Dynamic end-to-end image adaptation for guaranteed quality of service in wireless image data services

The paper investigates total end-to-end service variability issues in providing dynamic image adaptation services to wireless end users. While most existing image adaptation techniques focus on improving wireless transmission latency by adapting content-rich images to the time varying bandwidth availability of wireless networks, we have found dynamic service load variations at the server also significantly affect end-to-end service latency. We introduce a dynamic end-to-end image adaptation technique that optimizes the runtime image adaptation process so as to provide guaranteed total service latency (including both server processing latency and wireless transmission latency) with a maximized image quality. Through judicious tuning of application-layer image compression parameters, the proposed technique dynamically optimizes both the image quality and each component of service latency required for wireless image data services simultaneously depending on service variability issues existing at both server-side and network-side. Experimental results under synthetic service workloads demonstrate that our proposed dynamic end-to-end image adaptation can provide guaranteed service latency with a minimal impact on the image quality loss.