QoS-aware management of monotonic service orchestrations

Abstract

We study QoS-aware management of service orchestrations, specifically for orchestrations having a data-dependent workflow. Our study supports multidimensional QoS. To capture uncertainty in performance and QoS, we provide support for probabilistic QoS. Under the above assumptions, orchestrations may be nonmonotonic with respect to QoS, meaning that strictly improving the QoS of a service may strictly decrease the end-to-end QoS of the orchestration, an embarrassing feature for QoS-aware management. We study monotonicity and provide sufficient conditions for it. We then propose a comprehensive theory and methodology for monotonic orchestrations. Generic QoS composition rules are developed via a QoS Calculus, also capturing best service binding-service discovery, however, is not within the scope of this work. Monotonicity provides the rationale for a contract-based approach to QoS-aware management. Although function and QoS cannot be separated in the design of complex orchestrations, we show that our framework supports separation of concerns by allowing the development of function and QoS separately and then weaving them together to derive the QoS-enhanced orchestration. Our approach is implemented on top of the Orc script language for specifying service orchestrations.

The Robustness of Periodic Orchestrations in Uncertain Evolving Environments

“…The work reported here is complementary to that of [1,7] where the monotonicity of the QoS of web services is considered. One other possible line of future research is to extend the monotonicity properties of the assesments of non-recursive orchestrations [2] to periodic orchestrations.…”

Quantitative Verification for Monitoring Event-Streaming Systems

“…Figures 10a and 10c contains the matrix equations for model checking this model against Φ 1 and Φ 2 , respectively. Note that it is easy to change these two matrix equations into the form in Equation (2). The fact that the VOF f can be expressed as Equation (2) also implies that f is smooth.…”

“…The model specification files and other supporting files for the two case studies are available in the first author's homepage. 2…”

Uncertainty in the Cloud: An Angel-Daemon Approach to Modelling Performance

“…The quality of service (QoS) realised by MM 1 depends on a number of environmental factors [1]. Typically IaaS clouds contain a variety of machine types.…”

“…A service (hosted in the cloud, or elsewhere) may have less predictable performance behaviour than a conventional imperative program -the QoS of service-based systems are considered in detail in [1]. Some of the factors influencing the performance of applications in the cloud are:…”