service differentiation and grids
DESCRIPTION
Service Differentiation and Grids. Pascale V icat-Blanc Primet Benjamin Gaidioz, Pierre Billiau, François Echantillac, Mathieu Goutelle, Fabien Chanussot INRIA - Reso LIP Laboratory Ecole Normale Supérieure de Lyon France P ascale. [email protected]. Outline. - PowerPoint PPT PresentationTRANSCRIPT
Service Differentiation and Grids
Pascale Vicat-Blanc Primet
Benjamin Gaidioz, Pierre Billiau, François Echantillac, Mathieu Goutelle, Fabien Chanussot
INRIA - ResoLIP Laboratory
Ecole Normale Supérieure de Lyon
France
P. Vicat-Blanc Primet 2
Outline
Requirements for E2E Service Differentiation in Grids
The EDS approach (DataTAG project)
The QoSinus approach (e-Toile/VTHD project)
Conclusion
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Typology of Grid flows
Applications flows: Input & Output data Inter process communication messages (MPI, DSM, synchro…) Codes coupling Interactions Vizualizations Voice/Video in collaborative environments
Control flows: Grid environment deployment Applications deployment Control and Management of the Grid (middleware)
Monitoring, scheduling, loading, reporting, alarms…
All these flows share the same « network resource » and the same bottlenecks
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Example: e-toile : Infrastructure
VTHD 2.5 à 10 Gb/s
VTHD 2.5 à 10 Gb/s
16 power PClinked by Myrinet
8 x 2 PC linked by SCI
2 Gb/s
1 Gb/s
1 Gb/s
1 Gb/s
1 Gb/s
1 Gb/s
1 G
b/s
250 PC en cluster
1 cluster Myrinet de 10 PCs1 cluster de 8 PCs
IRISARennes
CEASaclay
PRiSMVersailles
EDFClamart
ENSLyon
ID-IMAGGrenoble
SUNGrenoble
ID-IMAGGrenoble
SUNGrenoble
ENSLyon
ID-IMAGGrenoble
EDFClamart
ENSLyon
ID-IMAGGrenoble
PRiSMVersailles
EDFClamart
ENSLyon
ID-IMAGGrenoble
CEASaclay
PRiSMVersailles
EDFClamart
ENSLyon
ID-IMAGGrenoble
IRISARennes
CEASaclay
PRiSMVersailles
EDFClamart
ENSLyon
ID-IMAGGrenoble
Routeur actif
Serveur 8 processeurs
Machine SMP
Service de dépôt dedonnées IBP
Routeur actif
IBCP
Serveur 3* bipro
Serveur biproMP760
12 PC bipro
16 Sun Cobalt
1 cluster de PC
Experimental Testbed
6 PC bipro
16 PC bipro
Clusters de PC 1,9 Ghz
Serveur bipro1,2 Ghz
Production Testbed
CERN
EuropeUS
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Grid Flows characteristics
Mice, Elephant, Lièvres et Tortues, … Throughput:
Rates: more than 9 orders of magnitude Few bytes for interactive traffic or control traffic To petabytes for bulk data transfer.
Delay: Very heterogeneous needs Some applications are very sensitive to latency (MPI; visu) Bulk Data Transfer delays have to be controlled
Reliability : Generally reliable (=> TCP) but some apps are loss tolerant (Astro)
Communication models: Point to point, point to multipoint, multipoint to point, multipoint to point Collectives operations, synchronisation barriers...
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1. Tags and myocardiumautomatic extraction
2. Motion estimation
3. Quantification
time
Medical Images processing : Pipeline
tagged MRI sequences
From 20MB to 2GB/frame
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How to control the performances?
Packet level (Network QoS) ~1 à 100s Mechanisms: classifiers, marquers et conditionners (routers) Models: IntServ, DiffServ, Corestateless,Proportional, EDS…
Round trip time level (E2E QoS) ~1 à 100 ms Congestion control and flow control (TCP, TFRC)
Session level s, mn, or hr Admission control, Resource reservation (RSVP), routing Load sharing, MPLS-TE, BoD
Long term Days, months... Provisionning, planification, oD
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Explored Approaches (INRIA RESO)
Grid really need End to end QoS (bulk to MPI & vizual.)Packet differentiation is already there in IP equipments PQ, WFQ, CBQ, WRR, RED, WRED… Lot of issues with IS & Diffserv
Service differentiation at transport levelTwo approaches have been explored at INRIA: E&E : DataTAG (assumption: bottleneck is in access&LAN)
Relative IP packet differentiated forwarding Each connection manages its individual QoS End protocol has to be adapted (SlowStart or AIMD)
Edge to Edge : e-Toile (assumption : bottleneck is in WAN) An Independant API defined and integrated in mw to specify session QoS
goals QoSINUS as a Grid network Service Interact with the Grid Measurement Infrastructure
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EDS approach
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Equivalent Differentiated Service Model
Goal: Sharing the network resources (bottleneck) and control the E2E performances according to the application specific requirements
=> delay sensitive/ loss sensitive/rate sensitive…
Constraints: new PHB at IP level Differentiated forwarding services without pricing No admission control required. PHB definition restricted to local parameters (no layer violation) The transport layer has to integrate some adaptation
mechanisms to contribute to end to end performance control.
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Equivalent Differentiated Services
Proportionality
Asymmetry (cf ABE)
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Equivalent Differentiated Services
The EDS model defines an arbitrary number N of classes.Differentiation on delay and loss rate for each class.A class i gets a delay coef di and a loss rate coef li. These coef are constants. let i and j be two classes, the router schedules and drops their
packets so that there is a ratio di/dj between local queuing delays and li/lj between local loss rates.
In order to avoid having privileged classes, coefficients are set:
if di<dj then li>lj or
if di>dj then li<lj for all I in [1,N] and j in [1,N]
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Adaptive Packet Marking: simple algorithm
Delay constraint Loss constraintSelected class
t t
lossdelay
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AIMD EDS packet marking principle
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Validation
EDS layer3 has been implemented in NS and in the Linux QoS kernel
EDS layer 4 has been implemented in SCTP via an adaptation of the AIMD algorithm in NS and Linux kernel and tested on a local emulated platform (NistNet) and on DataTAG link
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Results for a mix of traffic (NS simulations)
Interactive trafficTransfer delay <60%
Real-Time trafficLatency constraint respect 2x >
Bulk transfer#timeout
EDS3/4
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QoSINUS approach
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Develop a Grid testbed: On the Very High Bandwidth experimental network (VTHD) “Active Grid Technology” (dynamicity of the grid)
Develop a middleware prototype: Programmable Network and communication Libraries NFSp & GXFER, MPI madeleine, MOME (DSM), Active network services (QoS, Mcast)
Perform tests with high end applications computing intensive, data intensive, network intensive validation of a “high performance grid” model targeting large scale numerical simulations.
e-Toile GRID project goals
Management Monitoring Security IHM
Globus 2.2 Duroc, GRAM MDS, GRIS/GIIS GSI RSL
e-Toile: Allocator, Loader SIC - SPAM GSI - authoriz. LDT - GUIDE
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Programmable network INRIA RESO/LIP)
Active nodes TAMANOIR and IBP depot (Loci/UTK) deployed at the edge of VTHD
Gigabit supported with a TAN cluster (~1.3Gbits/s): TAN cluster = a front-end with back-ends for load balancing
ENS Lyon
fro
nta
le
Back-end 1
Back-end 2
Back-end N
…
VTHD
TAN CEA
Paris
TAN CERN
GenèveActive Flow
Actif flow
Receiver
Receiver
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QoSINUS: E2E Performance controllability
QoSINUS: Quality of Service Negociate, Invoke, Use
Goals: E2E QoS : an interface « application » <-> « network » Application QoS objective: eg. E2E transfer delay Use Network QoS: DiffServ (packet prioritization) A programmable service (adapt API & algorithm)
QoSinus principles Specification and negociation of a SLS for a microflow by Grid
scheduler or application Programmable mapping of the QoS objective in a packet DSCP
in the first active node (use EF, AF, BE, LBE…). Dynamic Adaptation of packet marking based on measurement
results (network and flow).
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QoS objectives programming
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IPv6inIPv4
IPv6 over MPLS
Nancy
Lyon
Grenoble
Nice
Rouen
ParisAUB
ParisMSO
ParisSTL
Rennes
INRIANancy
INRIA Lyon
FTRDGrenoble
FTRDSophia
FTRDCaen
ENSTFTRD Issy
OpentransitConnectivité IPv6
FTRD Rennes
INRIA
FTRD Lannion
ENST BrBrest
ENST BrRennes
INRIASophia
INRIARennes
IPv6/IPv42.5Gbps
IPv6/IPv41 Gbps
IPv6/IPv4STM1/4
IPv6 sur tunnel
IPv4 seulement Routeurs de sites VTHD++/eToile
Juniper : M20/M40/T640
Cisco GSR 12000
TSR Avici
INT
HEGP
CEA
EDF
PRISM
IMAGSun
Eurecom
VTHD++ plate-forme
CHU
CERN
INRIA Grenoble
CERN
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The VTHD backbone
“Really Very High Bandwidth”: provides 1Gb/s to 2Gb/sdirect access links Up to 4 x 2.5Gb/s in the core;
experimental network great availability Advanced services (Multicast, DiffServ, IPv6, MPLS,
GMPLS/UNI…)
connected to other research networks in EU through the DataTAG link (CERN in Geneva).
The VTHD network is deployed by France Telecom RNRT project VTHD and VTHD++
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DiffServ in VTHD
Application
VTHD
EdgeEF (10%)
Streaming 30% (AF TCP)
AF-UDP (30%)
Best-effort 30%
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Experimental results in e-Toile/ VTHD
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Conclusion
Diffserv philosophie provides the mean to extend the IP forwarding model with scalable and easy to deploy service differentiation mechanisms.Difficult to avoid it if we want to control performances in GRIDS !Standard PHB are deployed (Premium, LBE) in EU NRNs
EDS or propDS provide simple and autonomous solutions to add differentiated services in an IP network. An incremental solution (for access links and LANs) Adaptive end to end transport protocols (packet marking in AIMD...)
QoSINUS exploit and control DiffServ ingress point transparently. Provides a simple and extensible API to application (XML) Provides a multi-domain and transparent solution
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Future Work: Grid5000
Measure the gain obtained with challenging grid applications and grid infrastructures. Interaction with novel transport protocols for bulk transfersExplore deeply the multi-domain multi-service problemExplore the scalability of the EDS and QoSINUS approaches.
GRID5000 project : a large scale cluster interconnection in France With about 5000 processors aggregated With high performance DiffServ network links (RENATER) + high performance latency emulation tools. http://www.grid5000.org
Interconnected with GN2
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More info
RESO project at INRIA:
http://www.ens-lyon.fr/LIP/RESO
e-Toile: http://www.urec.cnrs.fr/etoile
VTHD: http://www.vthd.org
GRID5000: http://www.grid5000.org