PROJECT TITLE :

TrafficShaper: Shaping Inter-Datacenter Traffic to Reduce the Transmission Cost - 2018

ABSTRACT:

The emerging deployment of geographically distributed information centers (DCs) incurs a significant quantity of data transfers over the Web. Such transfers are sometimes charged by Internet service suppliers with the widely adopted qth percentile charging model. In such a charging model, the time slots with high (a hundred - q) percent of knowledge transmission do not have an effect on the whole transmission price and will be viewed as “free.” This brings the opportunity to optimize the scheduling of interDC transfers to minimize the whole transmission value. However, a terribly little work has been done to take advantage of those “free” time slots for scheduling inter-DC transfers. The crux is that existing work either lacks a mechanism to accumulate traffic to “free” time slots, or inevitably depends on previous information of future traffic arrival patterns. In this Project, we present TrafficShaper, a new scheduler that shapes the inter-DC traffic to use the “free” time slots concerned in the qth percentile charging model, therefore as to reduce or maybe minimize the transmission value. When shaping traffic, TrafficShaper advocates a simple principle: more traffic peaks ought to be scheduled in “free” time slots, while less traffic differentiation should be maintained among the remaining time slots. To this end, TrafficShaper designs a pricing-aware control framework, that makes online selections for inter-DC transfers while not requiring a previous information of traffic arrivals. To verify the performance of TrafficShaper, we tend to conduct rigorous theoretical analysis based on Lyapunov optimization techniques, large-scale trace-driven simulations, and small-scale testbed implementation. Results from rigorous mathematical analyses demonstrate that TrafficShaper can create the transmission value arbitrarily close to the optimum worth. Extensive trace-driven simulation results show that TrafficShaper can reduce the transmission cost by up to 40.23%, compared with the state-of-the-art solutions. The testbed experiments further verify that TrafficShaper will realistically scale back the transmission price by up to 19.thirty eight%.