SDN Controller Challenges
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Transcript of SDN Controller Challenges
SDN Controller Challenges
The Story Thus Far
• SDN --- centralize the network’s control plane– The controller is effectively the brain of the
network– Controller determines what to do and tell switches
how to do it.
The Story Thus Far
The Story Thus Far
Something Happened!!!!
The Story Thus Far
Let’s Ask the Brian!!!!
The Story Thus FarThink about what happen…Maybe come up with a solution
The Story Thus Far
• Controller runs control function• Control function creates switch state
– F(global network state) Switch state – Global network state can be graph of the network
Tell the network what to do
Challenges with Centralization
• Single point of failure– Fault tolerance
• Performance bottleneck– Scalability– Efficiency (switch-controller latency)
• Single point for security violations
Motivation for Distributed Controllers
• Wide-Area-Network– Wide distribution of switches: from USA to Australia.– High latency between one controller and All switches
• Application + Network growth– Higher CPU load for controller– More memory for storing FIB entries and calculations
• High availabilit
Class Outline
• Fault Tolerance– Google’s B4 paper
• Controller Scalability– Ways to scale the controller– Distributed controllers: Mesh Versus Hierarchy– Implications of controller placement
Fault Tolerance
Google’s B4 Network
• Provides connectivity between DC sites• Uses SDN to control edge switches• Goal: high utilization of links• Insight: fine-grained control over edge and
network can lead to higher utilization• Distributed Controllers– One set of controllers for each Data center (site)
Google’s B4 Network
• Provides connectivity between DC sites• Uses SDN to control edge switches• Goal: high utilization of links• Distributed Controllers– One set of controllers for each Data center (site)
Fault Tolerance in B4
• Each site runs a set of controller• Paxos is run between controllers in a site to
determine master
Quick Overview of Paxos• Given N controllers
– 1 Acts as leader, and N-1 as workers– All N controller maintain the same state
• Switches interact with leader• Change doesn’t happen until whole group agrees• Failure of primary
• N-1 work together to elect a new leader(determine new leader)
Network Events
Propagate State changes
Pros-Cons of Paxos
• Pros– Well understood and studied; gives good FT– Many implementations in the wild– E.g. Zookeeper
• Cons– Time to recover– Impacts through of the put of the entire system
Controller Scalability
What limits a controller’s scalability?
• Number of control messages from switch– Depends on the application logic• E.g. MicroTE/Hedera periodically query all switches for
stats• Reactive controller, evaluated in NoX, requires each
switch to send messages for a new flow– Packet-in (if reactive Apps)– Flow stats, Flow_time-outs
What limits a controller’s scalability?
• Application processing overhead• The controller runs a bunch of application– Similar to: A server running a set of programs– CPU/Memory constraint limit how the app runs
What limits a controller’s scalability?
• Distance between controller and the switches
Controller 1
Hedera L3 FW
How to Scale the Controller.• Obvious: add more controllers.• BUT: how about the applications?– Synchronization/concurrency problems. • Who controls which switch?• Who reacts to which events?
Controller 1
Hedera L3 FW
Controller 2
Hedera L3 FW
Controller N
Hedera L3 FW? ?
Stats + Install OF entries
Medium Sized Networks• Assumption:
– controller can’t store all forwarding table entries in memory – But can process all events and run all apps
• Each controller– Get same network events+ running same app. same output– But store output for only a fraction and config only a fraction
Controller 1
Hedera L3 FW
Controller 2
Hedera L3 FW
Controller N
Hedera L3 FW
Stats + Install OF entries
Medium Sized Networks: hyperflow
• Each controller– Push state to each controller– Each controller things it’s the only one in the network
Controller 1Hedera L3 FW
Controller 2Hedera L3 FW
Controller NHedera L3 FW
Stats + Install OF entries
Sub-subscribe ssytem
Large Sized Networks
• Assumptions– Each controller can’t store all the FIB entries– Each controller can’t run the entire application or
handle events
• Need to partition the application– But how?
Application partition 1
• Approach 1: each controller runs a specific application– How do your resolve conflicts in FW entries– Apps can conflict in the rules they install
Controller 1
Hedera
Controller 2
L3
Controller N
FW
Application partition 2
• Approach 2: all controllers run the same application but for a subset of devices– Results in a Distributed Mesh control plane
Controller 1
Hedera L3 FW
Controller 2
Hedera L3 FW
Controller N
Hedera L3 FW
Abstract Network view
Application Partition 2
• Abstract view exchanged with each other– Abstract view reduces the n/w information used
by each controller
Controller 2
Hedera L3 FW
REAL NETWORK
Controller 2’s View of NETWORK
Abstraction Provided byController 1
Abstraction Provided byController N
ONIX to the SDN Programmer
• Controllers synchronize through a DB or DHT– So each app needs synchronization code.– How do you deal with concurrency.
• How to synchronize between domains.
• How many domains? Or controllers?
• How many switches in a domain?
Application partition 3
• Approach 3: divide application into local, and global.– Results in a hierarchical control plane
• Global Controller and Local Controllers– Applications that do not need network-wide state• Can be run locally without communicate with other
controllers
Are Hierarchical Controllers Feasible
• Examples of local applications:– Link Discovery, Learning switch, local policies
• Examples of local portions of a global algo– Data center Traffic engineering
• Elephant flow detection (hedera)• Predictability detection (MicroTE)
• Local apps/controllers have other benefits– High parallelism– Can be run closer to the devices.
Kandoo: Hierarchical controllers
Controller 1
Hedera L3 FWController 2
Hedera L3 FW
Controller N
Hedera L3 FW
Global ControllerHedera
• 2 levels of controllers: global and local– Local applications are embarrassingly parallel– Local shields global from network events
Kandoo: Hierarchical controllers
Controller 1
Hedera L3 FWController 2
Hedera L3 FW
Controller N
Hedera L3 FW
Global ControllerHedera
• Local Controllers: run local apps– Returns abstract view to the global controller– Reduces # events sent to global and reduce size of network
seen by
Kandoo: Hierarchical controllers
Controller 1
Hedera L3 FWController 2
Hedera L3 FW
Controller N
Hedera L3 FW
Global ControllerHedera
• Global Controllers– Runs global apps: AKA apps that need network
wide state
Hedera Reminder
• Goal: reduce network contention• Insight: contention happens when elephants
share paths.• Solution:– Detect Elephant flows– Place Elephant flows on different flows
Implementing Hedera in Onix
Controller 1
Hedera: detection +placement
Controller 2
Hedera: detection+placement
• 2 levels of controllers: global and local– Local applications are embarrassingly parallel– Local shields global from network events
StatsStatsFlow
Table entries
Flow Table entries
Exchange TM+detection
Implementing Hedera in Kandoo
Controller 1Elephant detection
Controller 2 Controller N
Global ControllerHedera: Global placement
• Local Controllers: get stats from networks + elephant detection• Global Controller: decide flow placement + flow installation
Elephant detection Elephant detection
Inform of elephant flows
Stats
Install new flow table entries
Implementing B4 in Kandoo like architecture
Site ControllerElephant detection
Site Controller 2 Site Controller N
Global Controller
TE+BW allocator
• Local Controllers: get stats from networks + determines demand• Global Controller: calculate paths for traffic
Elephant detection Elephant detection
Install TE Ops
Stats + Install OF entries
TE DB
Inform of Flow demands
Kandoo to the SDN Programmer
• Think of what is local and what is global– When apps are written, annotate with local flag
• Kandoo will automatically place local – And place global.
• Kandoo restricts messages between global and local controllers– You can’t send OF styles messages – Must send Kandoo style messages
Summary
• Centralization provide simplicity at the cost of reliability and scalability
• Replication can improve reliability and scalability• For Reliability, Paxos is an option• For Scalability, conqueror and divide – Partition the applications
• Kandoo: Local apps and global apps– Partition the network
• Onix: each controller controls a subset of switches (Domain)