High-Level Abstractions for Programming Software Defined

Networks

Joint with Nate Foster, David Walker, Arjun Guha, Rob Harrison, Chris Monsanto, Joshua Reich, Mark Reitblatt, Cole Schlesinger

Jennifer RexfordPrinceton University

http://www.cs.princeton.edu/~jrex

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Software Defined Networks

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decouple control and data planes

Software Defined Networks

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decouple control and data planesby providing open standard API

Software Defined Networks

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(Logically) Centralized Controller

Controller Platform

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Protocols Applications

Controller PlatformController Application

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Payoff

• Cheaper equipment• Faster innovation• Easier management

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But How Should We Program SDNs?

Controller Platform

Controller ApplicationNetwork-wide visibility and control

Direct control via open interface

Today’s controller APIs are tied to the underlying hardware

OpenFlow Networks

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Data Plane: Packet Handling

• Simple packet-handling rules– Pattern: match packet header bits– Actions: drop, forward, modify, send to controller – Priority: disambiguate overlapping patterns– Counters: #bytes and #packets

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1. src=1.2.*.*, dest=3.4.5.* drop 2. src = *.*.*.*, dest=3.4.*.* forward(2)3. src=10.1.2.3, dest=*.*.*.* send to controller

Control Plane: Programmability

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Events from switchesTopology changes,Traffic statistics,Arriving packets

Commands to switches(Un)install rules,Query statistics,Send packets

Controller Platform

Controller Application

E.g.: Server Load Balancing• Pre-install load-balancing policy• Split traffic based on source IP

src=0*

src=1*

Seamless Mobility/Migration• See host sending traffic at new location• Modify rules to reroute the traffic

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Programming Abstractions for Software Defined Networks

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Network Control Loop

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Readstate

OpenFlowSwitches

Writepolicy

Compute Policy

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Reading State

SQL-Like Query Language

Reading State: Multiple Rules

• Traffic counters– Each rule counts bytes and packets– Controller can poll the counters

• Multiple rules– E.g., Web server traffic except for source 1.2.3.4

• Solution: predicates– E.g., (srcip != 1.2.3.4) && (srcport == 80)– Run-time system translates into switch patterns

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1. srcip = 1.2.3.4, srcport = 802. srcport = 80

Reading State: Unfolding Rules

• Limited number of rules– Switches have limited space for rules– Cannot install all possible patterns

• Must add new rules as traffic arrives– E.g., histogram of traffic by IP address– … packet arrives from source 5.6.7.8

• Solution: dynamic unfolding– Programmer specifies GroupBy(srcip)– Run-time system dynamically adds rules

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1. srcip = 1.2.3.41. srcip = 1.2.3.42. srcip = 5.6.7.8

Reading: Extra Unexpected Events

• Common programming idiom– First packet goes to the controller– Controller application installs rules

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packets

Reading: Extra Unexpected Events

• More packets arrive before rules installed?– Multiple packets reach the controller

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packets

Reading: Extra Unexpected Events

• Solution: suppress extra events– Programmer specifies “Limit(1)”– Run-time system hides the extra events

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packets

not seen byapplication

Frenetic SQL-Like Query Language

• Get what you ask for– Nothing more, nothing less

• SQL-like query language– Familiar abstraction– Returns a stream– Intuitive cost model

• Minimize controller overhead– Filter using high-level patterns– Limit the # of values returned – Aggregate by #/size of packets

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Select(bytes) *Where(in:2 & srcport:80) *GroupBy([dstmac]) *Every(60)

Select(packets) *GroupBy([srcmac]) *

SplitWhen([inport]) *Limit(1)

Learning Host Location

Traffic Monitoring

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Computing Policy

Parallel and Sequential Composition

Abstract Topology Views

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Combining Many Networking Tasks

Controller Platform

Monitor + Route + FW + LB

Monolithic application

Hard to program, test, debug, reuse, port, …

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Modular Controller Applications

Controller Platform

LBRout

eMonit

orFW

Easier to program, test, and debugGreater reusability and portability

A module for each task

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Beyond Multi-Tenancy

Controller Platform

Slice 1

Slice 2

Slice n

... Each module controls a different portion of the traffic

Relatively easy to partition rule space, link bandwidth, and network events across modules

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Modules Affect the Same Traffic

Controller Platform

LBRout

eMonit

orFW

How to combine modules into a complete application?

Each module partially specifies the handling of the traffic

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Parallel Composition [ICFP’11, POPL’12]

Controller Platform

Route on dest

prefix

Monitor on source

IP+

dstip = 1.2/16 fwd(1)dstip = 3.4.5/24 fwd(2)

srcip = 5.6.7.8 countsrcip = 5.6.7.9 count

srcip = 5.6.7.8, dstip = 1.2/16 fwd(1), countsrcip = 5.6.7.8, dstip = 3.4.5/24 fwd(2), countsrcip = 5.6.7.9, dstip = 1.2/16 fwd(1), countsrcip = 5.6.7.9, dstip = 3.4.5/24 fwd(2), count

• Spread client traffic over server replicas– Public IP address for the service– Split traffic based on client IP– Rewrite the server IP address

• Then, route to the replica

Example: Server Load Balancer

clients

1.2.3.4

load balancer

server replicas

10.0.0.1

10.0.0.2

10.0.0.3

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Sequential Composition [NSDI’13]

Controller Platform

RoutingLoad Balancer >>

dstip = 10.0.0.1 fwd(1)dstip = 10.0.0.2 fwd(2)

srcip = 0*, dstip=1.2.3.4 dstip=10.0.0.1srcip = 1*, dstip=1.2.3.4 dstip=10.0.0.2

srcip = 0*, dstip = 1.2.3.4 dstip = 10.0.0.1, fwd(1)srcip = 1*, dstip = 1.2.3.4 dstip = 10.0.0.2, fwd(2)

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Dividing the Traffic Over Modules

• Predicates– Specify which traffic traverses which

modules– Based on input port and packet-header

fields

Routing

Load Balancer

Monitor

Routing

dstport != 80

dstport = 80 >>

+

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High-Level Architecture

Controller Platform

M1 M2 M3Composition

Spec

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Partially Specifying Functionality

• A module should not specify everything– Leave some flexibility to other modules– Avoid tying the module to a specific

setting

• Example: load balancer plus routing– Load balancer spreads traffic over

replicas– … without regard to the network paths

Load Balancer

Routing>>

Avoid custom interfaces between the modules

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Abstract Topology Views [NSDI’13]

• Present abstract topology to the module– Implicitly encodes the constraints – Looks just like a normal network– Prevents the module from overstepping

34Real network Abstract view

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Separation of Concerns

• Hide irrelevant details– Load balancer doesn’t see the internal

topology or any routing changes

Routing view Load-balancer view

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High-Level Architecture

Controller Platform

View Definitions

M1 M2 M3Composition

Spec

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Supporting Topology Views

• Virtual ports– (V, 1): [(P1,2)]– (V, 2): [(P2, 5)]

• Simple firewall policy– in=1 out=2

• Virtual headers– Push virtual ports– Route on these ports– From (P1,2) to (P2,5)

V1 2

firewall

routing

P1 P2

1 122

3 3

4

4

5

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Writing State

Consistent Updates

Writing Policy: Avoiding Disruption

Invariants• No forwarding loops• No black holes• Access control• Traffic waypointing

Writing Policy: Path for New Flow

• Rules along a path installed out of order?– Packets reach a switch before the rules do

40Must think about all possible packet and event orderings.

packets

Writing Policy: Update Semantics

• Per-packet consistency– Every packet is processed by– … policy P1 or policy P2 – E.g., access control, no loops

or blackholes

• Per-flow consistency– Sets of related packets are processed by– … policy P1 or policy P2,– E.g., server load balancer, in-order delivery,

…

P1

P2

Writing Policy: Policy Update

• Simple abstraction– Update entire configuration at once

• Cheap verification– If P1 and P2 satisfy an invariant– Then the invariant always holds

• Run-time system handles the rest– Constructing schedule of low-level updates– Using only OpenFlow commands!

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P1

P2

Writing Policy: Two-Phase Update

• Version numbers– Stamp packet with a version number (e.g., VLAN tag)

• Unobservable updates– Add rules for P2 in the interior– … matching on version # P2

• One-touch updates– Add rules to stamp packets

with version # P2 at the edge

• Remove old rules– Wait for some time, then

remove all version # P1 rules

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Writing Policy: Optimizations

• Avoid two-phase update– Naïve version touches every switch– Doubles rule space requirements

• Limit scope – Portion of the traffic– Portion of the topology

• Simple policy changes– Strictly adds paths– Strictly removes paths 44

Frenetic Abstractions

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SQL-likequeries

OpenFlowSwitches

ConsistentUpdates

Policy Composition

Related Work

• Programming languages– FRP: Yampa, FrTime, Flask, Nettle– Streaming: StreamIt, CQL, Esterel, Brooklet, GigaScope– Network protocols: NDLog

• OpenFlow– Language: FML, SNAC, Resonance– Controllers: ONIX, POX, Floodlight, Nettle, FlowVisor– Testing: NICE, FlowChecker, OF-Rewind, OFLOPS

• OpenFlow standardization– http://www.openflow.org/– https://www.opennetworking.org/

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Conclusion

• SDN is exciting– Enables innovation– Simplifies management– Rethinks networking

• SDN is happening– Practice: useful APIs and good industry traction– Principles: start of higher-level abstractions

• Great research opportunity– Practical impact on future networks– Placing networking on a strong foundation

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Frenetic Project

http://frenetic-lang.org

• Programming languages meets networking– Cornell: Nate Foster, Gun Sirer, Arjun Guha, Robert Soule,

Shrutarshi Basu, Mark Reitblatt, Alec Story

– Princeton: Dave Walker, Jen Rexford, Josh Reich, Rob Harrison, Chris Monsanto, Cole Schlesinger, Praveen Katta, Nayden Nedev

Short overview at http://www.cs.princeton.edu/~jrex/papers/frenetic12.pdf