CSC 591 - Analysis and Control of

Computing SystemsComputing SystemsNorha M. VillegasFirst year PhD StudentInstructor: Prof. Dr. Hausi MüllerComputer Science Department

Agenda

• Dynamic computing systems and control theory overview

• Course overview

• Application of control theory to the control of dynamic

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• Application of control theory to the control of dynamic computing systems

• The application of control theory to the engineering of software systems

• Challenges ahead

• Summary and final remarks

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Dynamical Computing Systems

• Are highly dependent on the environment

▫ external context

▫ the computing system itself (internal context)

• Outputs depend on the system’s state

• The execution environment is not fully known in advance

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• The execution environment is not fully known in advance (design-time)

• Some design decisions must be pushed to run-time

• The system requires capabilities to reason about its own state and environment

• Are subject to continuous evolution▫ should be under constant development

▫ can never be fully specified

▫ require continuous adjustments and re-configuration

Complexity of Dynamic Computing Systems

The simultaneous explosion of information and integration of technology, and the continuous

evolution to Ultra Large Scale System

The proliferation of smart and context-aware applications, user centric-

services and ubiquitous environments

Software systems must become more versatile,

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The necessity of satisfying software requirements by regulating complex

and decentralized systems

The high dependency between changing business objectives and

software systems

become more versatile, flexible, resilient, self-

healing, configurable and optimizing

Bohem: A view of the 20th and 21st century of software engineering (2006); Northrop et al.: Ultra-large-scale systems – The software challenge of the future (2006)

Application of Control Theory

• Control theory is about addressing the dynamic nature of systems

▫ By regulating their dynamic characteristics

• Feedback control uses measurements of a system’s outputs to address specified goals

• Almost every automatic system implements feedback control

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• Almost every automatic system implements feedback control

• A feedback loop is the model used to automate the control of dynamic systems

Feedback loops are valuable for regulating the accomplishment of business level objectives through the regulation of computing and

software systems’ requirements, under uncertain and dynamic conditions

Controlling Dynamic Computing systems

Regulating the accomplishment of requirements and

Planning

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SymptomsPlans

requirements and business level

objectives, keeping the system

equilibrium

Execution

Monitoring

Analysis

Observations

Relevant ContextFeedback loops provide generic mechanisms for supporting the adaptation process of

dynamic systems: monitoring, analysis, planning and execution

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Learning Objectives

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To Explore the design and evolution of dynamic computing systems, as well as, the application of techniques for instrumenting existing software systems to monitor

and control their dynamic behaviourand control their dynamic behaviour

To understand the foundations of control

theory and the implications for their application to the monitoring, analysis, and

control of dynamic computing systems

To analyze existing control-based reference models,

reference architectures and software techniques

applicable to the control of dynamic software systems

To identify challenges related to the application of

control engineering to software engineering of

dynamic systems

Course Outline• Section 1: Feedback control of computing

systems▫ Introduction▫ Modeling and system identification▫ Input-output relationships▫ System modeling with block diagrams▫ Controllers, control analysis, and control

design

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design▫ State-space modelling

• Textbook: Hellerstein, J.L., Diao, Y., Parekh, S., Tilbury, D.M.: Feedback control of computing systems. John Wiley & Sons (2004)

• Hellerstein’s course – University of Washingtonhttp://research.microsoft.com/en-us/um/people/liuj/cse590k2008winter/default.aspx

Course Outline• Section 2: Application of control

engineering to software engineering

▫ Application steps

▫ Describing software systems in terms of control theory foundations

▫ Modeling the relationship between the

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▫ Modeling the relationship between the control input and measured output in software systems

▫ Designing software controllers

▫ Assessment

• Available on ConneX: https://connex.csc.uvic.ca/portal/site/eac7abb3-27a0-4a53-be0f-10525cabe46e?panel=Main

Foundations of control theory and feedback loops applied to

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Foundations of control theory and feedback loops applied to computing systems

Control System ArchitectureA SISO feedback control system

The goal: achieve a measured output according to the

control objectives (reference input)

Should be designed to

achieve the goal

Is dynamically changed to achieve

• Reference input: control objective

• Measured output: compared to the reference input

• Control error: difference between the reference input and the measured output

• Control input: signal(s) to affect the target system looking for a measured output closer to the reference input

• Disturbances and noise: affect the measured output

• Transducers: adapt signals for comparison

J. L. Hellerstein, Y. Diao, S. Parekh, and D. M. Tilbury, Feedback Control of Computing Systems. John Wiley & Sons. (2004)

changed to achieve the goal

Feedback Loops: examples from Nature

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Source: http://susty.com/tag/global-climate-change-feedback-loops/

Positive Feedback Loop: Global Warming �

http://www.anselm.edu/homepage/jpitocch/genbio/organizationnot.html

Homeostasis: + and – feedback loops to keep the equilibrium in the internal environment ☺

Control Objectives and Model Construction

• Controllers are designed for a specific purpose: control objective

• Three main control objectives strategies

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Strategy Name Description

Regulatory control Ensures that the measured output is as close as possible to the reference input

Disturbance rejection Controls the effects of disturbances on the measured output

Optimization Obtains the best value of the measured output (when the control input is not known in advance)

Control Objectives and Model Construction

• Modeling the input-output relationships of the target system

• It is crucial for controller design

• Hellerstein’s book focuses on modeling

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• Hellerstein’s book focuses on modeling techniques (mainly linear system theory) and their application to computing systems (queuing theory)

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In a feedback control the desired output is achieved by specifying the reference input (directly) instead of by manipulating the control input (indirectly)(indirectly)

The challenge: designing controllers to achieve the desired outputs

Properties of Control Systems Relevant for

Computing Systems

Stability AccuracyShort

SettlingSmall

Overshoot

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• Bounded inputs, bounded outputs

• Stable in operating regions

• Bounded inputs, bounded outputs

• Stable in operating regions

• The output converges to the reference input

• Control objectives are met

• The output converges to the reference input

• Control objectives are met

• Quick convergence

• Before the workload changes

• Quick convergence

• Before the workload changes

• Objectives achievement minimizing overshoot

• Caring of system degradation

• Objectives achievement minimizing overshoot

• Caring of system degradation

J. L. Hellerstein, Y. Diao, S. Parekh, and D. M. Tilbury, Feedback Control of Computing Systems. John Wiley & Sons. (2004)

Analyzing Control Properties: an unstable control

system

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Reference input0.5

CPU

utilization

Accuracy and small overshot are not

observed

• An improperly designed controller

• This feedback system is unstable: the controller overreacts to the CPU utilization

timeOpen loop Controller on

Analyzing Control Properties: a stable control

system

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Steady error -1rss-yss

Accuracy

Steady State

Stability

Short settlingMaximum overshoot

Initial Reference input 0.0

Reference inputSteady value 2.0

Settling time

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How to apply control engineering to the control of dynamic software systems, where the target system is not a physical system?

How to apply hybrid approaches (continuous and discrete) to the design of software controllers?

Issues in Controlling Dynamic Software Systems

Controllability

• Related to the properties of control systems

Observability

• Determination of the system’s state from measurements of the system

Stability

• Disturbances do not affect the system equilibrium

Robustness and efficiency

Autonomy

• Self-adaptive

Generality

• Knowledge bases should

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efficiency

• The controller’s ability to achieve the objectives even in larger environments

• Minimizing cost

• Self-adaptive• Self-configuring• Self-*

• Knowledge bases should evolve by incorporating new knowledge

Chattering

• Controlling the adaptation on state boundaries

• System performance

Scheduling and Efficiency

• Control the interactions and effects among multiple loops

Proactive reconfiguration

• Anticipating changes in the environment

• Prediction models

Passino, K. and Burgess, K.: Stability analysis of discrete event systems. John Wiley & Sons. (1998)

Identified Application Steps

Defining software control objectives

Describing the software system in

terms of control theory elements

Modeling the relationship between the control input and the measured output

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Designing the controller in terms of software components

Evaluating the control system (assessment)

Identified Application Dimensions

• Describing the software system in terms of control theory elements . Improving visibility of control in software systems

• Designing controllers in terms of software components• Control-based reference models, architectures, and patterns

• Describing the software system in terms of control theory elements . Improving visibility of control in software systems

• Designing controllers in terms of software components• Control-based reference models, architectures, and patterns

Software Design and Architectural perspective

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• Characterization of software components’ properties• Identification of variables and signals: properties to be

measured • Modeling the impact of control inputs on measured outputs

• Characterization of software components’ properties• Identification of variables and signals: properties to be

measured • Modeling the impact of control inputs on measured outputs

Model Definition (controller design)

• Simulation mechanisms to identify control parameters• Dynamic representation and management of control objectives• Dynamic monitoring mechanisms• Implementation of actuators and effectors• Controller complexity and trade-offs

• Simulation mechanisms to identify control parameters• Dynamic representation and management of control objectives• Dynamic monitoring mechanisms• Implementation of actuators and effectors• Controller complexity and trade-offs

Instrumentation

Engineering of Dynamic Software Systems

• The application control theory to software engineering requires:▫ Models and architectures to guide the design of controllers to

achieve dynamic system properties

▫ Explicit definition of feedback loops, their elements, and the

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▫ Explicit definition of feedback loops, their elements, and the interactions among them

▫ Dynamic management of control objectives

▫ Dynamic monitoring of internal and external context

▫ Dynamic adaptation of systems

Villegas, N.M., Müller, H.A., Tamura, G., Duchien, L., Casallas, R.: A Control Engineered Reference Model for Context-Based Self-Adaptation (2010)

Making Feedback Loops Explicit

• As feedback loops use to be hidden, there currently exists no explicit methods for analysis, validation, and verification of control mechanisms in dynamic software systems.

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• The explicitness of the feedback loops, their interactions and individual elements, renders the software reference models, architectures and designs, as analyzable, assessable and comparable software artifacts

Application of Feedback loops• Application of control theory to the engineering of dynamic software

and computing systems

• Feedback loops provide the generic mechanism for self-adaptation (collect, analyze, decide and act)

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SISO feedback control block diagram with explicit functional elements and corresponding interactions to control dynamic adaptation in a software system

Villegas, N.M., Müller, H.A., Tamura, G., Duchien, L., Casallas, R.: A Control Engineered Reference Model for Context-Based Self-Adaptation. (2010)

The Self-Controller Software Model

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Kokar, M.M., Baclawski, K., Eracar, Y.A..: Control Theory-Based Foundations of Self-Controlling Software (1999)

Feedback Control Architecture for Adaptive

Systems

• The control explicitness exposes obligations that fall on activities of design and development

• Design▫ Identification of control and

data elements▫ Control representation

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▫ Control representation▫ Selection of adaptation and

monitoring strategies• Analysis/V&V

▫ Validation of models and actuation plan

▫ Map the plan to available commands

• Implementation▫ Map from elements of design

to elements of implementation

Feedback control architecture proposed by Mary Shaw. Dagstuhl Seminar (2007)

Müller, H.A., Pezzè, M., Shaw, M.: Visibility of Control in Adaptive Systems (2008)

The Autonomic Element (MAPE-K loop)

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Kephart, J. O. and Chess: The vision of autonomic computing. (IBM - 2003)

Our Proposed Control-Based Reference Model

• Improving engineering of dynamic systems by making explicit:▫ Dynamic properties as

the control reference goals

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goals

▫ Separation of concerns among multiple feedback loops (at least three)

▫ Context management as an independent feed-back loop

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Definition and execution of the

Gathering and symptoms inference

Context Control Objectives

(from system control objectives)

Deciding about context manager

adaptation

Sensing and Preprocessing

Context management infrastructure

execution of the adaptation plan

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Provides context control

objectives

System’s context to support adaptation

monitoring

Enables objectives manager to decide about changes in control objectives

Supports the system adaptation

(context provisioning)

Our Reference Architecture for Control-Based Dynamic

Monitoring in SOA Governance

• Derived from our control-based reference model

• Applicable to the automation of run-time and change-time governance

• To assist the design and

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• To assist the design and implementation of monitoring infrastructures able to:▫ Monitor relevant context

▫ Support the dynamic adaptation of business objectives

▫ Self-configure

Norha M. Villegas and Hausi A. Müller: Context-Driven Adaptive Monitoring for Supporting SOA Governance. (2010 )

Study Case: Governance Feedback Loops for Supporting

Dynamic SOA Governance

• An initial SLA between HotelNearbyFacilities and ShoppingFacilitiesBrokerA▫ 10 transactions/second in

summer days

▫ 5 transactions/second for the remainder of the year

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remainder of the year

• ShoppingFacilitiesBrokerAcomposes services from different providers

• One SLA is defined between each shopping broker and each boutique

• On SLA violation, the infrastructure must support dynamic SLA negotiation

Norha M. Villegas and Hausi A. Müller: Context-Driven Adaptive Monitoring for Supporting SOA Governance. (2010 )

• The concrete architecture for dynamic monitoring in SOA governance

▫ Software architecture for implementing a dynamic

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implementing a dynamic monitoring infrastructure based on feedback loops

Norha M. Villegas and Hausi A. Müller: Context-Driven Adaptive Monitoring for Supporting SOA

Governance. (2010)

Toward a broad application of control theory to the engineering

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Toward a broad application of control theory to the engineering of dynamic software systems

Control-Based Design and Control Objectives

• Categorizing control-based architectural patterns for dynamic software systems

• With respect to control objectives

▫ How to identify control objectives in software systems?

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▫ How to identify control objectives in software systems?

▫ How to dynamically get the reference inputs related to the software control objective?

▫ How to represent software control objectives in such a way the can be processed and regulated at run-time?

▫ From the perspective of software requirements, how to elicit and specify control objectives?

Model Definition• The dynamic behaviour of computing and software systems must be

modeled to be controlled

• The relationships between control inputs and measured outputs

• Model variables and signals (variables that change over time)

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First-principle models

Mechanical and electrical

systems: e.g., Newton Laws

For computing systems: e.g.,

queuing relationships

Black-box models

Model scope (considered inputs and outputs)

Experimental design

(collecting data to estimate

model parameters)

Parameter estimation

Model evaluation

Until now, more applicable to Software Engineering

Support for Instrumentation

• Control-based design and architectural patterns

• Domain-specific languages, programming and specification languages (e.g., UML profiles for control-based software engineering)

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based software engineering)

• Software engineering frameworks that incorporate control engineering principles and techniques (e.g., monitors, controllers as filters, transducers)

Summary and Final Remarks

• I gained a deep insight of control engineering and its application to computing and software systems▫ The exploration and analysis of software systems from a control engineering

perspective, beyond controlling specific variables (e.g., performance, throughput)

▫ Not many documented contributions are available

• We designed, developed, and documented a valuable course that will be

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• We designed, developed, and documented a valuable course that will be available for the CSC Department. Control engineering provides important elements for the engineering of software systems

• The contribution is not only for CSC-Uvic, but for the adaptive software engineering community in general (e.g., ADAM team – Inria Nord Europe).

• Many opportunities have been identified for the improvement of software engineering for dynamic systems (from academia, research and industry), through the broad application of control engineering

• Other results▫ Two papers: 1 submitted to MESOA 2010. 1 will be submitted to SEAMS 2011

▫ Proof of concept: 1 demo for CASCON 2010 (tentative)

Thank you!

•Questions?

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Norha Villegas

nvillega@cs.uvic.ca

http://webhome.csc.uvic.ca/~nvillega/

Skype: norha.villegas