The interactive performance of SLIM: a stateless, thin-client architecture
Proceedings of the seventeenth ACM symposium on Operating systems principles
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
IEEE Internet Computing
A Streaming Piecewise-Constant Model
DCC '99 Proceedings of the Conference on Data Compression
A Progressive Ziv-Lempel Algorithm for Image Compression
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Context Models for Palette Images
DCC '98 Proceedings of the Conference on Data Compression
A Lossless 2-D Image Compression Technique for Synthetic Discrete-Tone Images
DCC '98 Proceedings of the Conference on Data Compression
Evaluating windows NT terminal server performance
WINSYM'99 Proceedings of the 3rd conference on USENIX Windows NT Symposium - Volume 3
IEEE Transactions on Circuits and Systems for Video Technology
The Performance of Remote Display Mechanisms for Thin-Client Computing
ATEC '02 Proceedings of the General Track of the annual conference on USENIX Annual Technical Conference
Fast Motion Detection for Thin Client Compression
DCC '02 Proceedings of the Data Compression Conference
Streaming Thin Client Compression
DCC '01 Proceedings of the Data Compression Conference
THINC: a virtual display architecture for thin-client computing
Proceedings of the twentieth ACM symposium on Operating systems principles
On the performance of wide-area thin-client computing
ACM Transactions on Computer Systems (TOCS)
Analysis and reduction of data spikes in thin client computing
Journal of Parallel and Distributed Computing
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In this paper, we describe Thin Client Compression (TCC), a novel codec for Screendumps and sequences of such images that exploits both local and global redundancy as well as interframe redundancy. Our method extends textual image compression to non-bilevel images, and uses three piecewise-constant models to separately code bilevel marks, non-bilevel marks, and the residue. It also speeds up pattern matching and substitution by exploiting the absence of noise in synthetic images, and shares its codebook across images. Our method compresses a series of test images 2.6 to 8.2 times better than state-of-the-art methods. Its speed is adequate for interactive logins, and it achieves the best end-to-end latency over low bandwidth connections.