Service-Oriented Grid Application Platform

The continuous increasing of computing power in electric system computing places a threshold to the single host use and suggests an approach based on distributed computing. An emerging solution is grid technology, which allows organization to make better use of existing computing resources by providing them with a single, transparent, aggregated source of computing power. New generation of grid infrastructure, where web services are building blocks, allow management of a web services workflow.At first, a service-based grid application development platform was proposed for large scale power system computing and simulation. Grid users can make use of all services that the platform supplied through a portal. Also, all the services are implemented using parallel methods, along with our grid platform, the computing and simulation performance is improved.Secondly, a novel strategy– QoS-Aware and Fault-Tolerant Workflow Composition– has been applied to utilize web services and business process execution language for overcoming the issues about task assignment, security, flexibility and workflow management. This new strategy is lightweight web services based computing power-sharing architecture, and it is not only suitable for executing computing works which are able to run in batches, but also be able to solve current issues in Web Services based Computing Application such as system resilience, fault tolerance, efficiency of job scheduling and the instability in congested network environment. This novel model that characterizes, estimates and analyzes several QoS properties of dynamically-executed fault-tolerant Web services compositions–namely the reliability and the execution time.Finally, since a workflow may fail by many reasons in a typically grid environment, such as service unavailable, network issue and etc. tracking the failures and try to recover from it is critical to workflow applications. To accomplish this goal, we propose a fault-tolerant model for workflow composition. In doing so, obtained estimations can contribute in acquiring more accurate information about the failures information and can be used later to improve the composition QoS in the future.