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    “A collection of application services spread over networked computers, which clients use remotely via middleware services”
    Application services: represent physical and logical concepts such as a printer (hardware service) and a chat room (software service)
    Middleware services: bridge the gap between application services and network operating system to make life easier for application programmers including; Lookup, transaction, remote-event, etc.
    1-reflection techniques are similar to self-adaptive software but self-adaptation exceeds the capabilities of reflection.
    (“ reflection can modify themselves at run time and change their behaviours but it can’t determine when and what the program needs to modify itself in run time”)
    2- one of the key architecture concepts for self-adaptive software is a “reconfiguration “ which refer to a system that switches the control regime based on the runtime situation
    3-As a new modelling paradigm self-adaptive software approaches provides two interactions; namely feedforward process from model to the executable and feedback process from execution to reconfiguration
    4- it generalize software engineering as its adaptive control in the sense that the system will switch to a different algorithm when the environment changes.
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  • ppt

    1. 1. Prof. A. Taleb-Bendiab, talk: WO, Conference: ICIES’05, Miami, Date:Prof. A. Taleb-Bendiab, talk: WO, Conference: ICIES’05, Miami, Date: 01/28/1501/28/15, Slide:, Slide: 11 A Machine Learning Middleware Service for On- Demand Grid Services Engineering and Support Prof. A. Taleb-BendiabProf. A. Taleb-Bendiab School of ComputingSchool of Computing Liverpool John Moores UniversityLiverpool John Moores University email:email: a.talebbendiab@livjm.ac.uka.talebbendiab@livjm.ac.uk http://www.cms.livjm.ac.uk/talebhttp://www.cms.livjm.ac.uk/taleb http://www.cms.livjm.ac.uk/Self-http://www.cms.livjm.ac.uk/Self-XX
    2. 2. ScopeScope  Situated Autonomic ComputingSituated Autonomic Computing  Problem Definition - ChallengesProblem Definition - Challenges  Design including; coordination and controlDesign including; coordination and control  model-based vs emergencemodel-based vs emergence  Specification of control modelsSpecification of control models  Design via experimentation and machine learningDesign via experimentation and machine learning  Example – on-demand reservation ofExample – on-demand reservation of application servicesapplication services  User Classification scenarioUser Classification scenario  Episodic resource requirementsEpisodic resource requirements  SOM Classification for Connected HomeSOM Classification for Connected Home MachineMachine  ImplementationImplementation  Case-studyCase-study
    3. 3. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 3 Situated AC Scenario: E-FireSituated AC Scenario: E-Fire ServicesServices
    4. 4. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 4 Challenges -- Global ComputingChallenges -- Global Computing  Global Enterprise SystemsGlobal Enterprise Systems  High-assurance systems development and life-High-assurance systems development and life- time managementtime management  Complexity and scale is rapidly increasingComplexity and scale is rapidly increasing  Bio-inspired Models -- AutonomyBio-inspired Models -- Autonomy  devolving software management, maintenance todevolving software management, maintenance to the software itselfthe software itself  Self-managing, self-tuning, self-protecting, ...Self-managing, self-tuning, self-protecting, ...  Need continuous measurement, introspectionNeed continuous measurement, introspection to supportto support  Observed and/or supervised adaptation for;Observed and/or supervised adaptation for;  Safe, predictable,Safe, predictable,  Coordinated, traceable, etc.Coordinated, traceable, etc.
    5. 5. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 5 So far …!So far …!  Current researchCurrent research  Instrumentation middleware services forInstrumentation middleware services for  improved usability and reliability for instance forimproved usability and reliability for instance for  grid-based applications, and ubiquitousgrid-based applications, and ubiquitous computingcomputing  Monitor, control and manage grid users’ applications.Monitor, control and manage grid users’ applications.  Context-awareness and QoS-Aware systemsContext-awareness and QoS-Aware systems  Event-based systemsEvent-based systems  Sensor networks, Etc.Sensor networks, Etc.  Further research is requiredFurther research is required  Management, assurance and fidelity of awarenessManagement, assurance and fidelity of awareness layer is a major concernslayer is a major concerns  Sensors and actuators (effectors) support webSensors and actuators (effectors) support web services and grid computingservices and grid computing  Current models looking at small scale systemsCurrent models looking at small scale systems
    6. 6. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 6 Design Approach Informed byDesign Approach Informed by Machine LearningMachine Learning  Frameworks and ModelsFrameworks and Models  Programming, interaction and/or controlProgramming, interaction and/or control models.models.  Two experiments were conductedTwo experiments were conducted  User Classification and on-demand serviceUser Classification and on-demand service reservationreservation  Autonomic software restore serviceAutonomic software restore service
    7. 7. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 7 Experiment #1: User ClassificationExperiment #1: User Classification  The scenarioThe scenario  Mining service usage models per class ofMining service usage models per class of users for preemptive service reservation andusers for preemptive service reservation and on-demand serviceson-demand services  MethodMethod  Developed an Simulation tool for IntelligentDeveloped an Simulation tool for Intelligent Connected Home, which generate servicesConnected Home, which generate services  Self-Organising Maps (SOM) applied extractSelf-Organising Maps (SOM) applied extract feature or usage modelfeature or usage model  Design and ImplementationDesign and Implementation  To followTo follow
    8. 8. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 8 Design and ImplementationDesign and Implementation  Data generated tool is developed toData generated tool is developed to produce training and test data for thisproduce training and test data for this application.application.  An OGSA and web service compliantAn OGSA and web service compliant SOM middleware service wasSOM middleware service was developeddeveloped  For rapid prototyping a Matlab library forFor rapid prototyping a Matlab library for SOM is used for classificationSOM is used for classification
    9. 9. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 9 SOM Classification Results ForSOM Classification Results For Connected Home Machine DevicesConnected Home Machine Devices • Lights and PlayStationII correlates • Video and Coffee Machine correlates • Video CD and Fans correlates • Vacuum cleaner and Washing machine correlates
    10. 10. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 11 So WhatSo What??  Exploiting ML:Exploiting ML:  anticipate and organize the consumers’ requests inanticipate and organize the consumers’ requests in advanced.advanced.  Job schedule is responsible for managing theJob schedule is responsible for managing the invocations of the services.invocations of the services.  Just-in-time services invocation and usageJust-in-time services invocation and usage  Etc.Etc.  In addition to the presented ML middleware service withIn addition to the presented ML middleware service with automated inclusion and use of usage model for userautomated inclusion and use of usage model for user and service classificationand service classification  Further support is required including;Further support is required including;  Specification and modelling of mined models and theirSpecification and modelling of mined models and their enactment for instance;enactment for instance;  Control and/or actuation modelsControl and/or actuation models  Neptune Meta-Language and Integrated developmentNeptune Meta-Language and Integrated development environment will be used for this.environment will be used for this.
    11. 11. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 12 Neptune Meta-Language #1Neptune Meta-Language #1
    12. 12. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 13 Neptune Meta-Language #2Neptune Meta-Language #2
    13. 13. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 14 Neptune Meta-Language #3Neptune Meta-Language #3
    14. 14. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 15 Conclusions & Further WorkConclusions & Further Work  Prototypes developed using .Net and supportPrototypes developed using .Net and support Web Services StandardsWeb Services Standards  Tested in a number of case studiesTested in a number of case studies  Intelligent Connected HomesIntelligent Connected Homes  E-HealthE-Health  With PlanetLab environmentWith PlanetLab environment  Further workFurther work  Integration of this work with the Neptune Language toIntegration of this work with the Neptune Language to supportsupport  norm-governed web services and architectures.norm-governed web services and architectures.  Situated Autonomic middlewareSituated Autonomic middleware  Integration machine learning services to supportIntegration machine learning services to support danger/novelty detectiondanger/novelty detection  Further evaluation of the frameworkFurther evaluation of the framework
    15. 15. Prof. A. Taleb-Bendiab, Talk: WO, CSAC’05 Workshop, Conference: ICIES’05, Miami, Date: 01/28/15, Slide: 16

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