Efficient policies for carrying traffic over flow switched networks
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Efficient Policies for Carrying Traffic Over Flow-Switched Networks. Anja Feldmann, Jenifer Rexford, and Ramon Caceres Presenters: Tauhid, Reji and Murshed. Objective. Increase the efficiency of the switching technique

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Efficient Policies for Carrying Traffic Over Flow-Switched Networks

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Efficient policies for carrying traffic over flow switched networks

Efficient Policies for Carrying Traffic Over Flow-Switched Networks

Anja Feldmann, Jenifer Rexford, and Ramon Caceres

Presenters: Tauhid, Reji and Murshed

Advanced Computer Networks


Objective

Objective

  • Increase the efficiency of the switching technique

  • Reduce the overhead for establishing and maintaining the dedicated route or shortcut for flow

Advanced Computer Networks


Introduction

Introduction

    A possible solution could be grouping series of related data packets into flows and sending the flows through a shortcut path

Benefits: improve performance and capitalizing on QoS of the switches

Drawbacks: consume network resources to create and maintain dedicated path for the flow

Different definition and criteria are necessary for flow construction and shortcut creation and maintenance

Advanced Computer Networks


Introduction contd

Introduction(Contd.)

Three parameters determine the flow and

shortcut decisions:

  • aggregation: level for traffic combination

  • timeout: time interval of any flow

  • trigger: traffic quantity or number of packets for constituting a flow

Advanced Computer Networks


Introduction contd1

Introduction(Contd.)

The effects of varying these parameters were

explored on three metrics of interest:

  • percentage of traffic following the shortcut

  • shortcut setup rate

  • number of simultaneous shortcut

Advanced Computer Networks


Trace collection of packets

Trace Collection of Packets

The Extensive packet-level trace collection was carried out on T1 line of AT&T Research Lab. Several aspects were considered as:

-the traffic trace reflects the dominance of WWW

-long continuous traffic traces were observed

-the endpoint machines were taken for consideration

-all the flow and shortcut parameters were evaluated

on various parameters

Advanced Computer Networks


Trace collection of packets contd

Trace Collection of Packets (Contd.)

The T1 line connects the AT&T Lab to the external

internet. The Ethernet segment carries all traffic to and

from the T1 line at a speed of 10-Mbits/s

The Sniffer was equipped with tcdump to collect information of 100 00 packets in raw binary format.

Advanced Computer Networks


Trace collection of packets contd1

Trace Collection of Packets (Contd.)

  • Tcdump read each packet and generated an ASCII log

  • Perl script classified each packet into flows

  • Splus function processed all the log files on different performance metrics

Advanced Computer Networks


Trace collection of packets contd2

Trace Collection of Packets (Contd.)

From the optional field of the web request messages, the operating system of the client machine was identified. Linux and/or Windows systems were classified as personal computers

IP address associated with multiple types of machines such as Windows and SunOS are classifies as Proxy Servers

Advanced Computer Networks


Hourly average throughput of the ethernet segment

Hourly average throughput of theEthernet segment

Advanced Computer Networks


The packet size distribution of the network traffic

The packet size distribution of the network traffic

Advanced Computer Networks


Trace collection of packets contd3

Trace Collection of Packets (Contd.)

  • Half of the outgoing traffic consists of 40

    bytes TCP acknowledgement packets, so the

    average packet size became 123 bytes

  • More than 60% of the incoming packets have

    552, 567, or 1500 bytes, that correspond to

    common maximum transfer unit size on the

    Internet

  • Using tcpreduce tool, the FTP, HTTP,

    SMTP, DNS, etc. data transfer were measured  

Advanced Computer Networks


Flow size distributions

Flow Size Distributions

  • Mixture of flows between 100 and 100,000 bytes

  • Majority of flows within range of 50 to 1000 bytes

  • 1/3 of flows between 1000 – 10,000 bytes. 1/3 between 100 – 1000 bytes

Advanced Computer Networks


Cumulative distribution

Cumulative Distribution

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Derivative of cumulative distribution

Derivative of Cumulative Distribution

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Density of the logarithm of the flow sizes

Density of the logarithm of the flow sizes

Advanced Computer Networks


Flow sizes of web traffic

Flow sizes of Web Traffic

  • SMTP (email) – large concentration of 1000 byte flows, remaining flows around 3000 bytes

  • Telnet – Bytes per flow is typically less than 100 bytes

  • HTTP has the largest bytes per flow. Flows fall into 3 main categories

    • 1. Less than 150 bytes, from failed TCP sessions and error messages.

    • 2. 150 – 300 bytes, from cache hit messages.

    • 3. Greater than 300 bytes, actual web page transfers.

Advanced Computer Networks


Flow sizes of traffic

Flow sizes of Traffic

Advanced Computer Networks


Flow duration of web traffic

Flow duration of Web Traffic

  • Duration of SMTP traffic falls between 0.01 seconds and 100 seconds, with high concentration between .01 and 1 second

  • Telnet flows typically have the longest duration. Data shows duration up to 17 minutes. Usually around 100 seconds

  • HTTP Flow duration typically around 1 second, but can last up to 100 seconds

Advanced Computer Networks


Flow duration of traffic

Flow duration of Traffic

Advanced Computer Networks


Http flows by machine type

HTTP Flows by Machine Type

  • End point machines have unique flow characteristics

  • Flow duration for modem connection is longer

  • Traffic to proxy servers tend to be a mixture of shorter and longer flows

  • Larger transfers have higher throughputs since TCP window grows

Advanced Computer Networks


Flow duration for different machines

Flow duration for different machines

Advanced Computer Networks


Combining multiple web responses

Combining Multiple Web Responses

  • 3 different levels of end-point aggregation

    • Port-to-port: Combines packets with the same IP address and port numbers at both end-points.

    • Host-level: Combines different TCP session from the same Web server to the same Web client.

    • Net-to-Net: Aggregating hosts that share the first 16 bits of the IP address.

Advanced Computer Networks


Flow sizes for web responses

Flow sizes for web responses

Advanced Computer Networks


Flow sizes for web responses1

Flow sizes for web responses

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Proportion of shortcut traffic

Proportion of Shortcut Traffic

  • With a trigger of 10 – 20 packets, network can avoid establishing shortcuts for short-lived flows.

  • X-packet trigger less effective for host-to-host using packet trigger since aggregation increases number of packets thus triggering too early

Advanced Computer Networks


Percent of shortcut traffic port to port

Percent of shortcut traffic (port-to-port)

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Percent of shortcut traffic host to host

Percent of shortcut traffic (host-to-host)

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Shortcut setup rate

Shortcut Setup Rate

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Shortcut setup rate contd

Shortcut Setup Rate (Contd.)

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Shortcut setup rate contd1

Shortcut Setup Rate (Contd.)

  • Setup rate is lower for larger packet size

  • Setup rate is lower for higher timeout

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Simultaneous shortcut connections

Simultaneous Shortcut Connections

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Simultaneous shortcut connections contd

Simultaneous Shortcut Connections (Contd.)

  • 0-packet trigger 75.8 shortcuts in average

  • 10-packet trigger reduces the average no of simultaneous shortcuts by a factor of 3.3 (75.8 to 23.6)

    • Reason: higher packet trigger causes less shortcut connections

  • For stable operation during heavy load, coarser aggregation and larger triggers may be necessary

Advanced Computer Networks


Simultaneous shortcut connections contd1

Simultaneous Shortcut Connections(Contd.)

Advanced Computer Networks


Simultaneous shortcut connections contd2

Simultaneous Shortcut Connections(Contd.)

  • 12 sec timeout causes 4.3 shortcuts

  • 300 sec timeout causes 44.5 shortcuts

  • Larger timeout increases no of shortcuts, as a result it reduces signaling load

  • Establishment of shortcuts is limited by no of connections, or the signaling capacity of the switch, or both

  • Substantial network overhead reduction is possible by timeouts, triggers, end-point aggregation

Advanced Computer Networks


Traffic flows along partial routes

Traffic Flows Along Partial Routes

  • As the hop count increases, the numbers increases exponentially. ( EX: first seven hops have 26, 71, 137, 267, 409, 916, 1508 different outcomes, respectively.)

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Partial route aggregation

Partial Route Aggregation

Advanced Computer Networks


Partial route aggregation contd

Partial Route Aggregation (Contd.)

  • Aggregating traffic along a portion of the routes decreases both the setup rate and the number of simultaneous connection

    • Seven hop: Setup rate = 20%,No. of Shortcuts = 11%

    • Three hop: Setup rate = 37%,No of Shortcuts = 16%

  • Percent of Byte in Shortcuts

    • End-to-End:92.2%

    • Seven hop:94.0%

    • Three hop:96.0%

Advanced Computer Networks


Partial route aggregation contd1

Partial Route Aggregation (Contd.)

  • Partial-route aggregation reduces network overheads while increasing the proportion of shortcut traffic

  • Partial-route aggregation combines transforms from replicas of the same web site, as well as related servers at the same institution

  • Partial route flows benefit more from larger timeout values

    • As seen in Table III for 60 sec and 300 sec.

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Summary

Summary

  • Flow characteristics vary with endpoint type (modem, personal computer, compute servers, proxy servers)

  • Aggregating consecutive and concurrent transfers from the same web server yields substantial benefits

Advanced Computer Networks


Summary contd

Summary (Contd.)

  • Aggregation and triggers both reduce overhead, but the reductions are not multiplicative

  • Variability in traffic load changes with time scale

  • Aggregating traffic along portions of the route between the source and destination yields additional reduction in network overhead

Advanced Computer Networks


Future work

Future Work

  • To evaluate specific new policies that balance the short-term tradeoffs between processor and network load

  • To investigate the policy and performance implications of combining traffic along a portion of the route

  • To study more detailed breakdown of web traffic by content type, as well as the implications of push technology and the new features in the emerging HTTP standards

Advanced Computer Networks


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