Dynamic, competitive scheduling of multiple DAGs in a distributed heterogeneous environment

With the advent of large scale heterogeneous environments, there is a need for matching and scheduling algorithms which can allow multiple DAG-structured applications to share the computational resources of the network. This paper presents a matching and scheduling framework where multiple applications compete for the computational resources on the network. In this environment, each application makes its own scheduling decisions. Thus, no centralized scheduling resource is required. Applications do not need direct knowledge of the other applications. The only knowledge of other applications arrives indirectly through load estimates (like queue lengths). This paper also presents algorithms for each portion of this scheduling framework. One of these algorithms is modification of a static scheduling algorithm, the DLS algorithm, first presented by Sih and Lee [1]. Other algorithms attempt to predict the future task arrivals by modeling the task arrivals as Poisson random processes. A series of simulations are presented to examine the performance of these algorithms in this environment. These simulations also compare the performance of this environment to a more conventional, single user environment.