A Novel Cooperative Content Fetching-Based Strategy to Increase the Quality of Video Delivery to Mobile Users in Wireless Networks

Abstract

Cooperatively fetching video content with the help of other mobile nodes can release some of the pressure on storage and bandwidth of the constrained mobile devices in wireless networks and speeds up the localization process of video resources so as to support better quality of viewing experience. In this context, the discovery of the appropriate mobile cooperative node becomes a key factor and is also a challenge for the deployment of such a fetching scheme. In this paper, we introduce a novel cooperative content fetching-based strategy to increase the quality of video delivery to mobile users in wireless networks (CCF). By intelligently monitoring the real-time variation in the state of the one-hop neighbors (immediate-neighbors) of the video resource downloader, CCF employs an innovative estimation model to measure the stability of these immediate-neighbors. In order to enhance the cooperative fetching efficiency, CCF designs a communication quality forecast model to measure link reliability and forecast the available bandwidth. By making use of a newly proposed cooperative fetching algorithm, CCF can speed up fetching and disseminating of video resources with the help of cooperative neighbors selected in terms of stability and communication quality. Simulation results show how CCF obtains higher selection accuracy of cooperative neighbors, lower average end-to-end delay, lower average packet loss ratio, higher average throughput, higher video quality, and lower maintenance overhead in comparison with state-of-the-art solutions.