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

SWE Spring ‘082  Introduction  Why change? causes  Change what? effects  Choices, choices …  Are we there yet?

SWE Spring ‘083 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

SWE Spring ‘084 Change drives adaptation Causes of change requirements faults resources Self-adaptation self-healing self-optimizing not trivial !

SWE Spring ‘085 Change drives adaptation Causes of change requirements faults resources Self-adaptation self-healing self-optimizing

SWE Spring ‘086 Different focus based on change handled

SWE Spring ‘087  What is a resource? “simple”, i.e. CPU, energy, network bandwidth service, i.e. speech recognition composite service, i.e. speech-to-speech

SWE Spring ‘088 Effects of change  Software parameters (fidelity)  Algorithms, switch the executing code  redeployment of components  Use of resources  Services

SWE Spring ‘089 different models & mechanisms,

SWE Spring ‘0810

SWE Spring ‘0811 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

SWE Spring ‘0812 Control loop for self-* systems Autonomic Computing: An architectural blueprint for autonomic computing, IBM, June 2006 (Fourth Ed.).

SWE Spring ‘0813 Adaptation at different levels Autonomic Computing: An architectural blueprint for autonomic computing, IBM, June 2006 (Fourth Ed.).

SWE Spring ‘0814 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]

SWE Spring ‘0815 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]

SWE Spring ‘0816

SWE Spring ‘0817 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]

SWE Spring ‘0818 Model of the system  Contained within each runtime component, autonomous [Georgiadis+, 2002]

SWE Spring ‘0819

SWE Spring ‘0820 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

SWE Spring ‘0821 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

SWE Spring ‘0822

SWE Spring ‘0823  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]

SWE Spring ‘0824  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

SWE Spring ‘0825  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.

SWE Spring ‘0826 Question: Who, what, when, adapts the adapting mechanisms?

SWE Spring ‘0827 Thank You !!! Questions ???