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- Title
Adaptive Compression for Remote Visualization.
- Authors
Constantinescu, Zoran; Vladoiu, Monica
- Abstract
Remote visualization techniques that use client-server environments allow users to access large datasets. One possible solution for remote visualization is the use of compression techniques, in which images are generated and compressed at the servers' side and then the encoded images are transferred over a data network, decompressed and displayed at the clients' side. In this paper we propose an adaptive algorithm based on reinforcement learning for choosing one of the available compression methods in order to maximize the frame rate. Our experiments show that such an algorithm can work in a dynamic and uncertain environment, consisting of a visualization server, a visualization client, and a network for transferring the compressed images between the server and the client.
- Subjects
REMOTE sensing; VISUALIZATION; MICROWAVE remote sensing; POLARIMETRIC remote sensing; CLIENT/SERVER computing; IMAGE servers; COOPERATIVE processing; DISTRIBUTED computing; INTERNET servers
- Publication
Petroleum - Gas University of Ploiesti Bulletin, Mathematics - Informatics - Physics Series, 2009, Vol 61, Issue 2, p49
- ISSN
1224-4899
- Publication type
Article