Content-based network resource allocation for real time remote laboratory applications

Abstract

This paper presents a practical solution to make remote laboratories a realizable dream. A remote laboratory is an online laboratory where students can get first-hand experience of engineering labs via Internet. Video transmission can provide hands on experience to the user but the transmission channel or networks typically have variable and low bandwidth that poses a tough constraint for such implementation. This work presents a practical solution to such problems by adaptively transmitting the best available quality of laboratory videos to the user depending on network bandwidth. The concept behind our work is that not all objects or frames of the video have equal importance, and thus bandwidth reduction can be accomplished by intelligently transmitting important parts at relatively higher resolution. A localized Time adaptive mean of Gaussian (L-TAMOG) approach is used to search for moving objects which are then allocated network resources dynamically according to the varying network bandwidth variations. Adaptive motion compensated wavelet-based encoding is used to achieve scalability and high compression. The proposed system tracks the network bandwidth and delivers optimally the most important contents of video to the student. Experimental results over several remote laboratory sequences show the efficiency of the proposed framework.

Polymorphic Wavelet Transform

“…The first dimension is the choice of suitable DWT filter. Different applications such as medical image processing, High Definition Television, video-surveillance applications, and wireless video all have different real-time constraints [22,24] and different filters may serve the requirements at different times.…”

“…An interface is provided for the application to dynamically notify the architecture about its performance requirements in terms of the hardware requirements and the image reconstruction quality requirements. Besides the previously mentioned video-surveillance application, other real-time video streaming applications such as those used in medical image processing [18], remote laboratories [22], or educational video streaming [24] may benefit enormously from the polymorphism of DWT kernels.…”

An Efficient Hardware Architecture for Multimedia Encryption and Authentication Using the Discrete Wavelet Transform

“…Recent research [7], [8] addresses these issues by choosing a simple DWT filter design with fewer adders and other hardware, thereby optimizing the hardware architecture for high performance. In [9], we provide a DWT-based architecture to enable real-time video-streaming applications such as those used in tele-medicine [10], remote laboratories [11], educational video streaming [12] and video surveillance. The DWT filters presented in [7] give a polymorphic hardware support for the real-time requirements of multimedia applications.…”

Algorithms and Architectures for Secure Embedded Multimedia Systems

“…An interface is provided for the application to dynamically notify the architecture about its performance requirements in terms of the hardware requirements and the image reconstruction quality requirements. Besides the previously-mentioned video surveillance application, other real-time video streaming applications such as those used in medical image processing [52], remote laboratories [76], or educational video streaming [78] may benefit enormously from the polymorphism of DWT kernels.…”

“…The first dimension is the choice of suitable DWT filter. Different applications such as medical image processing, High Definition Television, video surveillance applications, and wireless video all have different real-time constraints [78,76] and different filters may serve the requirements at different times.…”