Jeff Kephart
IBM Research
© 2003 IBM Corporation

IBM Research
 Background and Motivation
 Autonomic Computing Research at IBM
 Architecture
 Overview of Research Program
 Autonomic Computing Research Challenges
 Conclusions
2 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
 My role in autonomic computing

My group does research on agents and multi-agent systems
–
Architecture, Communication, Negotiation, Machine learning

AC Research strategy; joint program manager
 University relations; faculty awards, equipment grants
 Co-chair, International Conference on Autonomic Computing 2004
 What I hope to achieve here
 Explore overlaps between research interests of e-Science and AC communities
 Explore potential collaborations
3 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

4
IBM Research
Dozens of systems and applications
DNS
Server
Web
Application
Thousands of tuning parameters
Hundreds of components
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
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 Individual system elements increasingly difficult to maintain and operate

100s of config, tuning parameters for commercial databases, servers, storage
 Heterogeneous systems are becoming increasingly connected

Integration becoming ever more difficult
 Architects can't intricately plan component interactions

Increasingly dynamic; more frequently with unanticipated components
 This places greater burden on system administrators, but
 they are already overtaxed
 they are already a major source of cost (6:1 for storage) and error
 We need self-managing computing systems
 Behavior specified by sys admins via high-level policies

System and its components figure out how to carry out policies
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
6
Self-
Heal
Optimize Web servers, databases have hundreds of nonlinear tuning parameters; many new ones with each release. Adjusted manually.
Protect
The Human-Intensive Present The Autonomic Future
Configure Corporate data centers are multivendor, multi-platform. Installing, configuring, integrating systems is time-consuming, error-prone.
Problem determination in large, complex systems can take a team of programmers weeks.
Manual vulnerability analysis. Manual detection and recovery from attacks, cascading failures.
Automated configuration of components, systems according to high-level policies; rest of system adjusts seamlessly.
Automated detection, diagnosis, and repair of localized software/hardware problems.
Components and systems will continually strive to improve their own performance and efficiency.
Automated defense against malicious attacks or cascading failures; use early warning to anticipate and prevent system-wide failures.
Business case: Increased resiliency, responsiveness, efficiency, ROI
Reduced down-time, risk, time-to-value, cost
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
7 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
 Background and Motivation
 Autonomic Computing Research at IBM
 Architecture
 Overview of Research Program
 AI Research Challenges
 Conclusions
8 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
The Autonomic Element
 AEs are the basic atoms of autonomic systems
 An AE contains

Exactly one autonomic manager
 Zero or more managed element (s)
 AE is responsible for
 Managing own behavior in accordance with policies
 Interacting with other autonomic elements to provide or consume computational services
Autonomic Manager
Analyze Plan
Monitor
Knowledge
Execute
S E
Managed Element
An Autonomic Element
9
Service-oriented architecture
Software agents
An Autonomic Element software app, workload mgr, sentinel, arbiter, OGSA infrastructure elements
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Element interactions
 System self-* properties, behavior arise from interactions among autonomic managers
 Interactions are

Dynamic, ephemeral
 Formed by (negotiated) agreement
 Flexible in pattern; determined by policies

Based on OGSI -
> WSRF, …? and specific AC extensions
10
A multi-agent system!
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Example scenario: Autonomic Data Center
Autonomic Data Center
System
Manager
Resourcelevel utility
Resource
Arbiter
Policy
Repository
Registry
Service-level utility
Application
Manager
Application
Manager
Demand
11
Database
Router
Server
Storage
Application Environment
Database
Router
Server
Storage
Application Environment
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004
Demand
© 2003 IBM Corporation

IBM Research

100-150 researchers working on various aspects of Autonomic Computing
 Some projects predate AC initiative; now trying to realign them with AC architecture
 Technologies for specific autonomic elements
 Database, storage, network, server, client…

Generic element technologies for autonomic elements
 Autonomic Manager Toolset integrates many element-level technologies
– Modeling, analysis, forecasting, optimization, planning, feedback control , etc.
 Uses Open Grid Services Architecture standards for inter-element communication
 Available (with ETTK v1.1) on www.alphaworks.ibm.com
; open source later

Generic system-level technologies
 Dependency management, problem determination and remediation, workload management, provisioning , …
 System scenarios and prototypes
 Small- to medium-scale autonomic systems
 Demonstrate self-* arising from AC architecture + technology
 Identify gaps, necessary modifications
12 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research

Over 150 researchers working on various aspects of Autonomic Computing
 Some projects predate AC initiative; now trying to realign them with AC architecture
 Technologies for specific autonomic elements
 Database, storage, server, client…

Generic element technologies for autonomic elements
 Autonomic Manager Toolset integrates many element-level technologies
– Modeling, analysis, forecasting, optimization, planning, feedback control , etc.
 Uses Open Grid Services Architecture standards for inter-element communication
 Available (with ETTK v1.1) on www.alphaworks.ibm.com
; open source later

Generic system-level technologies
 Dependency management, problem determination and remediation, workload management, provisioning, …
 System scenarios and prototypes
 Small- to medium-scale autonomic systems
 Demonstrate self-* arising from AC architecture + technology
 Identify gaps, necessary modifications
13 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Autonomic Manager ToolSet
W. Arnold et al., Watson
 Facilitates autonomic mgr construction
 In accordance w/ AC architecture
 Catcher for generic AM technologies
 OGSI (Globus 3.0 beta) -> WSRF
 Policy tools
 Monitoring standards and technologies
 AI tools for knowledge representation, reasoning, planning
 Math libraries for modeling, optimization
 Feedback control
 AMTS V1.0 available as part of Emerging
Technologies Toolkit v 1.1 on IBM alphaWorks
(www.alphaworks.ibm.com)
 Considering open source

Should we think about OMII?
S E
Autonomic Manager
Analyze Plan
Monitor
Knowledge
Execute
S E
Managed Element
14 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research

Over 150 researchers working on various aspects of Autonomic Computing
 Some projects predate AC initiative; now trying to realign them with AC architecture
 Technologies for specific autonomic elements
 Database, storage, server, client…

Generic element technologies for autonomic elements
 Autonomic Manager Toolset integrates many element-level technologies
– Modeling, analysis, forecasting, optimization, planning, feedback control, etc.
 Uses Open Grid Services Architecture standards for inter-element communication
 Available (with ETTK v1.1) on www.alphaworks.ibm.com; open source later

Generic system-level technologies
 Dependency management, problem determination and remediation, workload management, provisioning , …
 System scenarios and prototypes
 Small- to medium-scale autonomic systems
 Demonstrate self-* arising from AC architecture + technology
 Identify gaps, necessary modifications
15 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Dependency Mgt & Self-Healing
G. Kar, Watson and H. Lee & S. Ma, Watson

Determine functional dependencies among elements
 Mine design docs, system config metadata, log files
 Actively probe running system
 Use dependency information for system configuration, healing
 Problem management lifecycle

Monitor->Detect->Localize->Repair->Learn
App Server
16
Dependency Matrix pWS pAS pDBS pingR 0 pingWS 0 pingAS 0 pingDBS 0
WS AS DBS R HWS HAS HDBS
1 1 1 1 1 1 1
0 1
0 0
1
1
1
1
0
0
1
0
1
1
0
0
0
0
0
0
0
0
1
1
1
1
0
1
0
0
0
0
1
0
0
0
0
1
Web Server
Router
DB
Server
Probe
Analysis & Control
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Enterprise Workload Management
D. Dillenberger
Data and
Transaction
Internet/
Extranet
Large, distributed, heterogeneous system
 Achieves end-to-end performance via adaptive algorithms
 Administrator defines policy
– Desired response times for various classes of users, apps
 eWLM managers on each resource cooperate to adaptively tune parameters
– OS, network, storage, virtual server knobs
– JVM heap size, # garbage collection threads
– Workload balancing, routing parameters
17 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research

Over 150 researchers working on various aspects of Autonomic Computing
 Some projects predate AC initiative; now trying to realign them with AC architecture
 Technologies for specific autonomic elements
 Database, storage, server, client…

Generic element technologies for autonomic elements
 Autonomic Manager Toolset integrates many element-level technologies
– Modeling, analysis, forecasting, optimization, planning, feedback control, etc.
 Uses Open Grid Services Architecture standards for inter-element communication
 Available (with ETTK v1.1) on www.alphaworks.ibm.com; open source later

Generic system-level technologies
 Dependency management, problem determination and remediation, workload management, provisioning, …
 System scenarios and prototypes
 Small- to medium-scale autonomic systems
 Demonstrate self-* arising from AC architecture + technology
 Identify gaps, necessary modifications
18 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Human Interaction with Autonomic Systems
P. Maglio, Almaden
 Basic questions
 What do middleware administrators do?
 How can we better support the problems and practices they have?

Learn answers to these questions via ethnographic studies
 Use insights to develop new ways to interact with complex computing systems
… but we thought that was the return port!
We had it wrong. Our assumption of how it worked was incorrect.
We start with looking at the proxy server log files, then the web server log files, then the application server admin log files then the application log files.
19 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Example scenario: Autonomic Data Center
Autonomic Data Center
System
Manager
Resourcelevel utility
Resource
Arbiter
Policy
Repository
Registry
Service-level utility
Application
Manager
Application
Manager
Demand
20
Database
Router
Server
Storage
Application Environment
Database
Router
Server
Storage
Application Environment
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004
Demand
© 2003 IBM Corporation

IBM Research
 Background and Motivation
 Autonomic Computing Research at IBM

Architecture
 Overview of Research Program

Scenarios
 Autonomic Computing Research Challenges
 Systems and Software
– Architecture, software engineering & tools, testing/validation
– Prototyping a large-scale self-* system
 Human-Computer Interaction
– Policies, Interfaces
 Artificial Intelligence
Learning, Negotiation, Self-healing, Emergent Behavior
 Conclusions
21 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Challenge : Architecture
Define set of fundamental architectural principles from which self-* emerges
 AE : How to coordinate multiple threads of activity?
 AE’s live in complex environments

Multiple task instances and types
– concurrent, asynchronous

Multiple interacting expert modules
S E
Autonomic Manager
Analyze Plan
Monitor Knowledge Execute
 AE : How to detect/resolve conflicts arising from
 Internal decisions by independent expert modules
 External directives (possibly asynchronous)

Internal policies vs. external directives
S E
Managed Element
An Autonomic Element
 System-level : Enable more flexible, service-oriented patterns of interaction
 As opposed to traditional top-down, hierarchical systems management
 Multi-agent architecture
– Communication
–
Representing and reasoning about needs, capabilities, dependencies
22 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

Challenge
IBM Research
Policy : “Set of guidelines or directives provided to autonomic element to influence its behavior”
 Human interface
 Authoring and understanding policies
 Avoiding or ameliorating specification errors
S E
Autonomic Manager
Analyze Plan
 Developing a universal representation and grammar
 Many different application domains, disciplines
 Many different flavors of policy
 Covers service agreements too?
 Algorithms that operate upon policies (and agreements?)
 Automated derivation of actions (e.g. planning, optimization)
 Automated derivation of lower-level policies from high-level policies
E.g. “Maximize profit from this set of service contracts”
 Conflict resolution
 Both design time and run time
 Need to establish protocols, interfaces, algorithms
Monitor Knowledge Execute
S E
Managed Element
23 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
 Action rule
 If (S) then do a
2
 Results implicitly in desired state s
2
 Goal
 Achieve a most desired state s
2
 Compute a
2 most likely to result in s
2
Current
State
S
 Assumes that most desired state can be determined a priori a
1 a
2
Possible
State s
1
Possible
State s
2 a
3
Possible
State s
3
24

Utility function
 Achieve state s with maximal net value V( s
) – C(a
S d s
)
 Benefit and burden of being explicit about value
 States have intrinsic value; value of policy is a derived quantity
Machine code
[More levels of code hierarchy] Workflows
Programming
Rules
Adapters,
Translaters
Actions Generative
Planning
Decisiontheoretic
Planning
Element
Goals
Optimization
Element utility functions
Modeling,
Optimization
System utility functions
Research Challenges in Autonomic Computing | CMU, September 4, 2003
Higher-level specifications
© 2003 IBM Corporation

IBM Research
Challenge

 Specify goals and objectives to AC systems, and visualize their potential effect
 Techniques must be
– Sufficiently expressive of preferences regarding cost vs. performance, security, risk and reliability
– Sufficiently structured and/or naturally suited to human psychology and cognition to keep specification errors to an absolute minimum
– Robust to specification errors
25 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Challenge
Establish theoretical foundation for understanding and performing learning and optimization in multi-agent systems.

 AE needs to learn a model of itself and environment quickly; environment is noisy, and dynamic in both state and structure
 On-line, so exploration of the space can be costly and/or harmful
 May be several hundreds of tunable parameters!
–
Maybe only a few dozen are relevant, but which ones?
– Some of them can only be changed upon reboot – is it worthwhile?

 Multi-agent system: several interacting learners
 What are good learning algorithms for cooperative, competitive systems?
– What are conditions for stability?
– What is sensitivity to perturbations?
 Opportunities for layered learning
26 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Challenge

 Methods for expressing or computing preferences
 Negotiation protocols
 Negotiation algorithms
27

 Explore conditions under which to apply
– Bilateral
– Multi-lateral (mediated, or not)
–
Supply-chain
 Study how system behavior depends on mixture of negotiation algorithms in AE population
Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
Challenge

 How do self-*, stability, etc. depend on
– Behaviors and goals of the autonomic elements
– Pattern and type of interactions among AEs
– External influences and demands on system
 Invert relationship to attain desired global behavior
– How?
– Are there fundamental limits?

 Hierarchical
 Distributed
28 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
 Background and Motivation
 Autonomic Computing Research at IBM
 Architecture
 Scenarios

Overview of Research Program
 Research Challenges
 Conclusions
29 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research

Autonomic Computing is a grand challenge, requiring advances in several fields of science and technology
 Policy, planning, learning, knowledge representation, multi-agent systems, negotiation, emergent behavior
 Human-system interfaces

Integrating these technologies to support self-management in complex, realistic environments is a research challenge in itself
 What are the best architectures and design patterns? Role of (multi-)agent systems?
 Building system prototypes is key to developing and validating AC technology and architecture

The e-Science community is facing many of the same challenges
 Which ones are you most interested in tackling?
 How might we collaborate?
 AMTS in OMII?
 Conferences (come to ICAC ’04 in NYC May 17-18)
 Encouragement from EPSRC?
 Seek effective collaborations with IBM Researchers
30 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
 A Vision of Autonomic Computing

IEEE Computer, January 2003
 IBM Systems Journal special issue on Autonomic Computing
 http://www.research.ibm.com/journal/sj42-1.html
 Web site
 www.research.ibm.com/autonomic

 www.autonomic-conference.org
 May 17-18, New York City
 Submission deadline: January 12, 2003
31 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation

IBM Research
32 Research Challenges in Autonomic Computing | EPSRC e-Science Meeting , March 26, 2004 © 2003 IBM Corporation