Ixia offers an extensive set of visibility intelligence feature stacks so you can get the most out of your visibility and security platform – our capabilities allow filtering based on L2 through L7. Moreover, we provide industry-specific, specialized capabilities. Each stack of features is executed with a purpose-built design to ensure you get the best performance whether in a physical data-center or a private, hybrid or public cloud.
See how we stack up!
- GTP Correlation
- GTP Load Balancing
- Location Aware
- Subscriber Sampling
- EPC Filtering
- Subscriber & Device Aware
GTP Session Correlation
To monitor quality of service (QoS) and assure quality of experience (QoE) for a mobile subscriber, you need complete visibility for all a subscriber’s data sessions. QoS and QoE are monitored with probes that generate relevant key performance indicators (KPIs) based on subscriber traffic. Probes, however, are not designed to correlate session traffic and with their resources dedicated to other functions, they become a capacity limitation with regards to the number of subscribers, throughput, and packets per second (pps) they can support. With the GTP session correlation feature, you can recreate a subscriber's full data session by tapping the various control and data plane Evolved Packet Core (EPC) or virtual EPC (vEPC) interfaces and by directing all traffic belonging to a given user to the same monitoring probe. By offloading the correlation to CloudLens or GSC, you can free probe resources by up to 50% - allowing you to scale out your monitoring infrastructure.
- True correlation covers at least S1-U, S11 interfaces, as well as handovers from 4G to 3G
- Other interfaces usually covered by probes are S5/8, S6a, S1-MME
GTP Load Balancing
To scale a monitoring infrastructure, load-balancing is required to ensure network probes get distributed traffic or sessions. Distribution ensures multiple probes can split the load of monitoring quality of service (QoS) without exceeding a given probe's capacity.
- Enabled by load balancing GTP data plane traffic (GTP-U) based on probe throughput capacity
- Enhanced by GTP session correlation function, assuring that traffic for one subscriber’s control and data sessions always reaches the same monitoring probe
Coupled with GTP correlation functionality, load balancing can be done on more than just throughput – one can load balance based on the number of supported subscribers per probe or by the supported packets per second (pps), which are often exceeded long before throughput.
Location Aware Filtering
Reduce monitoring costs by selectively sending traffic for subscribers connected to a specific area of the network to monitoring probes. This allows troubleshooting certain areas of a network geographically, while limiting the overloading of the overall monitoring infrastructure.
Reduce costs by sending only a certain percentage of the subscriber traffic to the monitoring infrastructure. Help improve throughput and limit load on tools, while still getting the insight needed to manage QoS and monitoring quality of experience (QoE).
- If a representative sample of data is selected, the variation in Probe KPIs (e.g. the percentage of calls dropped over a given period) will not be statistically significant.
This feature can be user together with subscriber aware filtering to provide whitelist capabilities for high value customers that are never sampled out.
Reduce monitoring costs by selectively sending traffic to probes based on traffic type. For example, you could send only voice over LTE (VoLTE) traffic or 4G traffic to probes, but not 2G, 3G, etc. This allows monitoring infrastructure to be more efficient, allowing faster resolution of issues based on traffic types.
Parameters for filtering include:
- Radio Access Technology (RAT) – 2G, 3G, 4G
- Bearer QoS Class Identifier (QCI), which can distinguish for example between regular data, voice and video conferencing
- APN (Access Point Name, which can further be used for differentiating between the data APN and VoLTE IMS for example)
Subscriber aware filtering enables two crucial use-cases for operators. First, it can be used as a debugging technique. Data from users who are using new features can be selectively filtered and analyzed. Second, it can be with the subscriber sampling feature to assure always-on monitoring of high value subscribers. You can get the same globally relevant statistics without losing visibility to key customers. This allows flexibility in ensuring visibility to user experience by different subscriber segments. Reduces cost on the infrastructure, while allowing an operator to provide customer's different SLAs.
- Subscribers can be identified either by IMSI (International Mobile Subscriber Identity) or IMEI (International Mobile Equipment Identity)
Beyond just subscribers, traffic can be isolated by device type, manufacturer, etc. This allows for faster troubleshooting of network issues, without overloading monitoring probes. Selectively monitoring probes of a different type allows operators to understand the QoE by device, allowing faster response and optimization of the network.
- Identify subscriber devices with IMEI (International Mobile Equipment Identity)
Visibility for the Mobile Core
Subscriber satisfaction drives a mobile operator's business health. Operators need a monitoring structure that provides them the information they need to reduce mean time to resolution (MTTR) of key issues. An infrastructure that allows them to manage quality of service (QoS) and monitoring and quality of experience (QoE).
Specialized visibility, tailored for the evolved packet core (EPC), whether in physical, virtual or hybrid deployments, is required to create a scalable monitoring infrastructure. MobileStack capabilities provide the subscriber-aware visibility an operator needs. These capabilities are offered on Ixia's GTP Session Controller and in CloudLens Private.