Multicast forwarding plane in future nws source routing has a competitive edge
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2010- 12 - 10 GLOBECOM FutureNet III. Multicast Forwarding Plane in Future NWs : Source Routing Has a Competitive Edge. Takeru Inoue Yohei Katayama Hiroshi Sato Takahiro Yamazaki Noriyuki Takahashi (NTT Labs., Japan). Gap between design and usage of Internet. Internet (TCP/IP)

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Multicast Forwarding Plane in Future NWs : Source Routing Has a Competitive Edge

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Multicast forwarding plane in future nws source routing has a competitive edge

2010-12-10 GLOBECOM FutureNetIII

Multicast Forwarding Plane in Future NWs: Source Routing Has a Competitive Edge

Takeru Inoue

Yohei Katayama

Hiroshi Sato

Takahiro Yamazaki

Noriyuki Takahashi (NTT Labs., Japan)

Takeru [email protected] Network Innovation Labs.


Gap between design and usage of internet

Gap between design and usage of Internet

  • Internet (TCP/IP)

    • Originally designed for 1:1 conversation model (60’s-70’s)

      • telnet, ftp, …

    • NOW: Mainly used for 1:N distribution model

      • Audio-video streaming, pub/sub services, file sharing, data-center, …

  • Efficient distribution model

    • Data is replicated at nodes and delivered to a group

      • Source and overall network overhead is decreased

    • Future NWs will support efficient distribution

      • In accordance with the usage

replication

Takeru [email protected] Network Innovation Labs.


Trend in multicast research

Trend in multicast research

  • History in multicast research

    • Twenty-year history

    • Main focus was group size, not group numbers

  • Recent trends

    • Supporting many groups (> 1T)

      • Increase in contents themselves and long-lived services

    • Dr. multicast [Vigfusson08] and MAD [Cho09]

      • Extend IP multicast for many groups

      • Handle only large groups and reduce forwarding state

    • FRM and LIPSIN [Ratnasamy06, Jokela09]

      • Based on source routing

      • Have no state limit, but suffer from small headers

    • No clear direction on multicast research for future networks

Takeru [email protected] Network Innovation Labs.


Our contribution and outline

Our contribution and outline

  • Our contribution

    • Most promising research direction in multicast

      • Focused on forwarding plane, because it directly affects quality and is designed before control plane

  • Outline

    • Taxonomy of multicast forwarding plane

      • Table-driven forwarding

      • Packet-driven forwarding(source routing)

        • Scalability improvement techniques: virtual ports, Bloom filters, and hierarchy

    • Assessment of multicast forwarding plane

      • Scalability on group number and group size

      • Forwarding performance

      • Control architecture

      • State management

Takeru [email protected] Network Innovation Labs.


External definition of multicast forwarding

External definition of multicast forwarding

  • Nodes independently determine their output ports

    • S = F(n, g)

      • S: set of output ports

      • F(n,g): function to determine S

        • n: node ID

        • g: group ID

    • Forwarding state maintained by overall network

Packet of Group1

p1

p2

p3

To Ports 2 and 3

Takeru [email protected] Network Innovation Labs.


Taxonomy

Taxonomy

g1

Forwarding state

g1: p2 p3

:

  • Table-driven forwarding

    • Nodes maintain columns (forwarding tables) and

      search them by group ID in packet

    • Max group # is limited by table size

    • e.g. IP multicast

  • Packet-driven forwarding

    • Source puts row on packet header

    • Nodes finds ports

    • No limit on group #, but group size is limited by header

    • Kind of source routing (nodes are stateless)

p1

p2

p3

Packet

n1:p2 n1:p3 …

p1

p2

p3

Table-driven forwarding

Packet-driven

forwarding

Takeru [email protected] Network Innovation Labs.


Review of scalability improvement techniques virtual ports

Review of scalability improvement techniques:Virtual ports

  • Virtual ports [Tian98, Jokela09]

    • Set of physical ports

      • Fork (ports on single node, e.g. vp1 in Fig)

      • Tunnel (ports on different nodes, e.g. vp2 in Fig)

    • Reduce forwarding state (tables or headers)

    • Nodes maintain mapping

      • Much smaller than forwarding table

vp1 …

Mapping of virtual ports

vp1: p2 p3

:

p1

p2

p3

vp1

vp2

Packet-driven forwarding

Takeru [email protected] Network Innovation Labs.


Review of scalability improvement techniques bloom filters

Review of scalability improvement techniques:Bloom filters

  • Bloom filters

    • Probabilistic data structure for set

    • Has great space efficiency at risk of false positive

      • e.g. 10 bits per element with 1 % error

    • Can be checked in constant time

  • Table-driven forwarding

    • Bloom filter is assigned to each port and

      has groups of ports [Gronvall02]

  • Packet-driven forwarding

    • Headers are replaced by Bloom filters

      [Ratnasamy06]

Bloom filters

g1

p1: …

p2: g1 …

p3: g1 …

p1

p2

p3

Table-driven forwarding

Bloom filter in packet

n1:p2 n1:p3 …

p1

p2

p3

Packet-driven forwarding

Takeru [email protected] Network Innovation Labs.


Review of scalability improvement techniques hierarchy

Review of scalability improvement techniques:Hierarchy

  • Table-driven forwarding

    • No improvement

      • Inter-domain nodes maintain same # of groups

  • Packet-driven forwarding [Zahemszky09]

    • Headers are replaced on domain border

      • Group size is greatly increased

    • Overhead on border can be distributed

g1

n1:p2 n1:p3 …

Headers table

g1: n2:p1 …

:

Domain border

g1

n2:p1 …

Packet-driven forwarding

Takeru [email protected] Network Innovation Labs.


Outline of assessment

Outline of assessment

  • Multicast forwarding plane

    • Table-driven forwarding

      • Group # is limited by forwarding table size

      • Improved by virtual ports and Bloom filters

    • Packet-driven forwarding

      • Group size is limited by packet header size

      • Improved by virtual ports, Bloom filters, and hierarchy

  • Assessment

    • Scalability with regard to group number and group size

    • Forwarding performance

    • Control architecture

    • State management

Takeru [email protected] Network Innovation Labs.


Scalability on group number and size

Scalability on group number and size

  • Target

    • Group # is > 1 T

    • Group size is < 1 M

      • Few large groups (Zipf distribution)

      • # of all nodes on delivery path

Takeru [email protected] Network Innovation Labs.


Scalability on group number and size1

Scalability on group number and size

Forwarding table: 18 Mbits

Packet header: 800 bits

  • Target

    • Group # is > 1T

    • Group size is < 1M

  • Table-driven forwarding

    • Group # is limited by table

    • Far less than 1T groups

      • 1M with Bloom filters

      • More groups can be supported in overall network, but gap is too large

  • Packet-driven forwarding

    • Group size is limited by header

    • Group # of nearly 1M is supported

      • 0.4M with all means

# of groups at node (log-scale)

Target

1T

1.8M

6-order

Bloom

93.8K

Group size (log-scale)

410K

640

Virtual ports

and Bloom

Hierarchy

6

1M

Takeru [email protected] Network Innovation Labs.


Forwarding performance

Forwarding performance

  • Table-driven forwarding

    • Performed in constant time by CAM

      other than with virtual ports

      • Repeated table lookup needed

  • Packet-driven forwarding

    • Performed in constant time

      with virtual ports and Bloom filters

      • Each physical port has TCAM

        • TCAM has virtual ports of the physical port

      • Bloom filter in packet is checked by all TCAMs in parallel

      • Packet is copied to all matched ports

Multiple elements in TCAM are checked against Bloom filter at once

Set of virtual ports

in Bloom filter

TCAMs

vp1 …

p1: …

p2: vp1 …

p3: vp1 …

p1

p2

p3

vp1

Packet-driven forwarding

Takeru [email protected] Network Innovation Labs.


Control architecture

Control architecture

  • Table-driven forwarding

    • Follows distributed route computation

      • Joins are routed to a source and populate each hop with forwarding entries

    • Distributed computation complicates assurance of stable operation

  • Packet-driven forwarding

    • Follows central route computation

      • Source calculates delivery path and puts it in packet

    • Simple and stable

      • Doesn’t impose heavy load on sources, because each source calculates a few trees rooted at themselves

      • Port list (used to calculate delivery trees) is equivalent to OSPF link state or BGP AS path

Takeru [email protected] Network Innovation Labs.


State management

State management

  • Successful NW protocols

    • NW state is updated by trusted entities, because state failures can affect entire NW

  • Protocols not widely deployed

    • NW state is updated by users

      • e.g. IP multicast, MobileIP, and IntServ

  • Table-driven forwarding

    • Relies on joins by users

    • Violates requirements of successful protocols

  • Packet-driven forwarding

    • State (packet header) is created by source (trusted entity)

    • Meets requirements of successful protocols

Takeru [email protected] Network Innovation Labs.


Conclusions

Conclusions

  • Taxonomy of multicast forwarding plane

    • Table-driven forwarding

    • Packet-driven forwarding (source routing)

  • Assessment of multicast forwarding plane

  • Future work

    • Quantitative analysis, control planes, and implementation issues

Takeru [email protected] Network Innovation Labs.


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