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Description: DistribCom Distributed Models and Algorithms for the Management of Telecommunication Systems Albert Benveniste, Claude Jard Albert Benveniste 21 March 2012 Overall Objectives and Topics Albert Benveniste 21 March 2012 Pour insérer ou

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slide1. DistribCom Distributed Models and Algorithms for the Management of Telecommunication Systems Albert Benveniste, Claude Jard Albert Benveniste 21 March 2012<br>
slide2. Overall Objectives and Topics Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide3. Overall Objectives and Topics Applications Distributed Autonomic Management of network and services
Observing: fault management
Planning: deployment and reconfiguration

Composite Web services emphasis on QoS
QoS aware management of service orchestrations
Handling Workflows & Data jointly 21 March 2012 Albert Benveniste - 3<br>
slide4. Overall Objectives and Topics Foundations for Autonomic Management of Wide Area Distributed Systems
Modeling: Petri nets, scenarios
Composing: components & interfaces
Constructing Models: self-modeling
Distributed algorithms

QoS-aware Management of Wide Area Distributed Systems
Probability: uncertainty & non-determinism
Performance: time, cost & weights
QoS: time, security, availability, reliability, quality Applications Distributed Autonomic Management of network and services
Observing: fault management
Planning: deployment and reconfiguration

Composite Web services emphasis on QoS
QoS aware management of service orchestrations
Handling Workflows & Data jointly 21 March 2012 Albert Benveniste - 4 autonomic scale-up<br>
slide5. People Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide6. History & Flows 21 March 2012 Albert Benveniste Blaise
Genest Anne
Bouillard Guillaume
Aucher Axel
Legay

François
Schwarzentruber New topic: non-classical logics
Seeding: statistical model-checking Albert Benveniste
Eric Fabre
Loïc Hélouët
Claude Jard

Anne Bouillard
Blaise Genest Guillaume Aucher
F. Schwarzentruber
Axel Legay

Albert Benveniste
Eric Fabre
Loïc Hélouët
Claude Jard<br>
slide7. Background research areas: trans-disciplinarity 50% Albert Benveniste….

Eric Fabre.……………….

Loïc Hélouët…..……………

Claude Jard…...……………

Guillaume Aucher………………

François Schwarzentruber…...

Axel Legay…………….. Models of Concurrency & Formal Methods

Logic & Verification

Software Engineering

Mathematics, Probability & Statistics

Control 21 March 2012 Albert Benveniste - 7 XXX

XXX

XXX

XXX

X

X

XX<br>
slide8. Major results A glimpse of science Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide9. Major results Foundations and Models
Efficient and expressive scenario models
Modular data structures (trellis unfoldings)
Enhanced with Time, Probability, Cost
Distributed autonomic algorithms
for Diagnosis
for Planning
Self-modeling
Our algorithms are model-based
Tens of thousands of components  construct models automatically Autonomic management algorithms
Autonomic Wavelength Power Tuning in a Photonic Network (demo)
Autonomic graceful shutdown and restart
Joint network and service active diagnosis in IMS
Composite Web services & QoS
QoS-aware management of service orchestrations (demo)
Handling Workflow & Data jointly using Document Based Workflows (demo) 21 March 2012 Albert Benveniste - 9<br>
slide10. Autonomic Wavelength Power Tuning in a Photonic Network Challenges
avoid manual tuning & over-dimensioning
optimize optical reach without regeneration
Distributed and adaptive solution
huge coupled non-linear constrained optimization problem
distributed P2P tuning with 1 agent per node
Autonomic power (re)allocation when connections join or leave
Results
ALU simulations demonstrate 50% reduction in regeneration equipment
2 joint ALU-INRIA patents Algorithm performs Chaotic Iterations:
pick a link at random
freeze all optical gains, adjust the gains of the selected link
forward the result to the neighbors limited optical power per fiber limited power regeneration per wavelength Albert Benveniste 21 March 2012 ALU-Inria
Common Lab<br>
slide11. Distributed (Factored) Planning Motivation Autonomic cross-domain management of networks & services

Moving the system from one state to another state while avoiding some unwanted states and optimizing some cost

Hitless maintenance
Graceful shutdown & restart
Security holes avoidance while reconfiguring system 21 March 2012 Albert Benveniste - 11 ALU-Inria
Common Lab<br>
slide12. Distributed (Factored) Planning Motivation Autonomic cross-domain management of networks & services

Moving the system from one state to another state while avoiding some unwanted states and optimizing some cost

Hitless maintenance
Graceful shutdown & restart
Security holes avoidance while reconfiguring system Approach and Result Optimal planning for a network of interacting automata

Features
Cross-domain P2P planning
Models: local to each domain
Distributed
Unsupervised: no coordinator
Solves the desired optimal planning problem

Pre-requisite
Self-modeling shall be applicable 21 March 2012 Albert Benveniste - 12 ALU-Inria
Common Lab<br>
slide13. Distributed (Factored) Planning: details Planning: drive optimally the network of interacting components to a target state
Message Passing Algorithms (MPA)
Weighted automata: finite state machine with additive costs on transitions
MPA  Belief Propagation in Belief Networks algorithm architecture = system architecture
Local plans combine into optimal global plan
For applications exhibiting local connectivity, factored planning is exponentially faster 21 March 2012 Albert Benveniste - 13 ALU-Inria
Common Lab<br>
slide14. Composite Web services and QoS QoS aware management QoS is multi-dimensional
Response time, Throughput
Security, Availability, Cost, …
Orchestrations may not be QoS-Monotonic ( but ≠ Bräss)
Due to interactions workflow/data/QoS
Not noticed in WS community
 QoS-Monotonicity: new topic
Conditions ensuring monotonicity
How to deal with lack of monotonicity Albert Benveniste<br>
slide15. Composite Web services and QoS QoS aware management QoS is multi-dimensional
Response time, Throughput
Security, Availability, Cost, …
Orchestrations may not be QoS-Monotonic ( but ≠ Bräss)
Due to interactions workflow/data/QoS
Not noticed in WS community
 QoS-Monotonicity: new topic
Conditions ensuring monotonicity
How to deal with lack of monotonicity 21 March 2012 Albert Benveniste - 15<br>
slide16. Composite Web services and QoS QoS aware management On top of monotonicity  Contract Based Management
Probabilistic Contracts
Compare using Stochastic Ordering
Monitoring using Page-Hinkley tests
Optimal Design and Late Service Binding
QoS calculus (Dioid Algebra)
Implementation in Orc: weaving QoS in functional spec 21 March 2012 Albert Benveniste - 16<br>
slide17. Composite Web services and QoS Document based workflows In complex business processes:
Workflows & Data seen as equal citizens
Workflows can be guarded by document patterns
Workflows can update documents
Not possible today: workflows and DB are separate technologies
Our objectives
Handling Workflow & Data jointly
A formal framework for Web-scale distributed service computing
Service Interfaces Albert Benveniste<br>
slide18. Composite Web services and QoS Document based workflows In complex business processes:
Workflows & Data seen as equal citizens
Workflows can be guarded by document patterns
Workflows can update documents
Not possible today: workflows and DB are separate technologies
Our objectives
Handling Workflow & Data jointly
A formal framework for Web-scale distributed service computing
Service Interfaces On top of Active XML documents [Abiteboul]

Results
A framework for Distributed Document Based Workflows
Verification of reachability properties
Platform under development 21 March 2012 Albert Benveniste - 18<br>
slide19. Publications See the written document Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide20. Industrial ties transfers & impact Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide21. Industrial ties, transfers & impact Topic Distributed algorithms for the autonomic management
Autonomic Wavelength Power Tuning in a Photonic Network
Autonomic graceful shutdown and restart
Joint network and service active diagnosis in IMS

Composite Web services, document based workflows, and QoS
Still we think the topic is important Impact ALU-BellLabs Common Lab / HiMa
EU IP-Univerself (ALU, Orange)
2 ALU(Inria) patents; detailed exploration of business opportunity by BD, now stalled
1 ALU(Inria) patent
Under study mainly with Orange Labs self-modeling

So far industrial contact missing (SAP? IBM?) 21 March 2012 Albert Benveniste - 21 ALU-Inria
Common Lab<br>
slide22. Competition & Cooperation Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide23. Competition & Cooperation Topic Fundamentals of distributed observation and supervision of wide area distributed systems

Distributed algorithms for the autonomic management of network and services

Composite Web services, document based workflows, and QoS Community Formal methods in computer science…………………………………(AA)

Network & service management .…….(A)
Distributed systems & algorithms in computer science and control ……..(AAA)

Web services ………….………………..(A)
Data bases …..………………………….(C)
Formal methods in… ………………..(AA) 21 March 2012 Albert Benveniste - 23<br>
slide24. Visibility Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide25. Visibility A. Benveniste is Directeur Scientifique of ALU-BL / Inria common lab
A. Benveniste is Directeur Scientifique of Labex CominLabs
CominLabs is an Excellence Center (Labex) funded for 10 years
Bretagne and Nantes labs in the area of Telecoms & Over-the-top Applications
Overall funding of 14M€
A. Benveniste is member of Orange Labs (and Safran) Scientific Councils
E. Fabre is head of the Action de Recherche High Manageability at ALU-BL / Inria common lab
L. Hélouët is invited researcher in the Indo-French LIA INFORMEL
C. Jard is Directeur de la Recherche at ENS Cachan Bretagne 21 March 2012 Albert Benveniste - 25<br>
slide26. Future plans DistribCom is not expecting to continue for 4 more years
Current plans are to merge DistribCom, S4, and Vertecs teams under the lead of Eric Fabre
We present the focus of DistribCom’s members in this context Albert Benveniste 21 March 2012 Pour insérer ou remplacer le visuel de fond sur la page titre :
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slide27. Seen from our side Some industrial challenges Autonomic management of wide area distributed systems
Knowledge plane  Self-Modeling+Learning

Cross-domain

Autonomic supervision

Many aspects for optimization
cost, energy, resilience, security

Moving to clouds? How we’d like to contribute (E. Fabre, A. Benveniste)

Knowledge = Models+Data  Self-Modeling+Learning

Cooperative : Distributed optimization
Non-cooperative : Games??

No central coordinator

Algorithms supporting multiple QoS dimensions

Today: centralizing data & management
Tomorrow?? 21 March 2012 Albert Benveniste - 27<br>
slide28. Seen from our side Some industrial challenges Web-scale Business Processes and Services
Safe and secure Business Processes

Multi-dimensional SLA
cost, energy, resilience, security

Workflows & Data

Computing as part of composite Services

Moving to clouds? How we’d like to contribute (L. Hélouët, C. Jard, A. Benveniste) a
Pay attention to semantics of distributed programs, have semantically rich interfaces (today syntax only)

Have semantically rich SLA, math models for QoS (not just “silver/gold/platinum”)

Document Based + Imperative Workflows

Algorithms as a Service

Today: centralizing data & management
Tomorrow?? 21 March 2012 Albert Benveniste - 28<br>
slide29. Future team (this slide is common with the other 3 teams) A new team is under construction (from Vertecs, S4, Distribcom), led by Eric Fabre.
Modeling, analysis and management of distributed heterogeneous systems
distribution : modularity, composition, concurrency
heterogeneity : quantitative aspects, as time, probabilities, costs, performance (QoS), etc
analysis : verification, test
management : control, diagnosis, planning, optimization...
self-modeling : automatic construction of models
Challenges
scaling up to large&complex by abstractions, approximate analysis, parameterization…
handling reconfigurable, partially known, open systems
designing distributed/modular management methods: modularity, multi-agent, games
Applications
large open reconfigurable softwares, as web-services or distributed active documents
(very) large structured systems: telecommunication network management
systems design 21 March 2012 Albert Benveniste - 29<br>
slide30. thanks<br>