Intelligent Coordination Design in Software Systems - PowerPoint PPT Presentation

Loading...

PPT – Intelligent Coordination Design in Software Systems PowerPoint presentation | free to download - id: 1dd204-ZDc1Z



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Intelligent Coordination Design in Software Systems

Description:

Intelligent Coordination Design in Software Systems. Srini Ramaswamy. Computer Science - UALR ... Intelligent Coordinating Entities. Structure: Uniform, ... – PowerPoint PPT presentation

Number of Views:13
Avg rating:3.0/5.0
Slides: 49
Provided by: srin75
Learn more at: http://www.cs.wayne.edu
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Intelligent Coordination Design in Software Systems


1
Intelligent Coordination Design in Software
Systems
  • Srini Ramaswamy
  • Computer Science - UALR
  • srini_at_acm.org/srini_at_ieee.org

Nothing endures but change Heraclitus
2
Analogy Snowflake symmetry
  • Growth in each arm affects the growth in other
    arms
  • Grow independently in a dynamic environment
    (rapidly varying temps, humidity, etc.)
  • Spatially homogenous for a single flake
  • Locally high level of visual similarity - Each
    arm responds in identical ways to identical
    conditions
  • Larger environmental scales ? lack of correlation
    between the shapes of different snowflakes
  • Locally homogeneous globally heterogeneous

3
Intelligent Coordinating Entities
  • Structure Uniform, scalable design
  • Behavior Localized decision-making behaviors,
    reinforced with
  • Dynamic aggregated learning models and
    information-sharing models
  • Uniform (locally homogeneous)
  • Symmetric (repeatable)
  • Well-defined Scalable
  • Vorticity Relies on a communication-centric
    framework

Simple, structured, well-defined coordinations
4
Major Topic Outline
  • Entity Modeling Design
  • Coordination Design
  • Multi-tiered Intelligent Control
  • Examples

A moments insight is sometimes worth a life
experience. Thomas Fuller
5
Practicality of Coordinated, Hierarchical
Abstractions
Slide adapted from Bernard P. Zeigler, Univ. of
Arizona
6
(No Transcript)
7
  • OO Encapsulation of resource (at some
    granularity) and its associated functions (strive
    for norms).
  • Needs
  • Service Interface Mechanism to publish service
    availability
  • Info. Sharing Interface Critical layer missing
    in current SOA
  • Major functions
  • Mechanisms to identify critical decisions for
    communication
  • Mechanisms to swiftly make a decision, apply
    reinforcement learning based validation support
    for evolutionary behaviors

8
(No Transcript)
9
Major Topic Outline
  • Entity Modeling Design
  • Coordination Design
  • Multi-tiered Intelligent Control
  • Examples

10
Learning from Biology (Symbiosis)
The major source of evolutionary novelty is the
acquisition of symbionts - the whole thing then
edited by natural selection i.e. Single-celled
creatures evolved by symbiosis. Dr. Lynn
Margulis
11
Factors to be Considered
  • Decision Complexity (selection)
  • From simple (atomic) to complex / aggregated
    decisions
  • Information Sharing Complexity (Symbionts)
  • Individually aggregated over time
    residual/reinforcement effect
  • In pockets, share info. with group appropriately

12
(No Transcript)
13
Key Premises
  • Ability for basic communication in every entity
  • Information transfer (on key decisions) forms
    the basis (need checks) for intelligent
    coordination
  • Sharing timely information regarding key
    decisions (time or response checks) defines
    successful coordinations between entities
  • Other application / domain dependent factors
    Usability, reliability, availability (-bility
    checks)

14
(No Transcript)
15
Basic Communication Strategies
  • Techniques
  • Peer to peer, full or selective broadcasts
  • Selective broadcasting introduced in
  • B. T. Barcio, S. Ramaswamy, K. S. Barber, "An
    Object Oriented Model Based Approach to Software
    Systems Development", 1995 ASQC Intnl. Conference
    on Software Quality, Oct. 1995
  • B. T. Barcio, S. Ramaswamy, K. S. Barber, "An
    Object-Oriented Modeling and Simulation
    Environment for Reactive Systems Development",
    International Journal of Flexible Manufacturing
    Systems, Volume 9, No. 1, Jan 1997, pp. 51-80

16
Basic Communication Strategies
  • Issue Determine what needs to be communicated
  • Base case
  • Normal (equilibrium state) a priori defined
    normal states system designed
  • Information pertaining to errors / critical
    decision choices needs to be communicated
  • Dynamic evolution
  • Allow for emergent behavior

17
Needs for Info. Sharing Design
  • Increased decisions ? increased design
    complexity
  • Software design quirks also lurk in corners and
    problems normally appear due to insufficient
    testing and monitoring at the seams
  • Seams may be deep and nested
  • Information about nested decision choices
    embedded at these seams are critical to designing
    good information sharing systems (apply
    hierarchy locks to define security / sharing
    privileges in hierarchical abstractions)
  • Petri Net transition invariants - an useful means
    for enabling coordinations

18
Using Petri Net Invariants Reader's Writer's
Problem (Readers)
P1
P3
T3
T1
2
P4
P2
P5
2
T4
T2
19
Petri Net Invariants Example Reader's Writer's
Problem (Writers)
P1
P3
T3
T1
2
P4
P2
P5
2
T4
T2
20
Petri Net T-Invariants Reader's Writer's Problem
(Readers Loop)
P1
P3
T3
T1
2
P4
P2
P5
2
T4
T2
21
Petri Net T-Invariants Reader's Writer's Problem
(Writers Loop)
P1
P3
T3
T1
2
P4
P2
P5
2
T4
T2
22
Coordination Design Login Process
Begin Login
User ID Password
Verify
Invalid Password
Check Mail
Mail Password
Try Again
Authenticate
23
Coordination Design T-Invariant Coverage
First Invariant (correct Login)
T3, T7
T1, T2, T9
Second Invariant (incorrect Login)
Third Invariant (forgot password)
T6
T4, T5, T8
  • n tries and lock technique based on T6

24
Coordination Design Login Process
  • Knowledge about T3, T5 and T6 can help design
    much better coordination behaviors
  • sufficient to understand (monitor) and predict
    systems evolutionary behavior.
  • T3 Key to maintenance and profiling - shared for
    logging maintenance and predicting usage patterns
  • T5 Key to behavior analysis Shared for
    prediction of user behaviors (ex. forgetfulness)
    between periods of usage
  • T6 Key to identifying intrusions shared
    appropriately with live intrusion detection
    modules

Bottomline Appropriate communication of
embedded knowledge (key decisions) supports
intelligent behavior evolution
25
ICE ? SOA
  • Modeling
  • Specs Semantic behavior, not technical (Unlike
    SOA)
  • Coordination requests complied with or fails
    (like SOA)
  • Explicit boundaries
  • Trust boundaries
  • Entities adapt and modify from apriori defined
    trust boundaries with other entities in the
    environment (unlike SOA)
  • Data boundaries (unlike SOA)
  • Entities selectively share black box
    information expected to be published by service
    (key decision information)
  • Security boundaries (like SOA)
  • Entities may/should impose security (like SOA)
  • Key issue, however, is not security, but
    selective information transfer
  • Coordination can be unavailable takes time

26
ICE ? SOA
  • Autonomous self-governing, self-determination
  • Entities respond to requests, not commands
    (like SOA)
  • Location transparency request independence
    (like SOA)
  • Allows flexible, dynamic context-dependent
    communication - selective or broadcast (unlike
    SOA)
  • Encapsulated loosely coupled - via provided
    services (like SOA)
  • Entity is not independent of caller (s) (unlike
    SOA)
  • Coordination is defined (SOA - Contract Exchange)
  • Schema Contract (a priori design)
  • Request parameters / result defined by schema
  • Contract defines procedures for coordination
  • Apriori defined multi-level information sharing
    structure
  • Logical boundary

27
Tool Support
28
(No Transcript)
29
(No Transcript)
30
Emergent Behavior Example
31
Emergent Behavior Example
Proceed w/ best (pre-determined) decision
choice Start reinforcement / support analysis
  • If decision supported,
  • continue
  • Else roll back and proceed
  • with best supported
  • decision
  • Update path choice info.
  • Apply aging / evolution criteria for best choice
    determination

32
  • With evolution, the normal state set grows over
    time with stronger support
  • Creates a psuedo-normal state

33
Major Topic Outline
  • Entity Design
  • Coordination Design
  • Multi-tiered Intelligent Control
  • Examples

The journey is the reward Tao
34
(No Transcript)
35
3-Tiered Intelligent Coordination Structure
  • Intelligence ability to identify problems and
    subsequently act / react to situational contexts
  • 3 tier design architecture
  • Lowest Tier Handle routine disruptions
  • Middle Tier Manage resources, support
    scalability
  • Top Tier Long term planning / analysis
  • Each tier builds on the previous levels
  • Provides a framework for self-adaptation, group
    intelligence and adaptive optimization
  • Supports distributed deployment
  • Supports scaling behaviors

36
SOA work w/ Malarvannan, Cybelink Systems, LLC
37
Major Topics Outline
  • Entity Design
  • Coordination Design
  • Multi-tiered Intelligent Control
  • Examples

Seekers are finders Afghan
38
Example MARS
C O O R D I N A T I O N
I N F O R M A T I O N
  • Modeled and analyzed using Petri nets
  • Enhance coordination by leveraging operational
    level intelligence

39
Alessandro Farinelli Luca Iocchi Daniele Nardi.
Multirobot Systems A Classification Focused on
Coordination. Transactions on Systems, Man, and
Cybernetics-Part B Cybernetics, October 2004,
vol. 34, no. 5.
Student Joe Ernest
40
Results
  • Software framework available for
  • Multithreading
  • Modified pair-wise communication in SMiRF (Serial
    Miniature RF Link) firmware to a 5-layer protocol
    stack implementation for wireless communication
  • Error handling needs improvement
  • Authentication non-existent
  • Mobile agent platform
  • Implemented tested on Mark IIIs

41
Example Job shop Scheduling
work w/ Ning Liu, Dr. Abdelrahman, TnTech
42
Results
  • Stable performance
  • Independent agents
  • Decentralized, with minimum global information
    (number current jobs and machines)
  • no master/slave relationships for dynamic job
    shop scheduling in distributed manufacturing
    systems
  • Robust during unpredictable job arrivals
  • Good, stable performance in static job shop
    scheduling
  • Stable, robust in dynamic job shop scheduling
    with unpredictable job arrivals

43
Extended Common Coupling
Software maintainability and reusability
affects
Common coupling
Definition-use analysis
used for
combine
applied to
Common coupling in kernel-based software
generate
defined
New common coupling categories
Kernel-based software
tested on
can be applied to
Open source operating systems
work w/ Dr. Ligou Yu, IUSB
44
Coupling Results
  • Extended common coupling types Stamp-common (A),
    data-common (B), stamp-control-common (C) and
    data-control-control (D) coupling
  • Studied global variable current in Linux
  • Appears in 18 kernal (114D, 382U)and 1071
    non-kernal (1403D, 6785U) modules
  • 68(A), 12(B), 11(C), 9(D), 0(pure common
    coupling)
  • More complex to maintain

45
Impact of Better Algorithms
Slide Source David Keyes, Columbia University
46
Conclusions
  • Overlaying hierarchical info. sharing software
    solutions onto existing implementation schemes
    (ex. SOA)
  • Support intelligent behaviors and improve
    scalability
  • Simple framework for enabling good coordinations
  • Similar to fractals
  • Self-similarity Smaller pieces are similar to
    larger pieces
  • System is made up of a few big entities, many
    medium sized entities, and a huge number of tiny
    entities, statistical self-similarity between log
    (Number) versus Log(size) for all entities
  • Scaling Value measured depends on the resolution
    level
  • Tiered intelligence structure with information
    sharing modeled and analyzed using Petri nets

47
The Snowflake Analogy Revisited
  • Growth (learning new behaviors communicating
    learned behaviors) in one arm (entity) affects
    growth in other arms
  • Faceting (simple a priori defined behaviors)
    affects growth when the crystals are small
  • Surface tension / inward attractive (molecular)
    force (group behaviors to build high vorticity
    (due to good cohesion and coupling support for
    information transfer), dynamic coordination mesh)
    helps build stability
  • Phonons (determination of necessary information
    to be communicated / group membership
    determination) support structural evolution
  • Branching instability (errors / disruptions in a
    dynamic operating environment) affects growth
    (adaptation) in larger forms

48
Questions / Discussions
  • Currently Funded Projects / Activities
  • Acxiom Corporation (06-07)
  • SME Driven Trainable Matching Engine
  • NSF MRI (06-09)
  • Arkansas ICE Emulation Laboratory
  • US DOT Eisenhower Fellowship (06-09)
  • Immersive Frameworks for Interactive Research,
    Support and Training
  • NASA Space Grant Consortium (06-07)
  • Development of Algorithms for Cooperating
    Multi-robotic Systems
About PowerShow.com