ABSTRACT: The first work in this research line addresses the transmission of pre-encoded JPEG2000 video within a video-on-demand scenario. The primary requirement for the rate allocation algorithm deployed in the server is to match the real-time processing demands of the application. Scalability in terms of complexity must be provided to supply a valid solution by a given instant of time. The FAst rate allocation through STeepest descent (FAST) method introduced in this work selects an initial (and possibly poor) solution, and iteratively improves it until time is exhausted or the algorithm finishes execution. Experimental results suggest that FAST commonly achieves solutions close to the global optimum while employing very few computational resources.

As explained in the manuscript, an important contribution of the FAST algorithm is the optimization procedure carried out in the sourcecode, so the Java implementation developed for this paper is provided herein:

ABSTRACT: The FAST algorithm was then adapted to allow the transmission of pre-encoded JPEG2000 video over time-varying channels, which are channels that vary their capacity during video transmission due to network congestion, hardware failures, or router saturation. Such variations occur often in networks and are commonly unpredictable in practice. The optimization problem is posed for such networks and a rate allocation method is formulated to handle such variations. The main insight of the proposed method is to extend the complexity scalability features of the FAst rate allocation through STeepest descent (FAST) algorithm. Extensive experimental results suggest that the proposed transmission scheme achieves near-optimal performance while expending few computational resources.