Many-to-Many Matching Games for Proactive Social-Caching in Wireless Small Cell Networks

In this paper, we address the caching problem in small cell networks from a game theoretic point of view. In particular, we formulate the caching problem as a many-to-many matching game between small base stations and service providers' servers. The servers store a set of videos and aim to cache these videos at the small base stations in order to reduce the experienced delay by the end-users. On the other hand, small base stations cache the videos according to their local popularity, so as to reduce the load on the backhaul links. We propose a new matching algorithm for the many-to-many problem and prove that it reaches a pairwise stable outcome. Simulation results show that the number of satisfied requests by the small base stations in the proposed caching algorithm can reach up to three times the satisfaction of a random caching policy. Moreover, the expected download time of all the videos can be reduced significantly

Modelling contents status for IPTV delivery networks

Since IPTV has been invented, IPTV is considered a dominant technology to distribute high quality videos and live channels anytime anywhere over challenging environment to end users who are having different preferences and demands. Presently, IPTV service providers manage IPTV delivery networks, in terms of contents, channels, resources, based on contents popularity distribution and/or users’ preferences only. Although content popularity and users’ preferences play an important role to cope with the increasing demand of IPTV contents/channels, these two measures fail in producing efficient IPTV delivery networks For that, IPTV delivery network designing should integrate the IPTV content characteristics like size, interactivity, the rapid changing lifetime. Therefore, the idea of this paper is to build a mathematical model that integrates all these factors in one concept called IPTV content status. Modeling the contents status according to its characteristics is an important point to design Content-Aware IPTV delivery networks.The experimental results showed the superiority of modeling IPTV content status in balancing the load and reducing the resources waste

Content-aware resource allocation model for IPTV delivery networks

Nowadays, with the evolution of digital video broadcasting, as well as, the advent of high speed broadband networks, a new era of TV services has emerged known as IPTV. IPTV is a system that employs the high speed broadband networks to deliver TV services to the subscribers. From the service provider viewpoint, the challenge in IPTV systems is how to build delivery networks that exploits the resources efficiently and reduces the service cost, as well. However, designing such delivery networks affected by many factors including choosing the suitable network architecture, load balancing, resources waste, and cost reduction. Furthermore, IPTV contents characteristics, particularly; size, popularity, and interactivity play an important role in balancing the load and avoiding the resources waste for delivery networks. In this paper, we investigate the problem of resource allocation for IPTV delivery networks over the recent architecture, peer-service area architecture. The Genetic Algorithm as an optimization tool has been used to find the optimal provisioning parameters including storage, bandwidth, and CPU consumption. The experiments have been conducted on two data sets with different popularity distributions. The experiments have been conducted on two popularity distributions. The experimental results showed the impact of content status on the resource allocation process