A generalized software framework for accurate and efficient management of performance goals

Hoffmann

Proceedings of the 36th International Conference on Software Engineering

2014

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121

123

Self-adaptation enables software to execute successfully in dynamic, unpredictable, and uncertain environments.Control theory provides a broad set of mathematically grounded techniques for adapting the behavior of dynamic systems. While it has been applied to specific software control problems, it has proved difficult to define methodologies allowing non-experts to systematically apply control techniques to create adaptive software. These difficulties arise because computer systems are usually non-linear, with varying workloads and heterogeneous components, making it difficult to model software as a dynamic system; i.e., by means of differential or difference equations. This paper proposes a broad scope methodology for automatically constructing both an approximate dynamic model of a software system and a suitable controller for managing its non-functional requirements. Despite its generality, this methodology provides formal guarantees concerning the system's dynamic behavior by keeping its model continuously updated to compensate for changes in the execution environment and effects of the initial approximation.We apply the methodology to three case studies, demonstrating its generality by tackling different domains (and different non-functional requirements) with the same approach. Being broadly applicable and fully automated, this methodology may allow the adoption of control theoretical solutions (and their formal properties) for a wide range of software adaptation problems.

“…Examples of this trend can be seen in research on control of web servers [44,50], data centers and clusters management [19,48], and operating systems [13,33,41,46,52,53].…”

Section: Related Workmentioning

confidence: 99%

Automated design of self-adaptive software with control-theoretical formal guarantees

Hoffmann

Proceedings of the 36th International Conference on Software Engineering

2014

Self Cite

121

123

“…Recent surveys capture the current state-of-the-art applying control-theory to software applications [17,46,58]-from controlling web server delays [38], to data service management [10], resource allocation [2,26,27,35], operating systems tuning [30,40,45], and energy management [25,41]. 1 http://www.martinamaggio.com/papers/fse17/ Some of these systems use automata-based formalisms to abstract software's behavior and temporal logic to specify some of its requirements [9,50], while we focus here on discrete-time control, where equation-based models are used to satisfy quantitative software properties.…”

Section: Related Workmentioning

confidence: 99%

Automated control of multiple software goals using multiple actuators

Papadopoulos

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

et al. 2017

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Modern software should satisfy multiple goals simultaneously: it should provide predictable performance, be robust to failures, handle peak loads and deal seamlessly with unexpected conditions and changes in the execution environment. For this to happen, software designs should account for the possibility of runtime changes and provide formal guarantees of the software's behavior. Control theory is one of the possible design drivers for runtime adaptation, but adopting control theoretic principles often requires additional, specialized knowledge. To overcome this limitation, automated methodologies have been proposed to extract the necessary information from experimental data and design a control system for runtime adaptation. These proposals, however, only process one goal at a time, creating a chain of controllers. In this paper, we propose and evaluate the first automated strategy that takes into account multiple goals without separating them into multiple control strategies. Avoiding the separation allows us to tackle a larger class of problems and provide stronger guarantees. We test our methodology's generality with three case studies that demonstrate its broad applicability in meeting performance, reliability, quality, security, and energy goals despite environmental or requirements changes.

“…For the given video encoding example, we can use the resources assigned to the application as an actuator [39,53]. We denote this value as speedup s(k).…”

Section: Devise the Modelmentioning

confidence: 99%

Software Engineering Meets Control Theory

2015 IEEE/ACM 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

Angelopoulos

et al. 2015

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Abstract-The software engineering community has proposed numerous approaches for making software self-adaptive. These approaches take inspiration from machine learning and control theory, constructing software that monitors and modifies its own behavior to meet goals. Control theory, in particular, has received considerable attention as it represents a general methodology for creating adaptive systems. Control-theoretical software implementations, however, tend to be ad hoc. While such solutions often work in practice, it is difficult to understand and reason about the desired properties and behavior of the resulting adaptive software and its controller.This paper discusses a control design process for software systems which enables automatic analysis and synthesis of a controller that is guaranteed to have the desired properties and behavior. The paper documents the process and illustrates its use in an example that walks through all necessary steps for self-adaptive controller synthesis.