Adaptive middleware supporting scalable performance for high-end network services

Network service-based computation is a promising paradigm for both scientific and engineering, and enterprise computing. The network service allows users to focus on their application and obtain services when needed, simply by invoking the service across the network. In this paper, we show that an adaptive, general-purpose run-time infrastructure in support of effective resource management can be built for a wide range of high-end network services running in a single-site cluster and in a Grid. The primary components of the run-time infrastructure are: (1) dynamic performance prediction; (2) adaptive intra-site resource management; and (3) adaptive inter-site resource management. The novel aspect of our approach is that the run-time system is able to dynamically select the most appropriate performance predictor or resource management strategy over time. This capability not only improves the performance, but also makes the infrastructure reusable across different high-end services. To evaluate the effectiveness and applicability of our approach, we have transformed two different classes of high-end applications-data parallel and distributed applications-into network services using the infrastructure. The experimental results show that the network services running on the infrastructure significantly reduce the overall service times under dynamically varying circumstances.