A Context-Aware Adaptive Streaming Media Distribution System in a Heterogeneous Network with Multiple Terminals

Abstract

We consider the problem of streaming media transmission in a heterogeneous network from a multisource server to home multiple terminals. In wired network, the transmission performance is limited by network state (e.g., the bandwidth variation, jitter, and packet loss). In wireless network, the multiple user terminals can cause bandwidth competition. Thus, the streaming media distribution in a heterogeneous network becomes a severe challenge which is critical for QoS guarantee. In this paper, we propose a context-aware adaptive streaming media distribution system (CAASS), which implements the context-aware module to perceive the environment parameters and use the strategy analysis (SA) module to deduce the most suitable service level. This approach is able to improve the video quality for guarantying streaming QoS. We formulate the optimization problem of QoS relationship with the environment parameters based on the QoS testing algorithm for IPTV in ITU-T G.1070. We evaluate the performance of the proposed CAASS through 12 types of experimental environments using a prototype system. Experimental results show that CAASS can dynamically adjust the service level according to the environment variation (e.g., network state and terminal performances) and outperforms the existing streaming approaches in adaptive streaming media distribution according to peak signal-to-noise ratio (PSNR).

Be-Ozr: An Efficient Available Bandwidth Estimation In Ieee802.11E Network

“…In [3], bandwidth estimation techniques were categorized into active probing, mathematical model based, and calculation based passive measurement techniques. In the work of [4], they classified bandwidth estimation technique into self-congestion and model-based approach, while [5] classified it into algorithm that are designed for specific networks (usually with guaranteed QoS), algorithm that uses probe packet with pre-determined spacing and algorithms targeting video streaming where a client-server is assumed. Researchers have presented different classification of bandwidth estimation technique; however, they perform the same role notwithstanding their different nomenclatures.…”