software self-adaptation a survey of the field “self-adaptive software evaluates its own behavior...

Software Self-Adaptation

A survey of the field

“Self-adaptive software evaluates its own behavior and changes behavior when the evaluation indicates it is not accomplishing what the software is intended to do, or when better functionality or performance is possible”.

- DARPA Broad Agency Announcement 98/12 -

Advisor: Prof. J.P. SousaStudent: Nikolaos AbatzisSWE796 – Spring 2008

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Introduction Why change? causes Change what? effects Choices, choices … Are we there yet?

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need for runtime change timescale for change complexity mobility - we must take account of the

environment (embedded systems are majority of systems around ~98%)1

enabler for change capability (Moore’s law)

1 Robertson, P., Laddaga, R. and Shrobe, H., Introduction: The First International Workshop on Self-Adaptive Software, Oxford UK 2000

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Change drives adaptation

Causes of change

•requirements

•faults

•resources

Self-adaptation

•self-healing

•self-optimizing

not trivial !

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Change drives adaptation

Causes of change

•requirements

•faults

•resources

Self-adaptation

•self-healing

•self-optimizing

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Different focus based on change handled

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What is a resource? “simple”, i.e. CPU, energy, network

bandwidth service, i.e. speech recognition composite service, i.e. speech-to-speech

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Effects of change

Software parameters (fidelity) Algorithms, switch the executing code redeployment of components Use of resources Services

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different models & mechanisms,

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process control loops

feedback loop

Shaw, M., Beyond Objects: A software design paradigm based on process control, in ACM Software Engineering notes, 20(1), January 1995, 27-38

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Control loop for self-* systems

Autonomic Computing: An architectural blueprint for autonomic computing, IBM, June 2006 (Fourth Ed.).

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Adaptation at different levels

Autonomic Computing: An architectural blueprint for autonomic computing, IBM, June 2006 (Fourth Ed.).

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architecture-based self-adaptation

Model composed of components & connectors Specific to C2, Weaves [Oreizy+, 1999] Architecture is generic, reusable adaptation

mechanism [Garlan+, 2004] Mechanisms for adaptation based on

Knowledge, potential to adapt the mechanism itself [Georgas+, 2004]

Self-adaptation language, Stitch [Cheng+, 2007] Hierarchical parallel finite state machines (HFSM)

[Karsai+, 2001]

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architecture of self-adaptation

peer-to-peer, aggregator-escalator-peer, Chain-of-configurators (Chain-of-responsibility pattern, Visitor pattern) [Hawthorn+, 2005]

Evaluation using ABAS [Neti+, 2007]

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No model of the system per se Agent transfers internal state, Port-Based

agents [Dixon+,2000] Use an adaptation automaton to map old

process states to new states [Biyani+,2007]

Agents dynamically change commitments which puts them in specific roles, situated (in an environment) multiagent systems (MAS) [Weyns+,2007]

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Model of the system Contained within each runtime

component, autonomous [Georgiadis+, 2002]

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search solutions – random & centralized control

population-based model Mechanisms: crossover, mutation, selection,

fitness Genetic algorithms [Whitley, 1994]. Genetic

programming, use algorithms to generate programs! [Poli+,2008]

Evolution platform – AVIDA [Golsby+,2007] Generate state diagrams for processing

components

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compose a solution, distributed

Cell inspired no specific model simple “instructions” local communication

Cell automata [George+, 2002] shows self-healing, very low-level

Cell inspired agents [Nagpal+, 2003] Self-assembly, computational synthesis

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Managing a resource at the O/S level conserve energy by adapting the fidelity of the

data presented to an application (Odyssey)[Flinn+,1999]

Managing multiple resources Maximize a utility function for a user executing

one or more tasks given available resources and their QoS, Environment Manager – Aura [Sousa+,2003]

Choice of runtime execution platform, given bandwidth, CPU, memory and energy considerations, tactics – Chroma [Balan+,2003]

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Managing multiple users Microeconomics/centralized – auction

protocol[Capra+,2003] everybody wins! Maximize the sum of bids received

Microeconomics/distributed – congestion pricing[Neugebauer+,2000] each user is charged depending on the “scarcity” of

the resource requested

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Many promising approaches exist, bringing tools from control theory, biology, economics, utility theory, artificial intelligence, etc.

Causes of change

•requirements

•faults

•resources

Self-adaptation

•self-healing

•self-optimizing

System complexity, environment, embedded systems have to deal with change. They need to adapt to it.

Adapting topology, resource usage, fidelity. No on-the-fly application modification, not yet anyways.

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Question: Who, what, when, adapts the adapting

mechanisms?

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Thank You !!!

Questions ???