Software Self-Adaptation

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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. Sousa
• Student Nikolaos Abatzis
• SWE796 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 (Moores 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

• Self-adaptation
• self-healing
• self-optimizing

• Causes of change
• requirements
• faults
• resources

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
  protocolCapra,2003
• everybody wins! Maximize the sum of bids received
• Microeconomics/distributed congestion
  pricingNeugebauer,2000
• each user is charged depending on the scarcity
  of the resource requested

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• 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.

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

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• Question
• Who, what, when, adapts the adapting mechanisms?

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• Thank You !!!
• Questions ???