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An Approach to Flexible QoS Routing Active Networks. Proceedings of the Fourth International Workshop on Active Middleware Services(AMS’02) 謝志峰 2002/11/14. Outline. Introduction QoS Support in Active Networks AQR (Active QoS Routing) operation Simulation of AQR Conclusions.

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An approach to flexible qos routing active networks

An Approach to Flexible QoS Routing Active Networks

Proceedings of the Fourth International Workshop on Active Middleware Services(AMS’02)



  • Introduction

  • QoS Support in Active Networks

  • AQR (Active QoS Routing) operation

  • Simulation of AQR

  • Conclusions

Introduction 1 2

  • Active Network(AN) are investigated since several years, attempting to satisfy the increasing needs of highly customizable protocol mechanisms.

  • AQR:The paper combines the concept of AN with suitable QoS routing mechanisms to form a novel approach called “Active QoS Routing(AQR)”.

Introduction 2 2

  • Three major concepts and terms in the context of AN will be referred to frequently in the remainder:

    • Active Applications(AA): It denote user-provided communicating applications which make use of AN

    • Execution Environment(EE):The runtime system available on an AN node is coined as EE

    • NodeOS:The abstract machine on which all developer of customizations for an AN can rely is called NodeOS

Qos support in active networks
QoS Support in Active Networks

  • Mechanisms which are usually associated with layers 3 or 4 : We find Active Congestion Control, which reduces the feedback delay for congestion control mechanisms by moving endpoint algorithms into the network.

  • Mechanisms which transfer application layer functionality into the network : Intelligent dropping of packets that correspond to specific frames of a video stream.

Aqr active qos routing operation 1 3
AQR (Active QoS Routing) operation (1/3)

  • 1.The AQR sender calculates all non-

    cyclic paths to the destination form the

    link state routing table.

  • 2. A probing packet carrying the QoS

    requirements, code for QoS calculation, the

    sender and receiver’s addresses and a list of

    visited nodes is sent to each first hop of these


Aqr operation 2 3
AQR operation (2/3)

  • 3. Upon receiving an AQR probing packet, an AQR-compliant transit node executes the AA code,which

    • Check if the minimum QoS requirements found in the packet can be met ,

    • Compares and updates the QoS data,

    • Adds itself to the list of already visited nodes, and

    • executes the code of the AQR sender, starting at step2 ---- except that no probing packets are sent to the source or to any other already visited node.

AQR operation (3/3)

  • 4. Only packets which conform to the minimum

    QoS requirements reach the AQR receiver,

    where a list of valid paths is generated. After

    a predefined period, the best path is chosen

    and communicated to the sender

Simulation of AQR(1/10)

  • We performed two series of simulations with the “ns” network simulator.

  • In all of our simulators, the nominal bandwidth of all links was 1.5Mbit/s, packet sizes of all packets including measurement packets were 500 bytes.

  • Delay between probing packet ”waves” was set to approximately 2 RTTs , and we generally used a simulation time of 360 seconds.

Simulation of AQR (2/10)

  • The goal of Figure 1 was to study the behaviour of delay based AQR in a somewhat realistic scenario.

  • The sender was at node 9, the receiver was at node 45.

Simulation of AQR (3/10)

  • One such result is depicted in fig.2 .

  • We chose this scenario because it shows a significant delay reduction(approx. 20%) despite a number of path changes.

Shortest Path


Simulation of AQR (4/10)

  • We chose to use a somewhat less realistic but more controllable scenario by mean of a 15-node topology, which is shown in fig.3.

  • Using node 5 as a sender and node 13 as a receiver.

  • We studied the behaviour of AQR both with (greedy) TCP background traffic and exponentially distrially UDP background traffic.

Simulation of AQR (5/10)

  • Figure 4 shows the delay of a constant bit rate AQR stream with TCP background traffic.

  • AQR based on bandwidth measurements alone not only increases the average delay but also jitter.


Shortest Path


Simulation of AQR (6/10)

  • In table 1(TCP background traffic) delay increased by approx. 9% in comparison with shortest path routing, jitter increased by 44%.

  • In table 2(UDP background traffic) The throughput increased by 27% in comparison with shortest path routing.The average delay increased by 8% and jitter increased by 87%.

Simulation of AQR (7/10)

Shortest Path

  • We now focus on a mixture (called”AQR-new”) of both parameters, where a delay threshold limits the choice of paths.

  • “AQR-old” denotes AQR solely relying on delay.




Simulation of AQR (8/10)

  • There was no other drastic change in the delay or throughput results (see table 3) ; as could be expected, the average delay was notably 15%smaller than the average delay of shortest path routing (TCP background traffic).

Simulation of AQR (10/10)

  • Unresponsive background traffic yields a different result, which is depicted in figure 7. (UDP background traffic)

Shortest Path


Simulation of AQR

  • The main advantage of AQR-new with unresponsive background traffic lies in a throughput enhancement which was as high as 33% in our simulations.

  • This enhancement is due to a smaller packet loss ratio. The average delay was reduced by 36%.


  • We have proposed AQR as an approach to combing Active Networks with QoS routing.

  • In the variant finally proposed, AQR combines a consideration of both bandwidth and delay for finding optimal paths.

  • This variant showed considerable improvements over shortest-path routing under various load combinations and characteristics.

Future and related work

  • We can research related topic with Active Network.

  • We can plan to consider multi-domain routing.

  • We can research different topic with AQR.