Probabilistic Prediction of the QoS of Service Orchestrations: A Truly Compositional Approach

Abstract

The ability to a priori predict the QoS of a service orchestration is of pivotal importance for both the design of service compositions and the definition of their SLAs. QoS prediction is challenging because the results of service invocations is not known a priori. In this paper we present an algorithm to probabilistically predict the QoS of a WS-BPEL service orchestration. Our algorithm employs Monte Carlo simulations and it improves previous approaches by coping with complex dependency structures, unbound loops, fault handling, and unresponded service invocations.

QoS-Aware Deployment of IoT Applications Through the Fog

“…As our immediate future work, we intend to employ probability distributions to represent QoS profiles and to exploit Monte Carlo simulation (as in [29]) to predict the reliability of deployment plans. Other QoS metrics which can be considered include reliability of links and nodes, power consumption, security, and monetary costs.…”

Analysing Multiple QoS Attributes in Parallel Design Patterns-Based Applications

“…Finally, it is worth highlighting the potentials and generality of our approach, which is not limited to parallel design patterns, but can also be adapted to predict QoS of other kinds of composite software applications. For instance, our previous work [5] shows how to employ Both, Delay, and Monte Carlo simulations to predict the QoS (e.g., response time, availability, or cost) of web service orchestrations.…”