n-Dimensional QoS Framework for Real-Time Service-Oriented Architectures

Service-Orientation has long provided an effective mechanism to integrate heterogeneous systems in a loosely coupled fashion as services. However, with the emergence of Internet of Things (IoT) there is a growing need to facilitate the integration of real-time services executing in non-controlled, non-real-time, environments such as the Cloud. With the need to integrate both cyberphysical systems as hardware-in-the-loop (HIL) components and also with Simulation as a Service (SIMaaS) the execution performance and response-times of the services must be managed. This paper presents a mathematical framework that captures the relationship between the host execution environment and service performance allowing the estimation of Quality of Service (QoS) under dynamic Cloud workloads. A formal mathematical definition is provided and this is evaluated against existing techniques from both the Cloud and Real-Time Service Oriented Architecture (RT-SOA) domains. The proposed approach is evaluated against the existing techniques through simulation and demonstrates a reduction of QoS violation percentage by 22% with respect to response-times as well as reducing the number of Micro-Service (S) instances with QoS violations by 27%.