link capacity estimation in wireless software defined networks

Link Capacity Estimationin Wireless Software Defined Networks

Farzaneh Pakzad, Marius Portmann, and Jared Hayward

School of ITEE, The University of QueenslandBrisbane, Australia

Presented by Farzaneh Pakzad25th International Telecommunication Networks and Applications ConferenceNovember 18-20, 2015, UNSW, Sydney, Australia

1

Overview• Background

• Motivation

• Bandwidth & Capacity Estimation in Traditional Networks

• Packet Pair/Train Probing

• Packet Pair/Train Probing in SDN

• Experiments

• Conclusion

2

Data

planeSimple Packet

Forwarding Hardware

Simple Packet Forwarding Hardware




3

Network Operating System (Control layer)

Control Programs (application layer ) SDN Controller

Background: Logical View of Software Defined Networking (SDN) Architecture

Data Plane






4

Packet-In Packet-Out

Network Operating System (Control layer)

Control Programs (application layer ) SDN Controller

Background: Logical View of Software Defined Networking (SDN) Architecture

The Promise of SDN

5

Improving

Network

Efficiency

Higher rate of innovation

Better Flow

Management

Easier Network Management

Lowering Costs

Programmable Networks

Background (contd.)Wireless Mesh Networks (WMNs)

6

Wireless Routers

Gateways

Mesh Clients

Node Types

Wireless Mesh Networks Challenges and Opportunities, Mihail L. Sichitiu, Electrical and Computer Eng. Dept., NC State University, Raleigh, NC, USA

Public Safety

Transportation

Mining

Enterprise Network

Emergency Response

Applications

Potential of using SDN for WMNs

7

Optimal Routing GOAL :

Global view

and centralised

control

Fine grained flow routing

Limitations with WMNs: Lack of global view and centralised control Routing is very coarse grainedResult in a limited performance

Network Topology Links Capacity

Available Bandwidth vs Link Capacity

• Link Capacity The maximum possible bandwidth of a link

• Available Bandwidth

The maximum unused bandwidth

9

Bandwidth and Capacity Estimation in Traditional Networks (active)

• Variable Packet Size probing (VPS) [1], [2] capacity of individual hops

• Self-Loading Periodic Streams (SLoPS) and Trains of Packet Pairs (TOPP) [4], [5]

end-to-end available bandwidth

• Packet Pair/Train Dispersion probing (PPTD)[3] end-to-end capacity of the path

Estimates

Estimate

Estimates

10

Packet Pair/Train Probing(Basic Idea)

Sender Receiver

Packet 1

Packet 2

Packet 1Packet 2

Packet 2 Packet 1

Back-to-Back

Packet size: Link Capacity: Time Dispersion:

LC

C

L

11

Packet Pair Probing in SDN

12

• Goal

The implementation of Link capacity estimation mechanism on any Standard OpenFlow SDN controller

• Approach

SDN controller initiate sending of packet pair/train across a link

Packet Pair Probing in SDN

SDNController C

Switch S2Switch S1Port 2

Port 1

13

Port 1

Port2

P1P2

Probing Packets

Packet-outP

Packet-InP1Packet-In

P2

H1 H2

12 tt 1t2t

LC

d

Set the “EtherType” of the Probe packet to unused value

Implementation/Experiments

• Methodology

– Considered simple topology described

–Mininet: Linux based network emulator

–Ns3: Emulate wireless links

– Iperf: Measure wireless link capacity (as a reference)14

• Ryu as our SDN controller platform

C

S2S1

Link Capacity Estimation using Packet Pair Probing

15Switch

Link Capacity Estimation using Packet Train Probing40TLengthTrainPacket

16

Estimation Root mean Square Error(RMSE) and Overhead as a Function of Train Length (T)

17

Impact of Cross Traffic

• Cross traffic cause underestimation of the link capacity

• Two Type of Cross Traffic

– Forward Cross Traffic Same Direction as the Probe Packets

– Reverse Cross Traffic Reverse Direction of the Probe Packets

18

C

S2S1

C

S2S1

Impact of Cross Traffic

19

Distance d=0 Train Length T = 40C

S2S1

C

S2S1

PF PPPPFF

Forward Cross Traffic Packet Train

PP RPPRRP

probe packets are interleaved with Reverse Cross Traffic

Compensate for the Impact of Reverse Cross Traffic

• Controller query the port statistics from Switches , i.e. received packet count at port 2 of switch S1

20

C

S2S1Port 2

PPPPP RRRRR RP P

)()1()(

TLRTTC

R = the number of interleaved reverse cross traffic between the first and last packet of the train

Compensate for the Impact of Reverse Cross Traffic

21

Distance d=0 Train Length T = 40

Conclusions

22

Implemented a Prototype using Ryu SDN controller

Good choice of Train length T

Compensate the impact of cross traffic

Future work

Evaluating this approach on a real wireless SDN test bed

References

[1] S. M. Bellovin, “A best-case network performance model,” 1992.

[2] V. Jacobson, “Pathchar: A tool to infer characteristics of internet paths,” 1997.

[3] V. Jacobson, M. J. Karels, “Congestion avoidance and control,” in ACM SIGCOMM computer communication review, vol. 18, no. 4. ACM, 1988, pp. 314–329.

[4] M. Jain and C. Dovrolis, End-to-end available bandwidth: Measurement methodology, dynamics, and relation with TCP throughput. ACM, 2002, vol. 32, no. 4.

[5] B. Melander, M. Bj¨orkman, and P. Gunningberg, “A new end-to-end probing and analysis method for estimating bandwidth bottlenecks,” in Global Telecommunications Conference, 2000. GLOBECOM’00. IEEE, vol. 1. IEEE, 2000, pp. 415–420.

[6] J. Guerin, M. Portmann, K. Bialkowski, W. L. Tan, and S. Glass, “Lowcost wireless link capacity estimation,” in Wireless Pervasive Computing (ISWPC), 2010 5th IEEE International Symposium on. IEEE, 2010, pp. 343–348.

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