Dynamic data broadcasting with traffic awareness

Data dissemination has significantly served as a scalable data delivery mechanism in wireless networks. However, even though the broadcast traffic has the nature of dynamic changes, most previous research efforts were elaborated upon the premise of static workloads and access patterns without having proper traffic awareness. In this paper, we address the existence of client impatience and accordingly devise an online traffic awareness mechanism based on a novel selective deferment and reflection (SDR) technique to estimate the dynamic workloads and access patterns in a granularity of a broadcast cycle. In comparison with prior probing and feedback approaches, our design is of practical usefulness in that it has low complexity and is light-weight without performance degradation. With various dynamic traffic scenarios, the experimental results show that with an increasing/decreasing workload, the real access frequency distribution is bounded by two specific estimated distributions. This fact in turn suggests us to employ a trigonometric tuning method to further enhance the estimation. In addition, we examine that the mean difference between the estimated access frequency distribution and the real one is very small, consequently indicating the feasibility and reliability of our proposed data broadcast mechanism with traffic awareness.