Optimal linear interpolation coding for server-based computing

Due to its reduced administrative costs and better resource utilization, server-based computing (SBC) is becoming a popular approach for delivering computational services across a network. 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 screen updates efficiently, existing approaches do not effectively support multimedia applications. To address this problem, we propose optimal linear interpolation (OLI), a new pixel-based 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 for an adaptive trade-off between network bandwidth and processing time requirements. We further propose and evaluate 2D 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.