1 intelligent coordination design in software systems srini ramaswamy computer science - ualr...
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Intelligent Coordination Design in Software
SystemsSrini Ramaswamy
Computer Science - UALRsrini@acm.org/srini@ieee.org
Nothing endures but change [Heraclitus]
2© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Intelligent Coordinating Entities
• Structure: Uniform, scalable design
• Vorticity: Relies on a communication-centric framework
• Behavior: Localized decision-making behaviors, reinforced with
• Dynamic aggregated learning models and information-sharing models
Simple, structured, well-defined coordinations
• Uniform (locally homogeneous)
• Symmetric (repeatable)• Well-defined & Scalable
4© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Practicality of Coordinated, Hierarchical Abstractions
Hierarchical:
Bottom up data sharing top-downdecisions flow Coordination time:log N N
Democratic:
All share data, All participate in decisionsCoordination time: N2
Slide adapted from : Bernard P. Zeigler, Univ. of Arizona
Nnumber of performers
speed-up: time to complete relative to single programmer
)(/1)( NaFNNt
t(1)
F(N) = N2
F(N) = N
F(N) = log N
1/ N
relative time to complete job (inverse ofspeed up)
Coordinationoverhead, F(N)
6© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
7© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
OO: Encapsulation of resource (at some granularity) and its associated functions (strive for norms).
Needs: 1. Service Interface: Mechanism to
publish service availability2. 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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
9© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Major Topic Outline
Entity Modeling & Design Coordination Design Multi-tiered Intelligent Control Examples
10© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Addressed by hierarchical abstractions / task focused design
Addressed by information sharing mechanisms
13© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
15© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Using Petri Net Invariants: Reader's Writer's Problem (Readers)
P1
P4
P3
P2 P5
2
2
T2
T3
T4
T1
19© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Petri Net Invariants Example: Reader's Writer's Problem (Writers)
P1
P4
P3
P2 P5
2
2
T2
T3
T4
T1
20© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Petri Net T-Invariants: Reader's Writer's Problem (Readers Loop)
T2
T3
T4
P1
P4
P3
P2 P5
2
2
T1
21© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Petri Net T-Invariants: Reader's Writer's Problem (Writers Loop)
P1
P4
P3
P2 P5
2
2
T2
T3
T4
T1
22© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Coordination Design: Login Process
Begin Login
User ID & Password
Verify
Check MailInvalid Password
Mail PasswordTry Again
Authenticate
23© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Coordination Design: T-Invariant Coverage
T1, T2, T9
T3, T7
T4, T5, T8T6
First Invariant (correct Login)
Second Invariant (incorrect Login)
Third Invariant (forgot password)
“n” tries and lock technique based on T6
24© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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
Coordination Design: Login Process
25© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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
ICE ≠ SOA
27© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Tool Support
28© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
29© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
30© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Emergent BehaviorExample
Red
uced
acc
ess
Ful
l acc
ess
No
acce
ss
31© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Proceedw/ best (pre-determined) decision choiceStart reinforcement / supportanalysis
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
Emergent BehaviorExample
32© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
• With evolution, the normal state set grows over time with stronger support
• Creates a psuedo-normal state
33© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Major Topic Outline
Entity Design Coordination Design Multi-tiered Intelligent Control Examples
The journey is the reward [Tao]
34© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
35© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
SOA work w/ Malarvannan, Cybelink Systems, LLC
37© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Major Topics Outline
Entity Design Coordination Design Multi-tiered Intelligent Control Examples
Seekers are finders [Afghan]
38© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
• Modeled and analyzed using Petri nets• Enhance coordination by leveraging operational level intelligence
COORDINATION
INFORMATION
Example: MARS
39© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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 III’s
41© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Example: Job shop Scheduling
J1 Ji JNc…
M1 MMcMm …
Auctioneer Auctioneer Auctioneer
…
…
Prices
BidsXijt
(Subproblem)
(Price-adjustment) Time slots
L
Decision point
tc
Length ofrolling time horizon
work w/ Ning Liu, Dr. Abdelrahman, TnTech
42© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Extended Common Coupling
Definition-use analysis
Open source operating systems
Common coupling
Kernel-based
software
Common coupling in
kernel-based software
New common coupling categories
Software maintainability and reusability
tested oncan be applied to
combine
affects
applied to
generate defined
used for
work w/ Dr. Ligou Yu, IUSB
44© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Impact of Better Algorithms
Slide Source: David Keyes, Columbia University
46© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
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© Srini Ramaswamy, Professor & Chairperson ● Computer Science ● Donaghey College of Information
Science and Systems Engineering ● University of Arkansas at Little Rock ● Little Rock ● AR 72204 September 19th 2006 Phone 501-569-8130 ● Fax: 501-569-8144 ● Email: srini@acm.org / srini@ieee.org / srini@ualr.edu Wayne State Univ.
Questions / DiscussionsCurrently 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
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