Modeling and Analyzing MAPE-K Feedback Loops for Self-Adaptation

Arcaini, Paolo; Riccobene, Elvinia; Scandurra, Patrizia

doi:10.1109/seams.2015.10

Cited by 157 publications

(104 citation statements)

References 24 publications

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“…Current approaches for supporting runtime adaptation in service-oriented systems offer poor support for validation [16] [7]. Like most autonomic systems, runtime adaptation in serviceoriented systems is based on IBM's Monitoring, Analysis, Planning, and Execution model (MAPE) [47]. However, MAPE does not support validation.…”

Section: Research Challengesmentioning

confidence: 99%

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

Mutanu

Kotonya

2019

IET softw.

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Software as a Service reflects a "service-oriented" approach to software development that is based on the notion of composing applications by discovering and invoking network-available services to accomplish some task. However, as more business organizations adopt service-oriented solutions and the demands on them grow, the problem of ensuring that the software systems can adapt fast and effectively to changing business needs, changes in their runtime environment and failures in provided services has become an increasingly important research problem. Dynamic adaptation has been proposed as a way to address the problem. However, for adaptation to be effective several other factors need to be considered. This paper identifies the key factors that influence runtime adaptation in service-oriented systems, and examines how well they are addressed in 29 adaptation approaches intended to support service-oriented systems.

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Section: Research Challengesmentioning

confidence: 99%

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

Mutanu

Kotonya

2019

IET softw.

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“…We assume that to realize modern challenges in industry, software products need to feature a certain degree of autonomy, i.e., they feature at least one component called planner capable of making decisions by providing a plan of actions which the system is supposed to perform to best fulfill its intended goal [8], [9]. This goal is encoded by providing the system with a fitness function that can be used to evaluate plans.…”

Section: Foundationsmentioning

confidence: 99%

“…a) Expected Change: The usefulness and importance of self-optimization at the customer's side has already been claimed in the original vision of autonomic computing [6] and has been shown on many occasions since [3], [7], [8]. In these cases, self-optimization usually refers to a process of specialization, i.e., the system is built with a large variety of possible use cases in mind and learns to work best for the few of these it actually faces on site.…”

Section: Introductionmentioning

confidence: 99%

Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms

Gabor

Belzner

Phan

et al. 2018

2018 IEEE International Conference on Autonomic Computing (ICAC)

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As automatic optimization techniques find their way into industrial applications, the behavior of many complex systems is determined by some form of planner picking the right actions to optimize a given objective function. In many cases, the mapping of plans to objective reward may change due to unforeseen events or circumstances in the real world. In those cases, the planner usually needs some additional effort to adjust to the changed situation and reach its previous level of performance. Whenever we still need to continue polling the planner even during re-planning, it oftentimes exhibits severely lacking performance. In order to improve the planner's resilience to unforeseen change, we argue that maintaining a certain level of diversity amongst the considered plans at all times should be added to the planner's objective. Effectively, we encourage the planner to keep alternative plans to its currently best solution.As an example case, we implement a diversity-aware genetic algorithm using two different metrics for diversity (differing in their generality) and show that the blow in performance due to unexpected change can be severely lessened in the average case. We also analyze the parameter settings necessary for these techniques in order to gain an intuition how they can be incorporated into larger frameworks or process models for software and systems engineering.

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“…Environmental risk analyses can be adopted at runtime, e.g. as on-line risk monitors, to control the execution of self-preservation strategies, and even to trigger adaptation and learning towards dealing with threats in the environment as in [3]. These domains, nonetheless, could benefit from considering biologically inspired mechanisms for efficient self-preservation responses as well as risk measures and factors.…”

Section: Related Workmentioning

confidence: 99%

Risk-Based Triggering of Bio-inspired Self-preservation to Protect Robots from Threats

Chiu

Araiza-Illan

Eder

2017

Towards Autonomous Robotic Systems

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Safety in autonomous systems has been mostly studied from a human-centered perspective. Besides the loads they may carry, autonomous systems are also valuable property, and self-preservation mechanisms are needed to protect them in the presence of external threats, including malicious robots and antagonistic humans. We present a biologically inspired risk-based triggering mechanism to initiate selfpreservation strategies. This mechanism considers environmental and internal system factors to measure the overall risk at any moment in time, to decide whether behaviours such as fleeing or hiding are necessary, or whether the system should continue on its task. We integrated our risk-based triggering mechanism into a delivery rover that is being attacked by a drone and evaluated its effectiveness through systematic testing in a simulated environment in Robot Operating System (ROS) and Gazebo, with a variety of different randomly generated conditions. We compared the use of the triggering mechanism and different configurations of self-preservation behaviours to not having any of these. Our results show that triggering self-preservation increases the distance between the drone and the rover for many of these configurations, and, in some instances, the drone does not catch up with the rover. Our study demonstrates the benefits of embedding risk awareness and self-preservation into autonomous systems to increase their robustness, and the value of using bio-inspired engineering to find solutions in this area.

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Modeling and Analyzing MAPE-K Feedback Loops for Self-Adaptation

Cited by 157 publications

References 24 publications

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

State of runtime adaptation in service‐oriented systems: what, where, when, how and right

Preparing for the Unexpected: Diversity Improves Planning Resilience in Evolutionary Algorithms

Risk-Based Triggering of Bio-inspired Self-preservation to Protect Robots from Threats

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