The following data describes key components of the tested platform. No other client data is collected by MQPerf.
Maximum throughput per scenario
MQPerf performs 16 different tests, optimizing JORAM configuration to get the highest message throughput for each test. 4 axis are explored, with two possible values for each axis:
The optimal throughput for your platform is given below for each test, as a number of messages per second. This optimum is a sustainable target over time. Actual data throughput can be obtained with the relevant message size factor.
You may benefit from those results in several ways. If you already use JORAM in your application, you can find the optimal throughput of JORAM for the specific scenarios involved, and compare with your own application results. You may also consider using alternate scenarios, when functionally compatible, to improve performances. If you are at the design phase of your application, you directly gain the performance potential of JORAM under the scenarios you plan using. Again the other results may lead you to consider alternate scenarios.
The latency for messages delivery has also been collected during the tests. It is represented by three values in the table below as follows:
[mean value] | [dispersion]% | [max value].
All latency values are used for calculating those indicators, no possibly aberrant value is discarded as is usually the case when performing statistic measurements. This should be considered when analyzing a possibly high max value. The max value is thus likely to vary when the test is run anew.
The dispersion indicator describes how many measures are lower than twice the mean value. It is given as a percentage, expressing a better result with a higher value. A dispersion of 100% means that less than 1 in 100 messages have a latency higher than twice the mean value.
Comparison with reference platforms
The results for the tested platform are compared to results for related reference platforms. They are displayed on two net diagrams with 8 axes, each axis standing for a particular scenario. The scale for each axis is specific, proportional to a relative maximum value. Those results help you identify the scenarios which your platform is most suited for. They also help you estimate the potential of JORAM on other reference platforms.
Positioning in the community scale
With MQPerf community we aim at demonstrating the wide use of JORAM and comforting JORAM users with the capabilities of the middleware over a wide range of platforms. Results coming from all MQPerf analyses are averaged into a mean througput value of the 16 scenarios. Your platform is positioned onto this scale, together with our reference platforms.