social networks follow a timeline based homepage to display such content to the end users. Content once posted on the timeline, remains visible for a limited time, determined by the rate of content generation in the network. There are various ways by which brands can become more visible on the timeline of their followers, for instance by retransmitting/advertising their content from time to time. Hence, with multiple content creators in the network, there is a competition over a user's timeline, which we analyse in this paper. We first characterise the occupancy distribution of a given user's timeline and then use queueing techniques to analyse the period of time a content is present on a given timeline. We then study the competition between different content creators and characterise the equilibrium rate of content generation. We finally provide some numerical results, which provide insights into the effect of various system parameters