A compact storage scheme for fast wavelet-based subregion retrieval

Adaptive Partitioning and Scheduling for Enhancing WWW Application Performance

“…Figure 5 depicts the above processing steps and four possible cutoff points for partitioning this chain for the server and client. We discuss the possible computation and communication scenarios for four partitioning points below [21]. Notice that we also need to consider that the data sent from the server to the client may be compressed first for transmission, then decompressed at the client site.…”

“…The model of computation and communication described in [6,21] uses the chain of tasks depicted in Fig. 5: (1) Fetching compressed wavelet data and extracting the subregion.…”

“…For the next generation of the Internet, e.g., T3 (45 MB/s), TV set-top boxes (10 MB/s), ATM, and vBNS (155 MB/s), the transmission time will significantly decrease but the demands for larger image files will continue increasing, especially when there are millions more users on the Internet. The ADL has adopted progressive multiresolution image delivery and subregion browsing as strategies to reduce Internet traffic when accessing map images [3,21]. This approach is based on the idea that users often browse large images via a thumbnail (coarse resolution) and desire to rapidly view higher-resolution versions and subregions of those images already being viewed.…”

Towards a hierarchical scheduling system for distributed WWW server clusters

“…To support these features, the ADL system is using a hierarchical data representation for multiresolution images [10]. Figure 3 depicts a task chain for processing a user request in accessing an image or subimage with a higher resolution, based on an implementation in [22]. Tasks in this chain are:…”