Cache content-selection policies for streaming video services

F-FDN: Federation of Fog Computing Systems for Low Latency Video Streaming

“…Due to popularity of the CDN approach in the streaming industry, we consider it in our evaluations. Our simulated CDN consists of a central cloud that holds the same characteristics as the previously described system and CDN servers which have 75% of the requested videos cached, which is a realistic level for CDN caching [21]. As CDNs are located close to viewers, any segments streamed from them have a lower latency compared to the central cloud.…”

“…For that purpose, we vary the number of arriving video segments from 3,000 to 4,500 (with increments of 500) within the same time interval and measure the percentage of video segments that miss their deadlines. In this experiment, FDNbased methods cache 30% and the CDN method caches 75% (for practical reasons [21]) of video segments, while Central Cloud stores all the video contents. Figure 5 demonstrates the performance of different methods as the workload size increases (horizontal axis).…”

Collaborative Cognitive Content Dissemination and Query in Heterogeneous Mobile Opportunistic Networks

“…[9] propose Behave peer-to-peer cache-oriented approach for Web applications that relies on the principles of Behavioural Locality inspired by collaborative filtering but it does not support dynamic mobile user topologies which we do in this paper. [7] proposes a regional caching approach of video content that takes into account content global popularity as well as regional tastes as well. The authors propose a model that captures the overlap between inter-regional and intra-regional preferences.…”

“…We model our collaborative cognitive caching as a bargaining game inspired by heuristic FairCache algorithm [1] and extend it to address real world challenges about the lack of support for dynamic demand matrix, dynamic node availability and congestion identified in [1,7,8,9]. We do this by enabling responsiveness to dynamically changing network topology, congestion avoidance and varying patterns of content publishers/subscribers while allowing low latency content retrieval, high cache efficiency and efficient use of resources.…”

“…the majority of Internet traffic is now dominated by streamed video content [7]) and can lead to surges of traffic if the content becomes popular. While large commercial providers use data centers to hold their data and user population across a very large geo area, and address traffic surges by delegating content distribution to servers located as close as possible to the users [7], we address scenarios which have significantly higher topology dynamics (including potential disconnections) and more dynamic workload patterns (unknown publishers and subscribers distributions). Our aim is to maximise matching of cached content and queries while minimizing latency and avoiding network congestion.…”