facebook
irp demo
Request Noction IRP Demo

Request a personalized demo/review session of our Intelligent Routing Platform

irp trial
Start Noction IRP Trial

Evaluate Noction IRP, and see how it meets your network optimization challenges

nfa demo
Noction Flow Analyzer Demo

Schedule a one-on-one demonstration of our network traffic analysis product

nfa trial
Free Noction Flow Analyzer Trial

Test drive NFA today with your own fully featured 30-day free trial

Tier 1 carrier performance report: July, 2017

The current report covers widely used Tier 1 carriers performance results in the US for the month of July 2017. Rare datapoints from distant locations have been omitted.

The presented analysis is based on more than 820 million successful probes that span the entire month. All data is aggregated per carrier on a daily basis and accounts for many thousands of successful probes. A control group (labeled C) is used as a base of comparison. The control group aggregates the average for all transit providers in a network, including Tier 1 carriers.

Average loss and latency

Fig. 1. Average Loss and Latency in July 2017
The numbers include a control group C (gray) to allow cross comparison.

The values for June 2017 are included for cross comparison.

low latency

Fig. 2. Average Loss and Latency in June 2017
The charts include a control group C (gray) to allow cross comparison.


Average packet loss analysis:

  • Distribution of average packet loss for the Tier 1 carriers in July is the same as in June. The leading positions were kept by NTT and Level 3, followed by Zayo and Centurylink;
  • When based on the control group level, higher average loss was shown for Telia and Hurricane.

Average latency analysis:

  • As in June, higher than average latency has been registered for: Hurricane, Cogent and GTT. Close to this group are Zayo, Xo and Telia, which show results positioned between the above mentioned tier one carriers and the control group level;
  • The best results in term of latency were obtained by Centurylink.
    Level 3 and NTT showed good results as well, positioned under the control group level;
  • A significant difference between results for the month of July compared to June was not registered. All Tier 1s showed roughly similar results to the previous month.

 

packet loss and latency in April 2017

Fig. 3. Better or worse Loss and Latency in July 2017
The numbers are differences from average control group.

worse latency

Fig. 4. Better or worse Loss and Latency in June 2017
The numbers are differences from average control group.


In comparison with the control group for the month of July, 2017:

  • NTT, Level 3, Centurylink and Zayo showed better results in terms of Loss;
  • Centurylink, NTT and Level 3 presented better results in terms of Latency.

In comparison with the data from June, 2017:

  • Centurylink migrated from the winner group into losers.Telia and Hurricane maintain the poorest results in terms of loss. Cogent remained in the losers group but showed continuous improvement in terms of loss as well.
  • Centurylink remains the best provider in terms of Latency, followed by Level 3 and NTT, meanwhile other Tier 1s are underperforming.
Loss

For the Loss analysis we use a scatter plot, where average values for the control group are assumed on the diagonal while the horizontal and the vertical axis highlight carrier metrics. All datapoints below the diagonal represent the better performing carriers and vice versa.

packet loss analysis

Fig. 5. Loss values spread on average diagonal
Datapoints comparison with diagonal.


Abnormally large losses are still registered for a large number of datapoints. As was mentioned in previous reports we consider excessive an average above 4.5% packet loss.
Given the fact that Tier 1 carriers are characterized by both low loss values for some networks and abnormally high losses for other networks, the conclusion is that high loss values are not caused by the carriers themselves but rather are caused by the networks they service or the networks they peer with. Whether the true cause is poor design, over-provisioned links or deficiencies in peering governance – this report cannot tell. What we can mention is that for many networks, whether permanently or sporadically, there is definitely an opportunity to improve things.

network loss

Fig. 6. Better or worse carrier loss (%)
Average placed on the zero line


A different representation of the above data places it around the control group (zero line) with gain values by carrier. Values are sorted and charted from left to right by increasing average loss. The chart depicts gains or worsening on a network based on the average control group’s performance – values are shown from left to right following better to worse loss values. The assumption of this analysis is that while a network’s conditions might be better or worse compared to other networks, the conditions tend to be equal across all carriers including the control group. While the carrier’s network is not the culprit causing additional loss, this analysis might be able to suggest whether those carriers peering with remote regions is deficient. Non-systemic issues with carriers will tend to cancel out with values being scattered equally above or below the zero line while systemic issues or gains will have a tendency to place a carrier consistently above or below it. The scatter plot highlights this assumption.
More so, if we average gains or losses compared with the control group we expect the noise to cancel out.

datapoint packet loss

Fig. 7. Average packet loss gains/losses by carrier July 2017
Averages determined for ALL datapoints or a cutoff at 4.5% control group applied.

average packet loss

Fig. 8. Average packet loss gains/losses by carrier June 2017
Averages determined for ALL datapoints or a cutoff at 4.5% control group applied.


A significant change in average Loss for the month of July, compared with June, has not been registered for most carriers. All Tier 1s showed roughly similar results to the previous month for averages determined for ALL datapoints and the cut off at the applied 4.5% control group. The only change has been registered for NTT which left the winners group.

The worst carrier in term of Loss for ALL datapoints is Hurricane. After the cut off at 4.5% control group level has been applied, Hurricane’s position visibly improved, presenting better result, however the carrier still remained in the group of losers.

As a result of the cut off at the applied 4.5% control group, NTT visibly improve its results. Zayo, contrariwise, left the group of the better performing carriers (Fig. 7).

Latency

For Latency analysis we use a similar scatter plot to the one we use for Loss. It displays control group values on the diagonal while highlighting individual carrier measurements on the horizontal and the vertical axis. Datapoints placed significantly and consistently below the average highlight better performing carriers while datapoints above the average highlight worse than average performance.

clusters datapoints

Fig. 9. Carrier latency with average group on the diagonal
Clusters of datapoints below diagonal highlight better performance


Based on data points presented in Fig.9 we can conclude the following:

  • NTT and Level 3 were present over the entire graph’s diagonal and have been showing latency levels higher than 200 ms;
  • Zayo, Cogent, GTT, XO, Telia, Hurricane and Centurylink have been mostly present within the latency diapazon of 85 – 180 ms.

average latency values

Fig. 10. Average latency gains/losses by carrier Values averaged for the difference between carrier performance and the average group in that network.


The differences in latency above from the control group are averaged with the expectation that better or worse performance will cancel out if the differences are caused by measurement noise.

The results show that during the month of July, 2017 in comparison with June, 2017:

  • All Tier 1s kept their positions in the corresponding categories: better or worst RTT reduction. The leading position in average RTT reduction was obtained by XO, which reduced its RTT for each packet with ~ 8 ms, followed by Zayo with ~ 3.5 ms reduction;
  • As in June, NTT demonstrated worst results, adding about 2.5 ms to the RTT of each packet a network forwards through this carrier.
Appendix. Carrier Loss (highlighted)

Loss improvement/worsening highlighting Centurylink datapoints.
Centurylink datapoints loss in July

Loss improvement/worsening highlighting Cogent datapoints.
Cogent datapoints loss in July

Loss improvement/worsening highlighting GTT datapoints.
GTT datapoints loss in July

Loss improvement/worsening highlighting Level 3 datapoints.
Level3 datapoints loss in July

Loss improvement/worsening highlighting NTT datapoints.
NTT datapoints loss in July

Loss improvement/worsening highlighting Telia datapoints.
Telia datapoints loss in July

Loss improvement/worsening highlighting XO datapoints.
XO datapoints loss in July

Loss improvement/worsening highlighting Zayo datapoints.
Zayo datapoints loss in July

Loss improvement/worsening highlighting Huricane.
Huricane datapoints loss in July

Appendix. Carrier Latency (highlighted)

Latency spread chart highlighting Centurylink.
latency Centurylink in July

Latency spread chart highlighting Cogent.
latency Cogent in July

Latency spread chart highlighting GTT.
latency GTT in July

Latency spread chart highlighting Level 3.
latency Level3 in July

Latency spread chart highlighting NTT.
latency NTT in July

Latency spread chart highlighting Telia.
latency Telia in July

Latency spread chart highlighting XO.
latency XO latency in July

Latency spread chart highlighting Zayo.
latency Zayo in July
Latency spread chart highlighting Huricane.
latency Huricane in July

 


Disclaimer*: The data presented in this report card is intended for information purposes only and is not to be interpreted as any form of promotion or debasement for carriers herein named. Information is obtained from the Intelligent Routing Platform Lite instances, where the compulsory consent of the legal entities for collection of such information is part of the Terms and Conditions document. For privacy protection, the exact location and number of IRP Lite instances are not provided.

Boost BGP Performance

Automate BGP Routing optimization with Noction IRP

bgp demo


Tags: Tier 1

SUBSCRIBE TO NEWSLETTER

You May Also Like

ACK and NACK in Networking

ACK and NACK in Networking

In networking, communication between devices relies on the efficient exchange of data packets. Among the essential...

BGP and asymmetric routing

BGP and asymmetric routing

What is asymmetric routing? Asymmetric routing is a network communication scenario where the forward and reverse paths...