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The Viable System Model

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Title: The Viable System Model


1
The Viable System Model CyberneticsRealizing
Self-Adaptive Software
School of Computing Mathematical Sciences
  • Andy Laws

2
Presentation Overview
  • Review the context and motivations for this work.
  • Summarize some related work in this area.
  • Outline the cybernetic foundations of our
    approach.
  • See where this has taken us so far.
  • Speculate on where these findings may take us in
    the future.

3
The Context
4
Software Engineering Considerations
  • The aim of Software Engineering has been
    described as
  • ...the systematic, principled, design and
    deployment of applications that fulfil softwares
    original promise - applications that retain their
    full malleability throughout their lifetime and
    that are as easy to modify in the field as they
    are on the drawing board. (Laddaga,1997)
  • In the thirty years since its establishment as a
    discipline many techniques have been introduced
    in pursuit of this goal, e.g.
  • structured programming - high-level languages- OO
    - process maturity etc. (Lehman, ) All require
    the software designer to predict every software
    circumstance and code to be provided to deal with
    the situation.
  • While significant improvements and highly
    successful have undoubtedly resulted, these
    efforts have failed to deliver on-going
    malleability and most software systems exhibit a
    growing fragility caused by continual adaptation
    to meet changing requirements.
  • There is growing evidence to suggest that it is
    time to reconsider the engineering and
    maintenance of software systems in a manner
    similar to physical products and that a more
    organic view of software should be adopted.

5
Coupled with this..
  • Over the last two decades, the development of raw
    computing power coupled with the proliferation of
    computing devices has grown exponentially.
  • The production of evermore complex, ambitious and
    connected systems distributed systems
    underpinned by internet developments
  • Such complexity strains the ability to adapt and
    maintain such systems manually in a timely manner
    yet they are required to be consistently
    available, highly-resilient, highly dependable
    etc.
  • Consequently, much recent attention has focused
    on devolving some of the responsibility for
    adaptive and evolutionary activities to the
    software itself.

6
Some Related Work
7
IBMs Autonomic Computing Approach
  • Inspired by the autonomic function of the human
    central nervous system. Such autonomic control
    regulates temperature, breathing, heart-rate etc.
    at a sun-conscious level.
  • Ideally, autonomic software systems will take
    care of the mundane elements of systems
    management themselves

8
Eight Characteristics of Autonomic Systems
  • Self-knowledge - Detailed knowledge of
    constituent components, current status etc.
  • Self-configuration/re-configuration - Adjustments
    to a changing environment
  • Self-optimizing - Monitor constituent parts and
    optimize accordingly
  • Self-healing - The ability to recover from
    malfunction
  • Self-protecting - Detect, identify and protect
    itself from attack
  • Environmentally aware know its environment, the
    context surrounding its activity and act
    accordingly
  • Co-operative Interact with other systems in a
    heterogeneous world open standards
  • Anticipatory anticipate and transparently
    implement the resources required to meet user
    goals

How these should be effectively structured is
still open to question.
9
A Cybernetic Approach
10
The Viable System Model
  • Beers VSM implements a control communication
    structure via hierarchies of homeostats (feedback
    loops)
  • 6 major systems ensure viability of the system
  • Implementation S1
  • Monitoring S2
  • Audit S3
  • Control S3
  • Intelligence S4
  • Policy S5
  • Offers an extensible, recursive, model-based
    architecture, devolving autonomy to sub-systems

Autonomic Systems
Anticipatory Self-awareness Deliberative
11
Recursion in the Model
  • Each System One is expected to develop as a VSM
    in its own right
  • Consequently, the model is re-produced in its
    entirety at each level
  • So this model contains further VSMs and is
    itself contained in a higher level VSM

12
Where this begins to get really interesting
  • The recursive nature of the underlying model
    suggests that each System One should develop as a
    Viable System Model in its own right.
  • If the recursion is pursued below the level of
    the human software team then we arrive at the
    level of the software system.
  • This strongly implies that the software system
    should assume the same overall management
    structure as the human software process
  • Consequently, we appear to have a theoretically
    supported management architecture for
    self-managing autonomic software

13
Bratman et als IRMA Architecture
  • Bratman et als Intelligent Resource-Bounded
    Machine Architecture (IRMA), a classic BDI agent
    model
  • It is noticeable that many of the elements
    contained in the model correlate directly to
    elements of the VSM
  • So
  • Planning Means-Ends Reasoning S3
  • Opportunity Analyser Filtering S4
  • Beliefs about the world S5
  • Desires and Deliberative Process S5
  • Intentions - S5 Policy passed to S3 for enactment
  • It is also apparent that some elements are
    missing for Viability

14
J-Reference Model
15
A Viable Intelligent Agent Architecture
  • Using Bratman et als IRMA approach and using the
    VSM as a reference model, we designed a Viable
    Intelligent Agent Architecture realizable using a
    multi-agent approach.
  • The design specifies, in some detail, the higher,
    deliberative processes of adaptation.
  • In some respects, the ready-mapping of existing
    IRMA components and the inclusion of viability
    components demonstrates the applicability of the
    VSM-based approach.

16
Perhaps more excitingly A Practical
ApplicationIn-Vehicle Telematics System (IVTS)
  • IVTS cover a broad range of computer-based
    systems, these may include or combine
  • Engine Management Systems
  • Drivers Information Systems
  • Vehicle Navigation Tracking Systems
  • Collision Avoidance Systems
  • Vehicle Security Systems
  • Using Jini Java RMI allows distributed
    applications to be developed as a series of
    clients that interact with application services
    via a look-up service.
  • The service-oriented abstraction considers a
    service as a logical concept that can be
    discovered dynamically by a client and used
    according to a contract of use

17
Monitoring Instrumentation Considerations
  • In order to debug, monitor and manage Jini
    applications, a dynamic instrumentation system,
    based again on Jini technology has been developed
  • Uses
  • Monitor service - connects with an application or
    lookup service and observes dynamic parameters
  • Logger utility - invoked by a monitor to record
    data
  • Analyzer utility - invoked by a monitor to
    compute complex parameters
  • A Management Service creates and controls the
    monitor service
  • The instrumentation system is implemented by
    combining Jinis
  • code mobility capabilities
  • Javas dynamic proxies
  • Jinis event models
  • To apply instrumentation
  • the management service requests the application
    service to set an instrumented parameter
  • The Look-up service monitor detects a change of
    state and notifies client
  • Management service wraps service in monitor
    service and sends proxy to client

18
Some Implications and Final Comments
  • The complete realization of a self-adaptive
    autonomic software system using the conceptual
    guidance of classical cybernetics and the VSM
    still has some way to go. Indeed, it isnt yet
    clear that full realization is possible and there
    are still many problems outstanding.
  • Nevertheless, the approach offers a recursive
    generalized architecture from human software team
    to self-managing software systems
  • However, the inclusion of the anticipatory and
    deliberative (Systems 4 and 5) systems appear to
    offer a step forward from purely autonomic
    systems. Of course, this brings its own problems
    environmental modelling ?
  • Nevertheless, using off-the-shelf technology that
    does not necessarily reflect this viewpoint
    exactly has allowed us to make significant
    progress and indicates that this approach may
    supply a ready-made theoretical underpinning for
    such software systems.

19
Speculations on further applications
  • Without wishing to impinge on the following
    speakers domain
  • The Grid
  • Perhaps applicable as an architecture for
    sustainable, viable virtual grid-like systems?
  • E-Science
  • A similar requirement for viable, adaptive
    structures?

20
Thanks Any Questions?
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