Testing an IP network improve the time to market, and reduce problems after deployment. Using the right tools will reduce the work time significantly. Practical examples include:
In a real life network, the received signal is never exactly the same as the original signal, some deviations will always happen. The physical distance the signal needs to travel in the network will cause inevitable delay. All the network nodes will add additional delay, but also add to the jitter and packet drop to the signal.
Emulating these deviations will help to strenghten the network to withstand the challenges, and also to estimate the QoE (Quality of Experience) with a given level of network quality.
With the deviation emulator Rude, it is possible to create scenarios of all of these deviations. In order to find out the maximum limits the network can take, it is possible to create a timed scenario where the amount of delay, for example, is gradually increased.
At times, everyone wants to be online at the same time. The network might be congested at peak hours due to crowds gathering to see a concert or a football match, or sudden traffic bursts may be created when something special happens and everyone needs to come online at once.
When the number of users are close to the network limits, the network performance is affected. To emulate a congested network with Deviation Emulator Rude, ready made traffic profiles are available to match real-life conditions in 3G and 4G networks. The conditions can be built from scratch as well.
A severe case of congestion may lead to random call and message drops, that are due to the high packet drop caused by the congestion. The picture below describes the functionality by showing a packet drop of 33%, targeted at each flow separately.
Traffic bursts can be emulated with the tool as well. The scenario is created by buffering the traffic for a short period, and then sending out the traffic in short, intense bursts. These traffic bursts will test the network capability to handle sudden increase in the traffic.
The network service may be down due to a crash or a planned maintenance. Testing the network's ability to recover from such a break is critical to see if automatic recovery is possible or whether some manual configuration needed.
Stressing the recovery to the limit with for example a timed scenario of repeating line breaks will definitely expose any weaknesses, or in the best case, confirm that the recovery processes run smoothly.
In real life, IP traffic will not be a constant flow of flawless packets. Instead, the traffic may be delayed or bursty, the bandwidth may be limited or the line may be down entirely for periods of time. On the byte level, packets may be dropped or corrupted or fragmented into smaller packets, and data may be lost or changed on the way. In streaming protocols, the initial delay is not the main concern, but the focus is on systems robustness to errors to ensure a smooth experience for the end user.
The picture above outlines an example of a video streaming service that is followed by a multitude of users with various types of equipment. Using the Rude IP deviation emulator, the desired data streams can be targeted on the basis of the IP address, protocol etc. The targeted data streams can then be deviated to emulate realistic network conditions that vary over time. The effect of each deviation on the Quality of Experience can be tested empirically.
5G network topologies includes splitting the basestation elements into the Central Unit CU and the Distributed Unit, DU. This introduces a new fronthaul interface between the units, that will have strict requirements for latency with attention to jitter.
A few examples of challenges the F1 interface include:
Even rare occurrences happen, and may cause a lot of headache if they first occur in the live network. Setting up complex scenarios is time consuming, and may be skipped due to the effort required. However, using the Deviation Emulator Rude, the task can be managed with only a light effort.
For example, rare priority classes may occurr simultaneously, affecting the system robustness. Manually creating the scenario will be a hard task.
With Rude, it is possible to use the Data Content Modification feature on the selected flows to modify the bytes in real time. Working as a Man-In-The-Middle, the Rude can modify the bytes as required, to change the priorities of the selected traffic to create the required scenario. The figure highlights the selected, modified traffic flow as red.