Reliability-driven dynamic binding via feedback control

Filieri, Antonio; Ghezzi, Carlo; Leva, Alberto; Maggio, Martina

doi:10.1109/seams.2012.6224390

Cited by 18 publications

(30 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Being able to take into explicit account the controller's logic could provide valuable insights about the dependence of the problematic behaviors not just on the workload but also on specific properties of the resource allocation strategy. This could support the automatic generation of controllers specifically tailored to elastic systems, extending our previous work [7,8].…”

Section: Discussionmentioning

confidence: 56%

Iterative test suites refinement for elastic computing systems

Gambi

Filieri

Dustdar

2013

Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering

Self Cite

View full text Add to dashboard Cite

Elastic computing systems can dynamically scale to continuously and cost-effectively provide their required Quality of Service in face of time-varying workloads, and they are usually implemented in the cloud. Despite their wide-spread adoption by industry, a formal definition of elasticity and suitable procedures for its assessment and verification are still missing. Both academia and industry are trying to adapt established testing procedures for functional and nonfunctional properties, with limited effectiveness with respect to elasticity. In this paper we propose a new methodology to automatically generate test-suites for testing the elastic properties of systems. Elasticity, plasticity, and oscillations are first formalized through a convenient behavioral abstraction of the elastic system and then used to drive an iterative test suite refinement process. The outcomes of our approach are a test suite tailored to the violation of elasticity properties and a human-readable abstraction of the system behavior to further support diagnosis and fix.

show abstract

Section: Discussionmentioning

confidence: 56%

Iterative test suites refinement for elastic computing systems

Gambi

Filieri

Dustdar

2013

Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…The controller is synthesized to achieve the desired reliability and performance, while minimizing the cost due the selection of higher service levels. We considered the problem of dynamic binding in previous work, controlling only a single objective with a single knob [7,64]. Here we provide a solution to the multi-objective problem.…”

Section: Multi-objective Service Dynamic Bindingmentioning

confidence: 99%

Automated multi-objective control for self-adaptive software design

Filieri

Hoffmann

Maggio

2015

Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering

Self Cite

View full text Add to dashboard Cite

While software is becoming more complex everyday, the requirements on its behavior are not getting any easier to satisfy. An application should offer a certain quality of service, adapt to the current environmental conditions and withstand runtime variations that were simply unpredictable during the design phase. To tackle this complexity, control theory has been proposed as a technique for managing software's dynamic behavior, obviating the need for human intervention. Control-theoretical solutions, however, are either tailored for the specific application or do not handle the complexity of multiple interacting components and multiple goals. In this paper, we develop an automated control synthesis methodology that takes, as input, the configurable software components (or knobs) and the goals to be achieved. Our approach automatically constructs a control system that manages the specified knobs and guarantees the goals are met. These claims are backed up by experimental studies on three different software applications, where we show how the proposed automated approach handles the complexity of multiple knobs and objectives.

show abstract

“…Different approaches in the literature for developing adaptive systems range from those that adopt a prominently control-theoretic perspective [14], to others that employ requirements [15,16,17], or architecture models [1,18,19] to reason about the best way to adapt the target system at run-time.…”

Section: Related Workmentioning

confidence: 99%

Incorporating architecture-based self-adaptation into an adaptive industrial software system

Cámara

Correia

Lemos

et al. 2016

Journal of Systems and Software

View full text Add to dashboard Cite

Complex software-intensive systems are increasingly relied upon for all kinds of activities in society, leading to the requirement that these systems should be resilient to changes that may occur to the system, its environment, or its goals.Traditionally, resilience has been achieved either through: (i) low-level mechanisms embedded in the implementation (e.g., exception handling, timeouts, redundancies), which are unable to detect subtle but important anomalies (e.g., progressive performance degradation); or (ii) human oversight, which is costly and unreliable. Architecture-based self-adaptation (ABSA) is regarded as a promising approach to improve the resilience and reduce the development/operation costs of such systems. Although researchers have illustrated the benefits of ABSA through a number of small-scale case studies, it remains to be seen whether ABSA is truly effective in handling changes at run-time in industrialscale systems. In this paper, we report on our experience applying an ABSA framework (Rainbow) to a large-scale commercial software system, called Data Acquisition and Control Service (DCAS), which is used to monitor and manage highly populated networks of devices in renewable energy production plants. In 4 Critical Software, Portugal. Preprint submitted to Journal of L A T E X Templates December 28, 2014Submitted for publication the approach followed, we have replaced some of the existing adaptive mechanisms embedded in DCAS by those advocated by ABSA proponents. This has allowed us to assess the development costs associated with the reengineering of adaptive mechanisms when using an ABSA solution, and to make effective comparisons, in terms of operational performance, between a baseline industrial system and one that uses ABSA. Our results show that using the ABSA concepts as embodied in Rainbow enabled an independent team of developers to: (i) effectively implement the adaptation behavior required from such industrial systems; and (ii) obtain important benefits in terms of maintainability and extensibility of adaptation mechanisms.

show abstract

Reliability-driven dynamic binding via feedback control

Cited by 18 publications

References 16 publications

Iterative test suites refinement for elastic computing systems

Iterative test suites refinement for elastic computing systems

Automated multi-objective control for self-adaptive software design

Incorporating architecture-based self-adaptation into an adaptive industrial software system

Contact Info

Product

Resources

About