IPTV service based on a content-zapping paradigm

Internet protocol television (IPTV) generically designates a real-time distribution service for multimedia contents over an IP network, such as the Internet. There are many advantages of IPTV deployment over current digital or air broadcast TV signals: integration, the use of the switched internet protocol (IP), the possibility to build home networks that can be used to share multimedia contents over different devices, the easy implementation of video on demand services and the usage of better compression and encryption standards. In order to implement this kind of service, it is extremely useful to have a system that can efficiently classify multimedia contents and users and distribute them in a customized way. This paper proposes a novel IPTV service for the distribution of personalized multimedia contents over IP networks based on the concept of content-zapping, in contrast to traditional channel-zapping: each client system receives a multimedia streaming that is automatically composed by the system based on the user preferences and the user will only interact with the system by requesting a content change or marking a content as favorite. The paper will describe the general functionality of the service and will present the detailed architecture of the IPTV server, the key component of the service infrastructure. The server must maintain a list of media contents residing in other systems and must keep a dynamic classification of the multimedia contents that are stored in its database. This classification is built and gradually refined based on the interactions between clients and multimedia contents. Special attention is given in the paper to the classification model, describing the general ideas that are used to automatically suggest multimedia contents to a specific user (that is characterized by his complete profile). A specific content may be suggested to the user based on the knowledge of the user profile and/or based on specific and dynamic information, such as the user position, the local temperature, date and time. The availability of this information obviously depends on the specific user device that is being used. The proposed system allows any client device to connect, allowing a high level of interoperability. It is also possible to use all the device capabilities and sensors, like Global Positioning System (GPS), accelerometers, light sensors, noise sensors, etc., thus creating a context environment that helps classify each user profile. These context-awareness mechanisms applied to mobile devices with wireless network (802.11b/g/n, WiMAX, GSM, UMTS, etc.) capabilities allow a better user experience and more accurate multimedia suggestions, due to the deep knowledge about the user device, network and environment. The system also allows the users to suggest contents to other users in the same “group of friends”. Several performance tests were already conducted and the results obtained show that the proposed system is very stable and fast, even for high increases on the number of users.