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Radhika Niranjan Mysore, Andreas Pamboris, Nathan
Farrington,
Nelson Huang, Pardis Miri,
Sivasankar Radhakrishnan, Vikram Subramanya, and Amin
Vahdat
Department of Computer Science and Engineering
University of California San Diego
PortLand: A Scalable Fault-Tolerant Layer
2
Data Center Network Fabric
1
Abstract
 A scalable, easily manageable, fault-tolerant,
and efficient data center network fabric.
 Existing layer 2 and layer 3 network protocols
face limitations in: lack of scalability, difficult
management, inflexible communication, or
limited support for virtual machine migration.
 PortLand, a scalable, fault tolerant layer 2
routing and forwarding protocol for data center
environments.
2
Introduction
 Increasing trend toward migrating applications,
computation and storage into data centers.
 Current network protocols impose significant
management overhead at this scale.
 Ideally, data center network architects and
administrators would have “plug-and-play”
deployment for switches.
3
Future Scenario
 R1. Any VM may migrate to any physical
machine.
 R2. An administrator should not need to
configure any switch before deployment.
 R3. Any end host should be able to efficiently
communicate with any other end host in the data
center along any of the available physical
communication paths.
 R4. There should be no forwarding loops.
 R5. Failures will be common at scale, so failure
detection should be rapid and efficient.
4
Background
 Data center network
1. Topology: hierarchical network tree
2. Forwarding:
Layer 3 forwarding will impose administrative
burden.
Layer 2 forwarding does not scale to networks
with tens of thousands of hosts. And STP would
limit performance.
Layer 2.5 VLAN forwarding limits flexibility for
dynamically changing communication patterns.
3. End Host Virtualization
To migrate a VM from one physical machine to
another, layer 2 and Layer 3 both have some
5
Fat Tree Networks
In general, a three-stage fat tree built from k-port switches can support
non-blocking communication among k³/4 end hosts using 5k²/4
individual k-port switches. We split the fat tree into three layers, labeled
edge, aggregation and core as in Figure 1. The fat tree as a whole is
split into k individual pods, with each pod supporting non-blocking
operation among k²/4 hosts.
6
Design
 The goal of PortLand is to deliver scalable layer 2
routing, forwarding, and addressing for data
center network environments.
 The baseline multi-rooted network topology is
known and relatively fixed. (Fat Tree)
 Building and maintaining data centers with tens of
thousands of compute elements requires
modularity, advance planning, and minimal
human interaction. When expansion does occur
to the network, it typically involves adding more
leaves.
7
Fabric Manager
 PortLand employs a logically centralized fabric
manager that maintains soft state about network
configuration information such as topology.
 In PortLand, we restrict the amount of centralized
knowledge and limit it to soft state. In this
manner, we eliminate the need for any
administrator configuration of the fabric manager
(e.g., number of switches, their location, their
identifier).
8
Positional Pseudo MAC
Addresses
 PMAC : encodes the location of an end host in the
topology.
 The end hosts remain unmodified actual MAC (AMAC)
addresses.
 Hosts performing ARP requests receive the PMAC of the
destination host.
 All packet forwarding proceeds based on PMAC
addresses.
 Egress switches perform PMAC to AMAC header rewriting
to maintain unmodified MAC at the destination host.
 pod:position:port:vmid
pod (16 bits): the pod number of the edge switch
position (8 bits): its position in the pod
port (8 bits): the switch-local view of the port number
the host is connected to.
vmid (16 bits): multiplex multiple virtual machines on
the same physical machine
9
PMAC (Cont.)
10
PMAC(Cont.)
 When an ingress switch sees a source MAC address
never observed before, the packet is vectored to the
switch software.
 The software creates an entry in a local PMAC table
mapping the host's AMAC and IP address to its
PMAC.
 The switch constructs the PMAC as described above
and communicates this mapping to the fabric
manager.
 The fabric manager uses this state to respond to ARP
requests. The switch also creates the appropriate flow
table entry to rewrite the PMAC destination address to
the AMAC for any traffic destined to the host.
 Implemented by OpenFlow
11
Proxy-based ARP
 We leverage the fabric manager to reduce
broadcast overhead in the common case. Uses
fabric manager to get the ARP mapping, if not
get, fabric manager will broadcast.
12
Distributed Location Discovery
 In order to plug-and-play, we present a Location Discovery
Protocol (LDP) to set switch position in the global topology.
 PortLand switches periodically send a Location Discovery
Message (LDM) out all of their ports both, to set their
positions and to monitor liveness in steady state, including:
 Switch identifier (switch id): a globally unique identifier for
each switch, e.g., the lowest MAC address of all local
ports.
 Pod number (pod): a number shared by all switches in the
same pod.
 Position (pos): a number assigned to each edge switch,
unique within each pod.
 Tree level (level): 0, 1, or 2 depending on whether the
switch is an edge, aggregation, or core switch.
 Up/down (dir): Up/down is a bit which indicates whether a
switch port is facing downward or upward in the multi-
rooted tree.
13
Distributed Location Discovery(Cont.)
14
Provably Loop Free Forwarding
 Once switches establish their local positions
using LDP, they employ updates from their
neighbors to populate their forwarding tables.
 Core switches learn the pod number of directly-
connected aggregation switches.
 Aggregation switches learn the position number
of all directly connected edge switches.
 For aggregation switches, if the destination is in
the same pod, then forward it according to the
position entry in PMAC; if the dest is not in the
same pod, then should forward it to the core
layer.
15
Fault Tolerant Routing
16
Fault Tolerant Routing (Cont.)
17
Discussion
18
Implementation
 Testbed consists of 20 4-port NetFPGA PCI card
switches. The switches run OpenFlow v0.8.9r2,
which provides the means to control switch
forwarding tables.
19
Evaluation
 For UDP flow, at least one of the failures falls on
the default path between sender and receiver.
20
Evaluation (Cont.)
 Convergence for TCP flows takes longer than the
baseline for UDP because TCP loses an en-tire
window worth of data. TCP's RTOmin set to
200ms in our system.
21
Evaluation (Cont.)
 After 110ms, connectivity is restored. Individual
switches detect the failures and notify the fabric
manager, which in turn reconfigures appropriate
switch forwarding tables.
22
Scalability
23
VM Migration
24
Conclusions
 The goal of this work is to explore the extent to
which entire data center networks may be treated
as a single plug-and-play fabric.
 PortLand, a set of Ethernet-compatible routing,
forwarding, and address resolution protocols
specifically tailored for data center deployments.
It makes data center networks can become more
flexible, efficient, and fault tolerant.
25

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PortLand.pptx

  • 1. Radhika Niranjan Mysore, Andreas Pamboris, Nathan Farrington, Nelson Huang, Pardis Miri, Sivasankar Radhakrishnan, Vikram Subramanya, and Amin Vahdat Department of Computer Science and Engineering University of California San Diego PortLand: A Scalable Fault-Tolerant Layer 2 Data Center Network Fabric 1
  • 2. Abstract  A scalable, easily manageable, fault-tolerant, and efficient data center network fabric.  Existing layer 2 and layer 3 network protocols face limitations in: lack of scalability, difficult management, inflexible communication, or limited support for virtual machine migration.  PortLand, a scalable, fault tolerant layer 2 routing and forwarding protocol for data center environments. 2
  • 3. Introduction  Increasing trend toward migrating applications, computation and storage into data centers.  Current network protocols impose significant management overhead at this scale.  Ideally, data center network architects and administrators would have “plug-and-play” deployment for switches. 3
  • 4. Future Scenario  R1. Any VM may migrate to any physical machine.  R2. An administrator should not need to configure any switch before deployment.  R3. Any end host should be able to efficiently communicate with any other end host in the data center along any of the available physical communication paths.  R4. There should be no forwarding loops.  R5. Failures will be common at scale, so failure detection should be rapid and efficient. 4
  • 5. Background  Data center network 1. Topology: hierarchical network tree 2. Forwarding: Layer 3 forwarding will impose administrative burden. Layer 2 forwarding does not scale to networks with tens of thousands of hosts. And STP would limit performance. Layer 2.5 VLAN forwarding limits flexibility for dynamically changing communication patterns. 3. End Host Virtualization To migrate a VM from one physical machine to another, layer 2 and Layer 3 both have some 5
  • 6. Fat Tree Networks In general, a three-stage fat tree built from k-port switches can support non-blocking communication among k³/4 end hosts using 5k²/4 individual k-port switches. We split the fat tree into three layers, labeled edge, aggregation and core as in Figure 1. The fat tree as a whole is split into k individual pods, with each pod supporting non-blocking operation among k²/4 hosts. 6
  • 7. Design  The goal of PortLand is to deliver scalable layer 2 routing, forwarding, and addressing for data center network environments.  The baseline multi-rooted network topology is known and relatively fixed. (Fat Tree)  Building and maintaining data centers with tens of thousands of compute elements requires modularity, advance planning, and minimal human interaction. When expansion does occur to the network, it typically involves adding more leaves. 7
  • 8. Fabric Manager  PortLand employs a logically centralized fabric manager that maintains soft state about network configuration information such as topology.  In PortLand, we restrict the amount of centralized knowledge and limit it to soft state. In this manner, we eliminate the need for any administrator configuration of the fabric manager (e.g., number of switches, their location, their identifier). 8
  • 9. Positional Pseudo MAC Addresses  PMAC : encodes the location of an end host in the topology.  The end hosts remain unmodified actual MAC (AMAC) addresses.  Hosts performing ARP requests receive the PMAC of the destination host.  All packet forwarding proceeds based on PMAC addresses.  Egress switches perform PMAC to AMAC header rewriting to maintain unmodified MAC at the destination host.  pod:position:port:vmid pod (16 bits): the pod number of the edge switch position (8 bits): its position in the pod port (8 bits): the switch-local view of the port number the host is connected to. vmid (16 bits): multiplex multiple virtual machines on the same physical machine 9
  • 11. PMAC(Cont.)  When an ingress switch sees a source MAC address never observed before, the packet is vectored to the switch software.  The software creates an entry in a local PMAC table mapping the host's AMAC and IP address to its PMAC.  The switch constructs the PMAC as described above and communicates this mapping to the fabric manager.  The fabric manager uses this state to respond to ARP requests. The switch also creates the appropriate flow table entry to rewrite the PMAC destination address to the AMAC for any traffic destined to the host.  Implemented by OpenFlow 11
  • 12. Proxy-based ARP  We leverage the fabric manager to reduce broadcast overhead in the common case. Uses fabric manager to get the ARP mapping, if not get, fabric manager will broadcast. 12
  • 13. Distributed Location Discovery  In order to plug-and-play, we present a Location Discovery Protocol (LDP) to set switch position in the global topology.  PortLand switches periodically send a Location Discovery Message (LDM) out all of their ports both, to set their positions and to monitor liveness in steady state, including:  Switch identifier (switch id): a globally unique identifier for each switch, e.g., the lowest MAC address of all local ports.  Pod number (pod): a number shared by all switches in the same pod.  Position (pos): a number assigned to each edge switch, unique within each pod.  Tree level (level): 0, 1, or 2 depending on whether the switch is an edge, aggregation, or core switch.  Up/down (dir): Up/down is a bit which indicates whether a switch port is facing downward or upward in the multi- rooted tree. 13
  • 15. Provably Loop Free Forwarding  Once switches establish their local positions using LDP, they employ updates from their neighbors to populate their forwarding tables.  Core switches learn the pod number of directly- connected aggregation switches.  Aggregation switches learn the position number of all directly connected edge switches.  For aggregation switches, if the destination is in the same pod, then forward it according to the position entry in PMAC; if the dest is not in the same pod, then should forward it to the core layer. 15
  • 19. Implementation  Testbed consists of 20 4-port NetFPGA PCI card switches. The switches run OpenFlow v0.8.9r2, which provides the means to control switch forwarding tables. 19
  • 20. Evaluation  For UDP flow, at least one of the failures falls on the default path between sender and receiver. 20
  • 21. Evaluation (Cont.)  Convergence for TCP flows takes longer than the baseline for UDP because TCP loses an en-tire window worth of data. TCP's RTOmin set to 200ms in our system. 21
  • 22. Evaluation (Cont.)  After 110ms, connectivity is restored. Individual switches detect the failures and notify the fabric manager, which in turn reconfigures appropriate switch forwarding tables. 22
  • 25. Conclusions  The goal of this work is to explore the extent to which entire data center networks may be treated as a single plug-and-play fabric.  PortLand, a set of Ethernet-compatible routing, forwarding, and address resolution protocols specifically tailored for data center deployments. It makes data center networks can become more flexible, efficient, and fault tolerant. 25