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The Video on Demand (VOD) system is considered a communicating multimedia system that can allow clients be interested whilst watching a video of their selection anywhere and anytime upon their convenient. The design of the VOD system is based on the process and location of its three basic contents, which are: the server, network configuration and clients. The clients are varied from numerous approaches, battery capacities, involving screen resolutions, capabilities and decoder features (frame rates, spatial dimensions and coding standards). The up-to-date systems deliver VOD services through to several devices by utilising the content of a single coded video without taking into account various features and platforms of a device, such as WMV9, 3GPP2 codec, H.264, FLV, MPEG-1 and XVID. This limitation only provides existing services to particular devices that are only able to play with a few certain videos. Multiple video codecs are stored by VOD systems store for a similar video into the storage server. The problems caused by the bandwidth overhead arise once the layers of a video are produced. The replication codec of a similar video and the layering encodes require further bandwidth storage and transmissions. The main objective of this paper is to propose a mechanism that can adapt an optimal video service according to mobile devices features and specifications. Therefore, it can save the CPU and RAM to be used on the server side. This paper proposed a novel adaptive policy to deliver the services of the VOD for several heterogeneous mobile devices. Additionally, the emphasis on introducing an up-to-date policy for profiling a video and an advanced protocol, namely the DNDS protocol, which is significant to propose a technique that depends on the collected data that delivers the most effective VOD facilities through cellular devices. This protocol is created to function over the whole current proposed systems components. Moreover, the DNDS protocol is applied and performed between the mobile clients, media forwarders and main servers. The performance of the proposed system is validated by examining two factors that rely on the RAM and the CPU. It can be found to be proven from the results that the proposed server contains lesser overload as the CPUs and RAMs servers is not important for converting every on-line video for every ordered device profile.

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