Interactive transmission processing for large images in a resource-constraint mobile wireless network

Abstract

In the state-of-the-art methods for (large) image transmission, no user interaction behaviors (e.g., user tapping) can be actively involved to affect the transmission performance (e.g., higher image transmission efficiency with relatively poor image quality). So, to effectively and efficiently reduce the large image transmission costs in resource-constraint mobile wireless networks (MWN), we design a content-based and bandwidth-aware Interactive large Image Transmission method in MWN, called the Iit. To the best of our knowledge, this is the first study on the interactive image transmission. The whole transmission processing of the Iit works as follows: before transmission, a preprocessing step computes the optimal and initial image block (IB) replicas based on the image content and the current network bandwidth at the sender node. During transmission, in case of unsatisfied transmission efficiency, the user’s anxiety to preview the image can be implicitly indicated by the frequency of tapping the screen. In response, the transmission resolutions of the candidate IB replicas can be dynamically adjusted based on the user anxiety degree (UAD). Finally, the candidate IB replicas are transmitted with different priorities to the receiver for reconstruction and display. The experimental results show that the performance of our approach is both efficient and effective, minimizing the response time by decreasing the network transmission cost while improving user experiences.