Feedback Control as MAPE-K Loop in Autonomic Computing

Abstract

Abstract:Computing systems are becoming more and more dynamically reconfigurable or adaptive, to be flexible w.r.t. their environment and to automate their administration. Autonomic computing proposes a general structure of feedback loop to take this into account. In this report, we are particularly interested in approaches where this feedback loop is considered as a case of control loop where techniques stemming from Control Theory can be used to design efficient safe, and predictable controllers. This approach is emerging, with separate and dispersed effort, in different areas of the field of reconfigurable or adaptive computing, at software or architecture level. This report surveys these approaches from the point of view of control theory techniques, continuous and discrete, in their application to the feedback control of computing systems, and proposes interpretations of feedback control loops as MAPE-K loop, illustrated with case studies.

A control-theory approach for cluster autonomic management: maximizing usage while avoiding overload

“…Control theory has been applied in High-performance Computing rather scarcely therefore it is still in need for basic research [3], [4], [5]. Most previous approaches propose rather simple linear models that, to our best understanding, lack the ability to reflect several nonlinear behaviors and variable constraints of the real system, since their accuracy is limited to a specific region of operation, failing to ensure the desired performance and stability objectives for all possible situations.…”

Towards a control-theory approach for minimizing unused grid resources

“…Recently, the perspectives of self-adaptive systems and autonomic management have also been considered in HPC. AC relies on a structure of feedback loop, where a controller, separate from the system to be managed, runs in parallel to it: the well known MAPE-K loop [4] involves components to Monitor (through probes and sensors), Analyze (extracting relevant information from data, and take decisions), Plan (transform decisions into adaptation actions) and Execute (perform adaptation actions). All this is done using Knowledge on the system (reified representation, data-base).…”

Autonomic Management of Reconfigurations in DPR FPGA-based Embedded System

“…Other perspectives are in co-ordination of multiple autonomic loops, switching controllers (integrating into the DSL schemes explored in another context [7]) ; modularity and hierarchical loops, both for re-use and to managed compilation complexity, and considering more ad-vanced discrete control features like logico-numeric properties [8] ; and integrating the DSL for Autonomic Managers into a global design process for FPGA-based applications. We also consider the general perspectives of basing Autonomic Management of Autonomic Computing systems on Control Theory [9,10].…”