Optimal linear interpolation coding for server-based computing
نویسندگان
چکیده
Server-based computing (SBC) is becoming a popular approach to deliver computational services across the network due to its reduced administrative costs and better resource utilization. In SBC, all application processing is done on servers while only screen updates are sent to clients. While many SBC encoding techniques have been explored for transmitting these screen updates efficiently, existing screen update approaches do not effectively support multimedia applications. To address this problem, we propose optimal linear interpolation (OLI), a new pixelbased SBC screen update coding algorithm. With OLI, the server selects and transmits only a small sample of pixels to represent a screen update. The client recovers the complete screen update from these samples using piecewise linear interpolation to achieve the best visual quality. OLI can be used to provide lossless or lossy compression to adaptively trade-off between network bandwidth and processing time requirements. We further propose and evaluate 2-D lossless linear interpolation (2DLI), which is based on OLI but additionally provides lower encoding complexity for lossless compression. Our experimental results show that when compared with other compression methods, 2DLI provides good data compression ratio with modest computational overhead, for both servers and clients.
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Low-Complexity Interpolation Coding for Server-Based Computing
In recent years, the growing total cost of ownership has resulted in a shift away from the distributed model of desktop computing toward a more centralized server-based computing (SBC) model. In SBC, all application logic is executed on the server while clients simply process the resulting screen updates sent from the server. To provide good performance, SBC systems employ various techniques to...
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