Various researchers have reported that traffic measurements demonstrate considerable burstiness on several time scales, with properties of self-similarity. Also, the rapid development of technologies has widened the scope of network and Internet applications and, in turn, increased traffic. The self-similar nature of this data traffic may exhibit spikiness and burstiness on large scales with such behaviour being caused by strong dependence characteristics in data: that is, large values tend to come in clusters and clusters of clusters and so on. Several studies have shown that TCP, the dominant network (Internet) transport protocol, contributes to the propagation of self-similarity. Bursty traffic can affect the Quality of Service of all traffic on the network by introducing inconsistent latency. It is easier to manage the workloads under less bursty (i.e. smoother) conditions. In this paper, we introduce a novel algorithm for traffic shaping, which can smooth out the traffic burstines...