The next generation large-scale computing applications require network support for interactive visualization, computational steering and instrument control over wide-area networks. In particular, these applications require stable transport streams over wide-area networks, which are not adequately supported by current transport methods. We propose a new class of protocols capable of stabilizing a transport channel at a specified throughput level in the presence of random network dynamics based on the classical Robbins-Monro stochastic approximation approach. These protocols dynamically adjust the window size or sleep time at the source to achieve stable throughput at the destination. The target throughput typically corresponds to a small fraction of the available connection bandwidth. This approach yields provably probabilistically stable protocols as a consequence of carefully adjusted step sizes. The superior and robust stabilization performance of the proposed approach is extensively evaluated in a simulated environment and further verified through real-life implementations and deployments over both Internet and dedicated connections under disparate network conditions in comparison with existing transport methods.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Goodput stabilization
- Stochastic approximation methods
- Transport control