Modern embedded systems are being modeled as Reconfigurable High Speed Computing System (RHSCS) where Reconfigurable Hardware, that is, Field Programmable Gate Array (FPGA), and softcore processors configured on FPGA act as computing elements. As system complexity increases, efficient task distribution methodologies are essential to obtain high performance. A dynamic task distribution methodology based on Minimum Laxity First (MLF) policy (DTD-MLF) distributes the tasks of an application dynamically onto RHSCS and utilizes available RHSCS resources effectively. The DTD-MLF methodology takes the advantage of runtime design parameters of an application represented as DAG and considers the attributes of tasks in DAG and computing resources to distribute the tasks of an application onto RHSCS. In this paper, we have described the DTD-MLF model and verified its effectiveness by distributing some of real life benchmark applications onto RHSCS configured on Virtex-5 FPGA device. Some benchmark applications are represented as DAG and are distributed to the resources of RHSCS based on DTD-MLF model. The performance of the MLF based dynamic task distribution methodology is compared with static task distribution methodology. The comparison shows that the dynamic task distribution model with MLF criteria outperforms the static task distribution techniques in terms of schedule length and effective utilization of available RHSCS resources.
A Dynamic Task Distribution approach using Clustering of Data Centers and Virtual Machine Migration in Mobile Cloud Computing
