laurent lefèvre inria / lip (umr cnrs, inria, ens, ucb) [email protected]
DESCRIPTION
Heavy and lightweight dynamic network services: challenges and experiments for designing intelligent solutions in evolvable next generation networks. Laurent Lefèvre INRIA / LIP (UMR CNRS, INRIA, ENS, UCB) [email protected] WAGEN Workshop - Jiuzhaigou - April 8, 2005 -. Challenges. - PowerPoint PPT PresentationTRANSCRIPT
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Heavy and lightweight dynamic network services: challenges and experiments for
designing intelligent solutions in evolvable next generation networks
Laurent Lefèvre
INRIA / LIP (UMR CNRS, INRIA, ENS, UCB)[email protected]
WAGEN Workshop - Jiuzhaigou - April 8, 2005-
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Challenges Active networks : programmable network
equipments which allow deployment of heterogeneous services in data plan (heavy services) In control / management plans (lightweight services)
How to urbanize networks with autonomous dynamic services ?
How to efficiently manage such heterogeneous services for providing efficient solutions inside the network ?
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Patterns Robustness
Best effort services Garanted services
Personnalized Generic services Dedicated services (application, user, stream…)
TTL One-usage service Persistant services
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Roadmap
Urbanization of dynamic network services Lightweight network functionalities Cluster-based network equipments Load balancing strategies for
heterogeneous services
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Where to map dynamic autonomous network services?
Urbanization is an open problem Mixes networking aspects with service
composition Access networks Peering points Front end of clusters LAN ?
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Service on data path
Proxy mode Dynamic deployment
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Replicated network service
Same service replicated on several network equipments
On the fly deployment with data streams
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Distributed network autonomous service
Service composition Allow pipelined approach Dealing with fault tolerance / load
balancing
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Unique service out of the data path
Dedicated equipment (legacy solution) Requires intelligent forwarding
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Distributed service outside the data path
Requires sensors to evaluate cost of multiple fwd operations
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Proposing a generic active environment able to handle heterogeneous services : The Tamanoir project
Supporting requirements of current networks (Gbits)
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Tamanoir Architecture : adapted for heterogeneous services
Resources consuming services : distributed storage, streams adaptation, on the fly compression, cryptography…
Services deployment / linked with middleware : reliable multicast…
Middle services : content based routing, QoS...
Light network services : packet marking, QoS…
NIC (Programmable)
Kernel
Execution
environment
Distributed resources
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Active service deployment
From application / middleware From TAN From network service Broker
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Tamanoir Active Node (TAN)Execution environment
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Performance evaluation of middle services
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Solution / Problem Simple Java service in user space can
support up to 450 Mbits ! (we eat the ants ! )
A stand-alone active node is not enough to fully support and apply active service to Gbit streams
Need to put lightweight network functionalities close to the network
Explore kernel services
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Kernel support for active node
NIC (Programmable)
Kernel
Execution
environment
Distributed resources
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Kernel Support
• Module inside Linux kernel : using netfilter
• Filtering ANEP packets• Allowing packet to cross the active node through the kernel space• Efficiently put ANEP packets inside the service in user space
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Netfilter Protocols define hooks on the packet way
inside IP stack Associate hooks and personalized
applications /services
1
52
43Routing
Routing
Local process
NF_IP_POST_ROUTINGNF_IP_FORWARD
NF_IP_LOCAL_OUTNF_IP_LOCAL_IN
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Communication between active service and OS module
A Tamanoir active service : a java part + kernel module Message control / parameters
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Performance evaluation
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Solution / Problem
Kernel active services greatly reduce latency for transient packets
Only applicable to lightweight network functionalities (state, CPU consumption..)
Reduce portability of active services What about CPU consuming services ?
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Cluster-based active node
NIC (Programmable)
Kernel
Execution
environment
Distributed resources
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Tamanoir architecture : on a cluster
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Pushing performances
Improving performances of active nodes : using clustering technology
Linux Virtual Server Strategies :
Round robin Least connected
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Performance evaluation
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Solution / Problem We support a full Gbit streams with a small
cluster based Tamanoir active node ! We need more resources for CPU consuming
active services How to balance workload between internal
nodes of an active node without knowing length of streams and needed services ?
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Feedback stream based load balancing policy (FBSb)
Needs dynamic strategies for heterogeneous deployment
FBSb Front-end machine with
updated “weight” table (CPU and memory consumption of back-end machines)
Back-end machines with feedback agents and sensors
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Experiments Heavy service (3-DES encryption) : this service
makes an intensive use of CPU (1 stream calling this service saturates a CPU, in our test implementation);
Medium service (stateful traffic analysis) : this service uses the CPU in a less intensive way, but its impact is not transparent (3-4 streams calling this service saturate a CPU, in our test implementation).
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Experiments 200: composed by 1 stream calling a service of
encryption and 11 streams calling for a traffic analysis with different delays of arrival of 1 second (201), 2 seconds (202) and 5 seconds (205).
300: composed by 4 streams calling a service of encryption and 8 streams calling for traffic analysis. with different delays of arrival of 0 second (300), 1 second (301) and 2 seconds (302).
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Experiments : FBSb, RR, LCFBSb FBSb FBSb RR RR RR LC LC LC
Test MAX AVG MIN MAX AVG MIN MAX AVG MIN
201 38.2 20.2 15.9 43.2 20.1 15.5 38.5 20.3 15.4
202 33.3 20 15.7 37.4 20.1 15.4 36.4 20.1 15.4
205 32.9 19.4 15.5 38.8 19.6 15.4 37.3 19.6 15.4
300 52 24.1 16.1 93.6 26 15.4 64.6 25.5 16.3
301 50.8 24.6 15.4 90.3 26.9 16.1 64 25.6 15.4
302 50.9 23.2 15.3 92.9 25.5 15.9 57.8 25 15.6
RR and LC : efficient if homogeneous dynamic services FBSb : efficient when heterogeneous deployment
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Conclusions and future works
We propose a gigabit supporting software based active node using kernel module deployment and cluster
Providing load balancing support inside cluster-based active equipments is a mandatory aspect for performances
Research could also benefit for network processors technology / programmable network interface cards
Deployment of large scale active/programmable platform based on emulation : French Grid5000 project
http://www.ens-lyon.fr/LIP/RESO/Software/Tamanoir