A Framework for Proactive Self-adaptation of Service-Based Applications Based on Online Testing

Abstract

Service-based applications have to continuously and dynamically selfadapt in order to timely react to changes in their context, as well as to efficiently accommodate for deviations from their expected functionality or quality of service. Currently, self-adaptation is triggered by monitoring events. Yet, monitoring only observes changes or deviations after they have occurred. Therefore, selfadaptation based on monitoring is reactive and thus often comes too late, e.g., when changes or deviations already have led to undesired consequences. In this paper we present the PROSA framework, which aims to enable proactive selfadaptation. To this end, PROSA exploits online testing techniques to detect changes and deviations before they can lead to undesired consequences. This paper introduces and illustrates the key online testing activities needed to trigger proactive adaptation, and it discusses how those activities can be implemented by utilizing and extending existing testing and adaptation techniques.

A prediction-driven adaptation approach for self-adaptive sensor networks

“…Pro-activeness decreases the aftereffects of changes, or improves control of change propagation (e.g. in environment monitoring, safety-critical systems) [27,17]. Resource prediction as conceived by [2,16,25] refers to estimating the available level of a resource in the near future, (e.g., in the next 10 seconds).…”

“…Hielscher et al [17] proposed PROSA, an online testingbased proactive self-adaptation. Firstly, they aim at predicting new failures from past monitoring data, but their goal is to detect whether one specific failure that has been uncovered in on aService-Based Applications (SBA) could also occur in other SBA instances.…”

“…Firstly, they aim at predicting new failures from past monitoring data, but their goal is to detect whether one specific failure that has been uncovered in on aService-Based Applications (SBA) could also occur in other SBA instances. Secondly, in [17] the authors reject past monitoring data after a dynamic adaptation of the system. In doing this the system may fall into cyclical adaptations without detecting it.…”

A Two-Phase Online Prediction Approach for Accurate and Timely Adaptation Decision

“…By this means, an upcoming functional failure can be forecasted before its real occurrence. [9] presents the PROSA framework, which defines key activities to initiate online testing either on the binding level or on the service composition level, and thereby proactively triggers the adaptation process. [10] investigates how to guarantee functional correctness of conversational services.…”

Adaptive composition in dynamic service environments

“…to prevent future failure or improve performance), these are still very limited and mainly focus on the change detection part, giving little or no consideration to the actual adaptation process. Proposed proactive change detection methods include applying performance prediction techniques [8,23,9], testing the behaviour of services 160 using generated test cases [7,24], and subscribing to change requests with the registry [25]. Such detection efforts can be considered complementary to our work (which focuses instead on the latter change handling step).…”