Pipelining image compositing in heterogeneous networking environments

Because of intensive inter-node communications, image compositing has always been a bottleneck in parallel visualization systems. In a heterogeneous networking environment, the variation of link bandwidth and latency adds more uncertainty to the system performance. In this paper, we present a pipelining image compositing algorithm in heterogeneous networking environments, which is able to rearrange the direction of data flow of a compositing pipeline under strict ordering constraint. We introduce a novel directional image compositing operator that specifies not only the color and α channels of the output but also the direction of data flow when performing compositing. Based on this new operator, we thoroughly study the properties of image compositing pipelines in heterogeneous environments. We develop an optimization algorithm that could find the optimal pipeline from an exponentially large searching space in polynomial time. We conducted a comprehensive evaluation on the ns-3 network simulator. Experimental results demonstrate the efficiency of our method. This paper brings up a novel directional image compositing operator that takes the data flow direction into account when performing compositing. With this operator, we are able to find all the valid compositing pipelines for the participating nodes in heterogeneous environments. We also propose a dynamic programming based optimization algorithm that could get the optimal pipeline in polynomial time.