Results

Figure 6.7: Impact of the unicast conversion threshold on the relative flow entry consumption (adapted from [Ble+15b]).

The investigated ASDM prototype is implemented using the Ryu�controller using OpenFlow version 1.3. The Mininet network emulator version 2.0 executes the experi-ments using on Open vSwitch to emulate SDN switches running on the Ubuntu 14.04 Linux operating system. The whole emulation is conducted in a VM with four CPU cores and 6GB memory on a server with an Intel Xeon E5-1410 processor.

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used in the network, not significant. This topology-independence is a significant result because it shows that the adaptation of the flow entry consumption is expected to not depend significantly on the topology, which makes its use easier for different network topologies.

The tradeoffbetween the state consumption and the data rate is essential to understand the impact of changing the unicast conversion threshold on data path resources. The connection between the data rate and the state consumption for different unicast conversion threshold values, termed data-rate-state profile, is depicted in Figure6.8.

Please note that the horizontal axis starts at 35% of the unicast data rate. While we found before that the flow entry consumption is independent of the investigated topologies, the data rate differs significantly between them. Not surprisingly, the tree topology gains the most from late replication strategies, e.g., when using . The impact of using multicast in the core network is visible but smaller. For unicast conversion thresholds larger than seven, the differences between the topologies diminish. The behavior is not surprising because, with larger thresholds, the depths of the topologies, and the group sizes both become small relative to the unicast conversion threshold. Therefore, the unicast conversion moves closer to the ingress switch, which reduces the impact of the topologies on the replication process.

Figure 6.8: The data-rate-state profiles of the investigated topologies (adapted from [Ble+15b]).

Figure6.9gives a view on the adaptation choice as well as the data rate and state tradeoffin the ISP topology. Changing the threshold allows the control plane application and its operators to select a point close to the approximated profile lines. For example, when moving from to , the consumption of flow entries is reduced from

Figure 6.9: A detailed view on the tradeoffbetween data rate and state in the ISP topology (adapted from [Ble+15b])

about 49% to 36% compared to the late duplication strategy. At the same time, the relative data rate increases from 48% to 53%.

A switch from to increases the multicast traffic significantly, from 41%

unicast data rate to 70% unicast data rate, or a 70% increase in data rate. Depending on the total data rate managed by the ASDM system, this might have a significant impact on the traffic engineering in the network. Multicast traffic is expected to be UDP-based, constant rate and well controllable. Hence, the typical burstiness and self-similarity patterns caused by per-connection feedback loops like those used by TCP [Wil+97] are not expected. Its constant bit-rate nature is expected to affect bursty traffic if queueing occurs. We, therefore, conclude that measuring the data rate of the multicast traffic in the ASDM is crucial. Furthermore, modifying the unicast conversion threshold should be done incrementally.

The results discussed before provide a clear understanding of the effect of the unicast conversion threshold on both, the data rate, and the state consumption from a global perspective. While the global perspective is important, and the system can mitigate local resource bottlenecks by skipping a specific data plane element, it is nevertheless important to understand the effects of the system on the resource consumption of individual data plane elements. To that end, Figure6.10provides an insight into the effect of the unicast conversion threshold on the peak state consumption on a single data plane element per area. The bars in the figure provide the absolute flow entry consumption per group member as denoted by the left vertical axis. The lines provide the

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Figure 6.10: The peak state consumption on single data plane elements per network area (adapted from [Ble+15b])

relative flow entry consumption relative to its maximum. Their vertical axis is denoted on the right side of the Figure. In both, the tree, and the ISP topology the flow entry consumption per group member is higher in the core area of the network than in the edge area. This is expected because, in the tree topology, all flow entries are placed on the same devices due to the lack of alternatives.

The peak flow entries consumption in the core area is higher at most values of the unicast conversion threshold. The values where the peak consumption in the core area consumes is smaller than in the edge area are 32, 64, and 128. These values are larger than most group sizes in the investigated group size distribution. With these values, virtually all groups are immediately converted to unicast traffic. Hence, they are considered an edge case when the unicast conversion threshold is as high as or higher than the group sizes. The impact of the unicast conversion threshold on the peak flow entry consumption per group member in each area is significant for both areas up to a value

of 8. After that, it stays flat for theedgearea and continues to shrink for thecorearea. We explain this effect with the same mechanism that reduces the flow entry consumption to zero in the core area for large unicast conversion thresholds: the larger the threshold becomes in comparison to the group sizes, the more likely it becomes that each group only uses a single flow entry. This single flow entry is located on the ingress switch of the group, which is always an edge device in our design. Therefore, the flow entry consumption stays flat at theedgewhile shrinking to zero in thecorearea. We conclude that if the unicast conversion threshold is significantly smaller than the average group size, the flow entry reducing effect impacts the core and the edge area devices similarly.

A flow entry shortage in the core network can be mitigated by increasing the unicast conversion threshold to a value that is close to the largest group sizes.

As we discussed, the effect of the unicast conversion threshold is different depending on the size of a multicast group. We investigate flow entry consumption per group member in more detail on the example of a single, randomly created group that grows from 1 to 128 members in Figure 6.11. When the group sizes approach values of which the unicast conversion threshold is a multiple of, spikes are visible in the state consumption. This effect is very pronounced for small group sizes and diminishes when the group becomes larger. Furthermore, thetreetopology shows a higher variability than theISPtopologies. In all topologies, larger groups show less variability in their state consumption per group member. Small groups show more variability as well as a lower flow entry consumption efficiency.

For all topologies, the state efficiency increases with growing group sizes. The only exceptions in the depiction are theISP topologies, here the unicast conversion threshold shows an increasing trend from group size 80 to 128. We consider this a measurement artifact since all other configurations show increasing efficiency. Finally, the upper bound for the state efficiency is depicted by a unicast conversion threshold of . In this case, all groups, independent of their size are converted to unicast at the group ingress switch. However, for large groups, this threshold requires a considerable replication load on a single data plane element, which we do not consider feasible.

The investigation of the data-rate-state profile showed diminishing returns for investing state to reduce the data rate and vice versa. This observation could lead to the assumption that there is an optimal unicast conversion threshold for the given network and load configuration. We investigated this finding in Figure6.12by assuming that both, one unit of state, and one unit of data rate, have the same value for the network operator. While this assumption is not expected to hold for many use cases, it shows that the ASDM can not only be used to adapt a multicast system to a control path resource shortage, but also to optimize the outcome of the resources invested in the system. Depending on the scarceness of state and of network capacity in the system, the optimal unicast conversion threshold is expected to change, yet the fact that is can be derived is helpful for network operators.

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Figure 6.11: The influence of group sizes on the flow entry consumption for selected unicast conversion thresholds (adapted from [Ble+15b])

In Figure6.12on the horizontal axis, we see the flow entries consumed per group member, on the vertical axis the data rate reduction per flow entry. The depiction shows the data rate reduction return per invested flow entry. It is visible that the maximum return on invested flow entries is with unicast conversion threshold for all three topologies. The differences between the topologies are small. We, therefore, assume that

Figure 6.12: Selecting the unicast conversion threshold optimize the data rate reduction return on invested flow entries for a given cost function for data rate and state

(adapted from [Ble+15b])

the optimal value depends on the valuation of data rate and state as well as the group size distribution in the ASDM control plane application.