Central Control over Distributed Routing fibbing.net SIGCOMM Stefano Vissicchio 18th August 2015 UCLouvain Joint work with O. Tilmans (UCLouvain), L. Vanbever.

Slides:



Advertisements
Similar presentations
Path Splicing with Network Slicing Nick Feamster Murtaza Motiwala Santosh Vempala.
Advertisements

Jennifer Rexford Princeton University MW 11:00am-12:20pm Logically-Centralized Control COS 597E: Software Defined Networking.
Software-defined networking: Change is hard Ratul Mahajan with Chi-Yao Hong, Rohan Gandhi, Xin Jin, Harry Liu, Vijay Gill, Srikanth Kandula, Mohan Nanduri,
Logically Centralized Control Class 2. Types of Networks ISP Networks – Entity only owns the switches – Throughput: 100GB-10TB – Heterogeneous devices:
© 2010 Cisco and/or its affiliates. All rights reserved. 1 Segment Routing Clarence Filsfils – Distinguished Engineer Christian Martin –
Opportunities and Research Challenges of Hybrid Software Defined Networks ACM SIGCOMM Computer Communication Review table of contents archive Volume 44.
Improving TCP Performance over Mobile Ad Hoc Networks by Exploiting Cross- Layer Information Awareness Xin Yu Department Of Computer Science New York University,
Dynamic Routing Scalable Infrastructure Workshop, AfNOG2008.
Mobile and Wireless Computing Institute for Computer Science, University of Freiburg Western Australian Interactive Virtual Environments Centre (IVEC)
1/14 Ad Hoc Networking, Eli M. Gafni and Dimitri P. Bertsekas Distributed Algorithm for Generating Loop-free Routes in Networks With Frequently.
Revisiting Ethernet: Plug-and-play made scalable and efficient Changhoon Kim and Jennifer Rexford Princeton University.
Network Architecture for Joint Failure Recovery and Traffic Engineering Martin Suchara in collaboration with: D. Xu, R. Doverspike, D. Johnson and J. Rexford.
Ashish Gupta Under Guidance of Prof. B.N. Jain Department of Computer Science and Engineering Advanced Networking Laboratory.
Traffic Engineering With Traditional IP Routing Protocols
Traffic Engineering Jennifer Rexford Advanced Computer Networks Tuesdays/Thursdays 1:30pm-2:50pm.
Shadow Configurations: A Network Management Primitive Richard Alimi, Ye Wang, Y. Richard Yang Laboratory of Networked Systems Yale University.
1 Traffic Engineering for ISP Networks Jennifer Rexford IP Network Management and Performance AT&T Labs - Research; Florham Park, NJ
CSE331: Introduction to Networks and Security Lecture 9 Fall 2002.
Traffic Engineering in IP Networks Jennifer Rexford Computer Science Department Princeton University; Princeton, NJ
A General approach to MPLS Path Protection using Segments Ashish Gupta Ashish Gupta.
1 Design and implementation of a Routing Control Platform Matthew Caesar, Donald Caldwell, Nick Feamster, Jennifer Rexford, Aman Shaikh, Jacobus van der.
A Routing Control Platform for Managing IP Networks Jennifer Rexford Princeton University
Rethinking Internet Traffic Management: From Multiple Decompositions to a Practical Protocol Jiayue He Princeton University Joint work with Martin Suchara,
Routing.
A Routing Control Platform for Managing IP Networks Jennifer Rexford Princeton University
Backbone Networks Jennifer Rexford COS 461: Computer Networks Lectures: MW 10-10:50am in Architecture N101
Multipath Routing Jennifer Rexford Advanced Computer Networks Tuesdays/Thursdays 1:30pm-2:50pm.
A Routing Control Platform for Managing IP Networks Jennifer Rexford Princeton University
A General approach to MPLS Path Protection using Segments Ashish Gupta Ashish Gupta.
Multipath Protocol for Delay-Sensitive Traffic Jennifer Rexford Princeton University Joint work with Umar Javed, Martin Suchara, and Jiayue He
1 Network-wide Decision Making: Toward a Wafer-thin Control Plane Jennifer Rexford, Albert Greenberg, Gisli Hjalmtysson ATT Labs Research David A. Maltz,
Jennifer Rexford Princeton University MW 11:00am-12:20pm Wide-Area Traffic Management COS 597E: Software Defined Networking.
© 2006 Cisco Systems, Inc. All rights reserved. ICND v2.3—3-1 Determining IP Routes Introducing Link-State and Balanced Hybrid Routing.
Analysis of RIP, OSPF, and EIGRP Routing Protocols using OPNET Group 5: Kiavash Mirzahossein Michael Nguyen Sarah Elmasry
Packet-Switching Networks Routing in Packet Networks.
Jennifer Rexford Fall 2014 (TTh 3:00-4:20 in CS 105) COS 561: Advanced Computer Networks BGP.
Floodless in SEATTLE : A Scalable Ethernet ArchiTecTure for Large Enterprises. Changhoon Kim, Matthew Caesar and Jenifer Rexford. Princeton University.
Measuring IP Network Routing Convergence A new approach to the problem 59.
The Network Layer Introduction  functionality and service models Theory  link state and distance vector algorithms  broadcast algorithms  hierarchical.
Distance-vector Multicast Routing Protocol (DVMRP)
IP fast reroute s olutions and challenges Amund Kvalbein.
Lecture 2 Agenda –Finish with OSPF, Areas, DR/BDR –Convergence, Cost –Fast Convergence –Tools to troubleshoot –Tools to measure convergence –Intro to implementation:
Intradomain Traffic Engineering By Behzad Akbari These slides are based in part upon slides of J. Rexford (Princeton university)
Jennifer Rexford Fall 2010 (TTh 1:30-2:50 in COS 302) COS 561: Advanced Computer Networks Backbone.
Achieving Convergence-Free Routing using Failure-Carrying Packets K. Lakshminarayanan et al. Presented by Ang Li 06/29/07.
Evolving Toward a Self-Managing Network Jennifer Rexford Princeton University
IP Routing Principles. Network-Layer Protocol Operations Each router provides network layer (routing) services X Y A B C Application Presentation Session.
Evolving Toward a Self-Managing Network Jennifer Rexford Princeton University
P4 Amore! ( Or, How I Learned to Stop Worrying and Love P4) Jennifer Rexford Princeton University.
Spring 2000CS 4611 Routing Outline Algorithms Scalability.
1 Chapter 4: Internetworking (IP Routing) Dr. Rocky K. C. Chang 16 March 2004.
© 2015 Cisco and/or its affiliates. All rights reserved. Public 1 Toerless Eckert, IJsbrand Wijnands,
1 Traffic Engineering By Kavitha Ganapa. 2 Introduction Traffic engineering is concerned with the issue of performance evaluation and optimization of.
Separating Routing From Routers Jennifer Rexford Princeton University
© 2002, Cisco Systems, Inc. All rights reserved..
A Framework for Computed Multicast applied to MPLS based Segment Routing draft-allan-spring-mpls-multicast-framework-00 Dave Allan, Jeff Tantsura; Ericsson.
Preliminaries: EE807 Software-defined Networked Computing KyoungSoo Park Department of Electrical Engineering KAIST.
PC Rev 1 Fibbing, coding, vectoring April 21, 2016.
University of Maryland College Park
The DPIaaS Controller Prototype
Network Layer.
© 2002, Cisco Systems, Inc. All rights reserved.
Routing.
Software Defined Networking (SDN)
Dynamic Routing and OSPF
COS 561: Advanced Computer Networks
Backbone Traffic Engineering
BGP Instability Jennifer Rexford
Routing.
Using Service Function Chaining for In-Network Computation
Presentation transcript:

Central Control over Distributed Routing fibbing.net SIGCOMM Stefano Vissicchio 18th August 2015 UCLouvain Joint work with O. Tilmans (UCLouvain), L. Vanbever (ETH Zurich) and J. Rexford (Princeton)

SDN (e.g., OpenFlow, Segment Routing) Traditional (e.g., IGP, distributed MPLS) SDN is based on antithetical architecture with respect to traditional networking

Centralization improves network management, but sacrifices robustness of distributed protocols Manageability Flexibility Scalability Robustness SDN ad hoc low highest high Traditional IGP, tunnelling (RSVP-TE) by design high low

We propose Fibbing, a hybrid SDN architecture Fibbing central control over link-state IGPs

Manageability Flexibility Scalability Robustness SDN ad hoc low highest high Traditional IGP, tunnelling (RSVP-TE) by design high low Fibbing by design high Fibbing combines advantages of SDN and traditional networking

Manageability Flexibility Scalability Robustness Fibbing by design high same as SDN per-destination full control thanks to partial distribution some function are distributed Fibbing combines advantages of SDN and traditional networking

Central Control over Distributed Routing fibbing.net Manageability1 Scalability 2Flexibility 3 Robustness4

Central Control over Distributed Routing fibbing.net Manageability1 Scalability 2Flexibility 3 Robustness4

SDN achieves high manageability by centralizing both computation and installation derives FIB entries install FIB entries computes paths requirements e.g., OpenFlow controller or RCP

Fibbing is as manageable as SDN, but centralizes only high-level decisions Fibbing controller computes paths requirements

Fibbing keeps installation distributed, relying on distributed protocols distributed control-plane install FIB entries computes FIB entries data-plane

Distributed installation is controlled by injecting carefully-computed information control-plane messages

We study which messages to inject for controlling intra-domain routing protocols forwarding paths weighted topology shortest-path computation link-state IGP inputfunctionoutput

The output of the controlled protocol is specified by operators’ requirements forwarding paths weighted topology shortest-path computation inputfunction provided by operators or controller optimizers (e.g., DEFO) link-state IGP output

Inverse To control IGP output, the Fibbing controller inverts the shortest-path function forwarding paths weighted topology shortest-path computation

Central Control over Distributed Routing fibbing.net Manageability1 Scalability 2Flexibility 3 Robustness4

AB C destinationsource Consider this simple network (implemented with Cisco routers) D1 D2 X

AB CX An IGP control-plane computes shortest paths on a shared weighted topology D1 D2 control-plane shortest paths

IGP shortest paths are translated into forwarding paths on the data-plane D1 D2 data-plane traffic flow AB C X AB CX D1 D2 control-plane

In Fibbing, operators can ask the controller to modify forwarding paths requirement (C,A,B,X,D2) AB CX D1 D

The Fibbing controller injects information on fake nodes and links to the IGP control-plane node V1, link (V1,C), map (V1,C) to (C,A) AB CX D1 D requirement (C,A,B,X,D2)

Informations are flooded to all IGP routers in the network node V1, link (V1,C), map (V1,C) to (C,A) AB CX D1 D requirement (C,A,B,X,D2)

Fibbing messages augment the topology seen by all IGP routers 1 D2 node V1, link (V1,C), map (V1,C) to (C,A) AB CX D1 D V1 requirement (C,A,B,X,D2)

Augmented topologies translate into new control-plane paths AB CX D1 D requirement (C,A,B,X,D2) 1 D2 V1 node V1, link (V1,C), map (V1,C) to (C,A)

Augmented topologies translate into new data-plane paths AB C D1 D2 X AB CX D1 D D2 V1 node V1, link (V1,C), map (V1,C) to (C,A) requirement (C,A,B,X,D2)

Theorem Fibbing can program arbitrary per-destination paths Any set of forwarding DAGs can be enforced by Fibbing

Fibbing can program arbitrary per-destination paths paths to the same destination do not create loops Theorem Any set of forwarding DAGs can be enforced by Fibbing

By achieving full per-destination control, Fibbing is highly flexible fine-grained traffic steering (middleboxing) per-destination load balancing (traffic engineering) backup paths provisioning (failure recovery) Theorem Any set of forwarding DAGs can be enforced by Fibbing

Central Control over Distributed Routing fibbing.net Manageability1 Scalability 2Flexibility 3 Robustness4

We implemented a Fibbing controller network topology + path reqs. per-destination forwarding DAGs augmented topology reduced topology running network CompilationAugmentationOptimization Injection/ Monitoring

We also propose algorithms to compute augmented topologies of limited size network topology + path reqs. per-destination forwarding DAGs augmented topology reduced topology running network CompilationAugmentationOptimization Injection/ Monitoring compilation heuristics per-destination augmentation cross-destination optimization

network topology + path reqs. per-destination forwarding DAGs augmented topology reduced topology running network CompilationAugmentationOptimization Injection/ Monitoring compilation heuristics per-destination augmentation 1.simple 2.merger cross-destination optimization For our Fibbing controller, we propose algorithms to be run in sequence

A B C DEF original shortest-path “down and to the right” Consider the following example, with a drastic forwarding path change A B C DEF desired shortest-path “up and to the right”

A B C DEF Simple adds one fake node for every router that has to change next-hop 1

1 1 1 Merger iteratively merges fake nodes (starting from Simple’s output) A B C DEF

1 1 1 A B C DEF Merger iteratively merges fake nodes (starting from Simple’s output)

This way, Merger programs multiple next-hop changes with a single fake node A B C DEF

A B C DEF Previous SDN solutions (e.g., RCP) cannot do the same This way, Merger programs multiple next-hop changes with a single fake node

Simple and Merger achieve different trade-offs in terms of time and optimization efficiency and up to 90% with cross-destination optimization Merger reduces fake nodes by up to 50% Merger takes 0.1 seconds Simple runs in milliseconds We ran experiments on Rocketfuel topologies, with at least 25% of nodes changing next-hops

We implemented the machinery to listen to OSPF and augment the topology network topology + path reqs. per-destination forwarding DAGs augmented topology reduced topology running network CompilationAugmentationOptimization Injection/ Monitoring OSPF interaction module

Experiments on real routers show that Fibbing has very limited impact on routers router memory (MB) # fake nodes DRAM is cheap >> # real routers

Experiments on real routers show that Fibbing has very limited impact on routers router memory (MB) # fake nodes DRAM is cheap CPU utilization always under 4%

Experiments on real routers show that Fibbing does not impact IGP convergence Upon link failure, we registered no difference in the (sub-second) IGP convergence with up to 100,000 fake nodes and destinations no fake nodes

Experiments on real routers show that Fibbing achieves fast forwarding changes installation time (seconds) μ s/entry # fake nodes

Central Control over Distributed Routing fibbing.net Manageability1 Scalability 2Flexibility 3 Robustness4

Fibbing improves robustness by relying on the underlying IGP thanks to its shared topology see paper IGP provides fast failure detection and control-plane sync IGPs re-converge quickly [Filsfils07] no controller action needed in some cases Fibbing supports fail-open and fail-close semantics

D2 V1 AB C X We ran a failure recovery case study, with distributed Fibbing controller D1 D2 ( fail-open(D2) ); ( fail-close(D1) );

Fibbing survives replica failures with no impact on forwarding D2 V1 AB C X D1 D2 ( fail-open(D2) ); ( fail-close(D1) );

Fibbing reacts to network failures quickly re-optimizing forwarding AB C X D1 D2 ( fail-open(D2) ); ( fail-close(D1) );

Fibbing reacts to partitions, respecting fail-close and fail-open semantics AB C X D1 D2 ( fail-open(D2) ); ( fail-close(D1) );

Fibbing recovers correctly (as soon as failures are fixed) D2 V1 AB C X D1 D2 ( fail-open(D2) ); ( fail-close(D1) );

Fibbing shows the benefits of central control over distributed protocols heavy work is still done by routers avoids SDN deployment hurdles Simplify controllers and improves robustness network-wide automated control Realizes SDN management model Works today, on existing networks

Stefano Vissicchio Tell me lies, tell me sweet little lies — Fleetwood Mac Central Control over Distributed Routing fibbing.net