Architecture for Cooperative Prefetching in P2P Video-on- Demand System

Most P2P VoD schemes focused on service architectures and overlays optimization without considering segments rarity and the performance of prefetching strategies. As a result, they cannot better support VCRoriented service in heterogeneous environment having clients using free VCR controls. Despite the remarkable popularity in VoD systems, there exist no prior work that studies the performance gap between different prefetching strategies. In this paper, we analyze and understand the performance of different prefetching strategies. Our analytical characterization brings us not only a better understanding of several fundamental tradeoffs in prefetching strategies, but also important insights on the design of P2P VoD system. On the basis of this analysis, we finally proposed a cooperative prefetching strategy called "cooching". In this strategy, the requested segments in VCR interactivities are prefetched into session beforehand using the information collected through gossips. We evaluate our strategy through extensive simulations. The results indicate that the proposed strategy outperforms the existing prefetching mechanisms.Comment: 13 Pages, IJCN

Insights from Analysis of Video Streaming Data to Improve Resource Management

Today a large portion of Internet traffic is video. Over The Top (OTT) service providers offer video streaming services by creating a large distributed cloud network on top of a physical infrastructure owned by multiple entities. Our study explores insights from video streaming activity by analyzing data collected from Korea's largest OTT service provider. Our analysis of nationwide data shows interesting characteristics of video streaming such as correlation between user profile information (e.g., age, sex) and viewing habits, viewing habits of users (when do the users watch? using which devices?), viewing patterns (early leaving viewer vs. steady viewer), etc. Video on Demand (VoD) streaming involves costly (and often limited) compute, storage, and network resources. Findings from our study will be beneficial for OTTs, Content Delivery Networks (CDNs), Internet Service Providers (ISPs), and Carrier Network Operators, to improve their resource allocation and management techniques.Comment: This is a preprint electronic version of the article accepted to IEEE CloudNet 201

User producer interaction in context: a classification

Science, Technology and Innovation Studies show that intensified user producer interaction (UPI) increases chances for successful innovations, especially in the case of emerging technology. It is not always clear, however, what type of interaction is necessary in a particular context. This paper proposes a conceptualization of contexts in terms of three dimensions – the phase of technology development, the flexibility of the technology, and the heterogeneity of user populations – resulting in a classification scheme with eight different contextual situations. The paper identifies and classifies types of interaction, like demand articulation, interactive learning, learning by using and domestication. It appears that each contextual situation demands a different set of UPI types. To illustrate the potential value of the classification scheme, four examples of innovations with varying technological and user characteristics are explored: the refrigerator, clinical anaesthesia, video cassette recording, and the bicycle. For each example the relevant UPI types are discussed and it is shown how these types highlight certain activities and interactions during key events of innovation processes. Finally, some directions for further research are suggested alongside a number of comments on the utility of the classification