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

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)”.

 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 Introduction(2/2)

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.

 1.The AQR sender calculates all non- cyclic paths to the destination form the cyclic paths to the destination form the link state routing table. link state routing table.  2. A probing packet carrying the QoS requirements, code for QoS calculation, the requirements, code for QoS calculation, the sender and receiver’s addresses and a list of sender and receiver’s addresses and a list of visited nodes is sent to each first hop of these visited nodes is sent to each first hop of these paths. paths. AQR (Active QoS Routing) operation (1/3)

 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 step except that no probing packets are sent to the source or to any other already visited node. AQR operation (2/3)

 4. Only packets which conform to the minimum QoS requirements reach the AQR receiver, QoS requirements reach the AQR receiver, where a list of valid paths is generated. After where a list of valid paths is generated. After a predefined period, the best path is chosen a predefined period, the best path is chosen and communicated to the sender and communicated to the sender AQR operation (3/3)

 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(1/10)

 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 (2/10)

 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. Simulation of AQR (3/10)

 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 (4/10)

 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. Simulation of AQR (5/10)

 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 (6/10)

 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 (7/10)

 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 (8/10)

 Unresponsive background traffic yields a different result, which is depicted in figure 7. (UDP background traffic) Simulation of AQR (10/10)

 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%. Simulation of AQR

 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. Conclusions

 We can research related topic with Active Network.  We can plan to consider multi-domain routing.  We can research different topic with AQR. Future and related work