Supporting Adaptive Remote Access to Multiresolutional or Hierarchical Data for Large User Groups


Advances in storage and processing technologies now allow content providers and scientists to capture, simulate, or create immense collections of data. Unfortunately, advances in networking technologies, while impressive, have not kept pace. Although we can build multi-gigabit networks, achieving those line speeds end-toend remains almost impossible. Distributing content to large groups of independent users makes that task even harder. As the gap between the amount of data we can capture, store, and process and the resources we have to transmit that data increases, the problem of scalable and adaptive distribution becomes increasingly central to the performance of high-bandwidth and high-volume applications such as data visualization, teleimmersion, and media streaming. In my research, I address the distribution of multiresolutional or hierarchical datasets to large groups of heterogeneous and independent users.

ACM Multimedia Doctoral Symposium