Research & Development Activities a l´UNIFACS Prof. Dr. Joberto S. B. Martins Salvador University – UNIFACS Salvador – BA, Brazil
Short Presentation "Docteur" in Computer Science, UPMC, Paris – France, 1986; M.Sc. in Electronic Engineering, PII, Eindhoven – Netherlands, 1979; Electric Engineer, emphasis on Telecommunications, at UFPB, 1977. Worked as visiting scientist at ICSI – California University at Berkeley (USA) in 1995. Full Professor at UFPb from 1977 to 2000. Current position: Professor at Salvador University UNIFACS and visiting professor at Hochshule Für Technik Und Wirstchaft Des Saarlandes, HTW – Saarbrucken, in Germany. Additional information: see “Joberto Martins” on Google
Agenda Research & Development Activities UNIFACS (in brief)
Research Area/ Topics Area/ Domain:
Networking (reseaux)
Topics:
Future Internet/ SDN/ Monitoring Resource Allocation/ Autonomic Management Smart Grid/ Smart Cities
Future Internet/ SDN/ Monitoring Technical Aspects/ Protocols Network for Experimentation (NfExp) OpenFlow/SDN – Software Defined Networking Monitoring:
CMFs: OFELIA/Protogeni/OMF PerfSonar IRODs - Integrated Rule-Oriented Data System
In Brief: What we Need for Future Internet (a perspective) Visions and proposals for the Future Internet:
(Re)Think fundaments: routing, access, identity, other issues
We need experimentally-driven research:
Fast and scalable realistic scenarios
We need new business models and business incentives for adoption
Future Internet How to Evolve? How to evolve from current Internet to Future Internet (FI)?
Incremental approach: The basic architecture is kept; small solutions are adopted incrementally
Clean-Slate Design: The principle is to innovate from the scratch, eventually, adopting radical changes on the network architecture (Stanford approach) Openflow/ SDN – Software-Defined Networking
Hybrid Approach
New protocols and new architectures have been proposed but there is a problem:
Internet is so big that any modification is not easily adopted by stakeholders Innovation process on current Internet may take years (from protocol/ service development to overall adoption)
Future Internet Networks for Experimentation (NfExp) Network innovation and experimentation is difficult:
Routers and switches are “closed” Software-only experiments have both performance and scalability issues New protocols development make take years
Need a validation process for new design New infrastructures (testbeds) for developing and testing new or futuristic networking ideas: TESTBED architectures
Future Internet Networks for Experimentation (NfExp) GENI (US) - Global Environment for Network Innovations FIRE (EU) - Future Internet Research and Experimentation FIBRE (BR-EU) - Future Internet testbeds / experimentation between BRazil and Europe FED4FIRE AKARI (JP) OFELIA …
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FIBRE Network Topology and Architecture Overview U. Bristol UFPA
UFPE
UNIFACS WDM
UFSCar OCF OCF OCF
OMF
OCF
OMF
OMF
UFG
OCF
OMF
PoP-UB PoP-PA
PoP-PE
PoP-BA OCF
OMF
PoP-DF
PoP-i2CAT
PoP-SP
PoP-GO
PoP-UTH
Prot GENI
PoP-RJ
OCF
OMF
OCF
USP OCF
RNP
OMF
i2CAT WDM
OCF
OMF
OCF
OCF
UFRJ
UTH
OMF OMF
UFF CPqD
OFELIA – OpenFlow in Europe Linking Infrastructure OMF – Orbit Management Framework ProtoGENI WDM GMPLS Wireless experimental facility Small wireless facility (3 nodes) 10
FIBRE Testbed (islands outside BR)
Miami, FL, US (AmLight) (Florida International University - FIU) In EUROPE:
i2CAT - Spain University of Bristol - UK UTH – University of Thessaly - Greece
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FIBRE Network Topology and Architecture Overview
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FIBRE Architecture Overview U. Bristol UFPA
UFPE
UNIFACS WDM
UFSCar OCF OCF OCF
OMF
OCF
OMF
OMF
UFG
OCF
OMF PoP-UB
PoP-PA
PoP-PE
PoP-BA
OCF
OMF
PoP-i2CAT
PoP-UTH
PoP-SP
PoP-GO
Prot GENI PoP-DF PoP-RJ
OCF
OMF
OCF
USP
OCF OMF
RNP i2CAT
WDM OCF
OMF
OCF
OCF
UFRJ
UTH
OMF OMF
UFF CPqD
OFELIA Control Framework OMF ProtoGENI WDM GMPLS Wireless experimental facility Small wireless facility (3 nodes)
•
13 remote islands: large-scale federated facility between Brazil and Europe
•
Heterogeneous Network resources: OpenFlow switches, wireless infrastructures, optical devices, virtualization - XEN servers, other
•
A federation of Control and Monitoring tools: OCF, OMF and Protogeni 13
FIBRE-BR I&M Architecture
PerfSonar tools on FIBRE IRODs data storage OML-based monitoring OFELIA monitoring tool
FIBRE Project/ Team FP7 Project (5 Million Euros):
Concluded: 2015 NaaS (Network-as-a-Service) approach right now: RNP support New islands being included
UNIFACS: 05 MSc; 01 PhD Next possible approach:
IoT experimentation support: Brazilian project submitted (FAPESP) European project (maybe + UPMC, …)
FIBRE Brazilian Team (2014)
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Resource Allocation & Autonomic Management Autonomic Management Resource Allocation/ Provisioning:
Bandwidth Allocation Models BAMs
Bandwidth Allocation Models BAMs Principles Originally meant for IP + MPLS networks with Traffic Engineering (DS-TE networks - RFC 3564):
Traffic Class (TCs) mapping of application/ services Bandwidth Constraints by TC Bandwidth Allocation Model (BAM) allocates resource (bandwidth)
BAM defines the way resources are allocated:
Using BAM applications/ services organized in classes (TCs) have resources granted/ allocated, resources blocked and/or resources preempted Both impacts and may control overall network behavior
Bandwidth Allocation Models – BAMs Traffic Pattern/ Matrix: - Dynamic - Multiservice/ Multimedia
Per-Link Basic Principle
An TC1 Allocation (BC1) = p Ax LSP Request
Aj
Resource Broker
- Network monitoring - State control
Contour variables: - Limited bandwidth - Fix - Other
TC2
BAM-based
Allocation (BC2) = q Ak
(various models) LSP Grant/ No Grant
Az
R1
TC3 Allocation (BC3) = r Ay
Application/ Network Requirements (sample): SLA (Service Level Agreement) QoS – Quality of Service QoE – Quality of Experience Network policies other
BWLink01 = p+q+r
Per-Link characteristics: LSP grant LSP blocking LSP preemption Link utilization other
R2 BWLink01
LSPx LSPy LSPz
LSPm
BAM – Alternative Models Existing BAM models:
MAM - Maximum Allocation Model RDM – Russian Dolls Model G-RDM – Generalized RDM (proposed by Rafael Reale & Joberto Martins - 2015)
New BAM propositions/ developments:
AllocTC-Sharing (proposed by Rafael Reale & Joberto Martins - 2014) GBAM – Generalized BAM Simulation
BAMs & Network Traffic Dynamics IP Context What is proposed:
Bandwidth (resource) allocation should dynamically adapt “overall bandwidth availability” in relation to network traffic profile dynamics
How to do it?
Changing BAMs dynamically (either BAM option and/or BAM configuration) while keeping overall SLAs (Service Level Agreements) and traffic management polices
BAM new models BAM behavior investigation (simulation) in relation to network traffic profile and management requirements
Issues to do it (BAM switching and/or BAM (re)configuration): Needs knowledge about current network status and expertise for deciding why and when to adopt a new BAM model and/ or a new configuration approach Should be done preferably “on-the-fly”
BAM Framework with autonomic characteristics
BAM Framework & Autonomy Information Plan
KNOWLEDGE PLAN
Alert/ Monitoring
NETWORK PARAMETERS (A)
PATH SELECTION ALGORÍTHMS (B)
STATE SIMULATOR (D)
CONTROL ELEMENT (G)
BANDWIDTH ALLOCATION MODELS (C)
PERFORMANCE ANALYSER (E)
STATE VALIDATOR (F)
Action
Execution Plan
Knowledge plan:
CBR – Case Based Reasoning Other approaches can be implemented
DB ACCESS (G)
DB
BAM Framework & Autonomy with SDN/ OpenFlow Information Plan KNOWLEDGE PLAN
Alert/ monitoring
NETWORK PARAMETERS (A)
PATH SELECTION ALGORÍTHMS (B)
STATE SIMULATOR (D)
CONTROL ELEMENT (G)
PERFORMANCE ANALYSER (E)
BANDWIDTH ALLOCATION MODELS (C)
DB
DB ACCESS (G)
STATE VALIDATOR (F)
Action Execution Plan
Rule
OpenFlow Switch 1
SDN CONTROLLER
...
NETWORK
Switch n
BAM – Alternative Models Existing BAM models:
MAM - Maximum Allocation Model RDM – Russian Dolls Model G-RDM – Generalized RDM
New propositions/ developments:
AllocTC-Sharing GBAM – Generalized BAM
Application areas:
IP/MPLS Optical networks (lambda allocation; WDM networks) (ongoing work) Telecommunications (IP operator) “Service Neutrality” (ongoing work) Resource Allocation & Autonomy (generalization)
Resource Allocation - BAM Project Team and Perspectives UNIFACS: 02 MSc; 01 PhD 2016:
01 PhD 02 new MSc
Possible new approaches (next 05 years):
BAM new approaches (GBAM): IoT resource allocation/provisioning 5G/ wireless Cloud?
+ Autonomy in highly dynamic allocation/ provisioning scenarios
Smart Grids Concepts and Perception – Focus on Networking Smart Grid (revisiting the concept and perception):
Next Generation Electric Power System (NGEPS) Incorporate renewable energy sources (wind, solar, geothermal, other) More intelligent system providing automated management and new services more efficiently
Smart Grid & Networking:
Computer networks supporting NGEPS: An integrated high-speed, reliable and secure data communications network supporting EPS operations and management Bound by specific requirements
New resources must be introduced in the Electric System´s computer network: New network architecture, more sensors, new process automation; bidirectional data flow (operator user) and other innovations
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Smart Grid
Smart Grid – Functional View
TI-like Approaches
Network Issues
Infrastructure: monitoring, IEDs, IEC 61850, …
Source: http://www.greentechmedia.com/images/wysiwyg/News/endtoendtax
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Smart Grids Some Network Requirements Bidirectional communications and data-intensive applications:
Monitoring, sensors, Automated Metering Infrastructure/ Automated Meter Reading (AMI/AMR), actuation elements, other Specific Smart Grid systems may require data-intensive (+time-sensitive) support: WASA, monitoring, other Real-time bidirectional communications is mandatory (Ex.: NGEPS User)
QoS, QoE and Time-sensitive information exchange:
Diversified and heterogeneous communications, real-time and synchronization requirements for IEC 61850, substations and monitoring
Resilience, Availability, Reconfiguration and Fault Recovery:
Resilience models, high availability, other Wide Area Protection Systems (WAPS), self-healing functions, Wide Area Situation Awareness (WASA), other aspects
Network-Specific Security aspects (subset of the overall security issue)
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250 MW
A
Smart Grid at UNIFACS
250 MW
100 MW
C
150 MW 1
B 50 MW 3
150 MW 100 MW 100 MW
Grid Modeling with “R” (+ graphs) Grid Reconfiguration Reconfiguration Management with Autonomic Characteristics
4 200 MW
50 MW 5 50 MW
50 MW
100 MW
2 300 MW
200 MW
6 100 MW
D
100 MW
350 MW
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250 MW
A
Smart Grid at UNIFACS
250 MW
100 MW
Paper: Hybrid algorithm based on Genetic Algorithm and
Tabu Search for Reconfiguration Problem in Smart Grid Networks Using " R "
C
50 MW 3
150 MW 100 MW 100 MW
4 200 MW
Flavio G Calhau · Romildo M S Bezerra · Joberto B Martins ·Alysson Pezzutti
The reconfiguration of distribution networks aims to support the decision process, planning and/or real-time control of the operation of electricity networks It is accomplished by modifying the network structure of distribution feeders by changing the status of sectionalizing switches It is proposed a hybrid algorithm (Genetic and Tabu) for the reconfiguration problem based on “R” in order to better support the decision making process The “R” modeling of the electricity networks improves the response time when handling issues related to network reconfiguration using graph theory A simulation of IEEE 16-bus system demonstrates the computational efficiency for the set of results derived from the new algorithm proposed
150 MW 1
B
50 MW 5 50 MW
50 MW
100 MW
2 300 MW
200 MW
6 100 MW
D
100 MW
350 MW
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Smart Grid & Smart Cities Project Team and Perspectives UNIFACS: 02 MSc; 01 PhD 2016:
01 PhD 01 new MSc
Possible new approaches:
Smart Cities should be the main focus (starting in 2016) 01 European Project submitted in 2015 Another project submission in Brazil (in 2016)
Smart Grid activity will focus on specific projects with the industry
UNIVERSIDADE SALVADOR UNIFACS Laureate International Universities (US) Salvador – BA - Brazil 32.000 students Private institution All areas (BAC) Masters & PhD:
05 programs PPGCOMP Computer Science
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U N I FAC S & P P G C O M P CO M P U T E R S C I E N C E P RO G R A M -- Masters – since 1999 – PPGCOMP -- PhD - Multiinstitucional (DMCC) – since 2006 - until 2018 (UNIFACS/ Universidade Federal da Bahia – UFBA and Universidade Estadual de Feira de Santana – UEFS)
MSc: http://www.ppgcomp.unifacs.br/ PhD: http://wiki.dcc.ufba.br/PMCC/ApresentacaoDMCC
Coordination: Prof. Dr. Joberto S. B. Martins
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PPGCOMP Areas
Research axes: Software Engineering Computer Networks Web/Multimedia Applications and GIS
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Software Engineering (06 profs):
Software Maintenance and Technical Debt Ubiquitous Computing and Software Engineering Information Technology Management Business Intelligence XBRL SPED, Data Quality, GIS and Security XBRL and Mobile Computing SOA, Web Services and XBRL Data Mining Data Visualization Software Visualization Software Quality Software Process Services (ITIL, ISO 20000, CMMI-SV and MPS Services) 36
Computer Networks (04 profs): Future Internet/Networks for Experimentation/ Monitoring Autonomic Management OpenFlow and Virtualization Smart Grid & Smart Cities Context Awareness Modeling and Simulation Ubiquitous and Pervasive Computing
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Web/Multimedia Applications and GIS (03 profs):
Geographic Information Systems (SIG) Multimedia, Hypermedia and Web Technologies Virtual and Augmented Reality Mobile Objects and Trajectory Semantics Knowledge Mining in Space-Temporal database Crowdsourcing Mobile SIG and WEB SIG Interactive Digital TV Embedded Systems
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PPGCOMP TEAM 2016 Professor Artur Henrique Kronbauer
Dr – UNIFACS/UFBA - BR – 2013
Bruno Carreiro
Dr – UNIFACS/UFBA – BR - 2015
Ernesto de Souza Massa Neto
Dr – UNIFACS/UFBA – BR - 2014
Eldman Nunes
Dr – UFF – BR - 2003
Glauco de Figueiredo Carneiro
Dr – UNIFACS/UFBA - BR – 2011
Joberto Sérgio Barbosa Martins
Dr – UPMC (Paris VI) – França – 1986
Jorge Alberto Prado de Campos
PhD – UMO (Maine at Orono) – US - 2004
Paulo Caetano da Silva Paulo Nazareno Sampaio Rodrigo Spínola
Dr – UFPE - BR - 2010 Dr – Univ. Paul Sabatier / LAAS-CNRS – França - 2003 Dr - COPPE/UFRJ - BR - 2010
Sergio Martins Fernandes
Dr. – USP – BR - 2013
José Maria Nazard – UFJF (C)
Dr – UFRJ – BR – 2004
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Thanks Discussion and Questions
Contact: Prof. Dr. Joberto S. B. Martins
[email protected] or
[email protected] +33 6 40 90 90 47 +55 71 9 8868 7595 Skype_id: jobertomartins
