Integrated QoS-aware Resource Provisioning for Parallel and Distributed Applications

Abstract

With more parallel and distributed applications moving to Cloud and data centers, it is challenging to provide predictable and controllable resources to multiple tenants, and thus guarantee application performance. In this paper, we propose an integrated QoS-aware resource provisioning platform based on virtualization technology for computing, storage and network resources. Coarse-grained CPU mapping and fine-grained CPU scheduling mechanisms are proposed to enable adjustable computing power. A hierarchical distributed scheduling mechanism is implemented on a scalable storage system to guarantee I/O throughput for individual tenants and applications. A network manager has also been developed to guarantee the data transmission rate. Web-based interface enables users to monitor realtime resource utilization and to adjust resource QoS levels on the fly. According to our experimental results, the resource cost can be saved up to 45% without degrading the performance of a distributed data processing benchmark; and the performance of a parallel agent-based simulation can be improved by 91% using the same amount of resources.