eoMind combines a series of algorithms that automatically inform you of the impact of problems and the quality of experience of your subscribers: when things go wrong, or when unusual events take place, in true millisecond real-time. It communicates these ndings to you in natural language on a social network like wall – and allows you to interact with the algorithms to ne-tune and personalize the output to your needs. It is backed up by dynamic visualizations that are created as supporting case notes on each nding.
eoMind takes data from your own data sources; your own probes (not only Anritsu probes), network elements, OSS/BSS systems and from social networks. The eoMind platform runs a series of pre-de ned learning algorithms that analyze the streams of data in real-time.
These algorithms are designed by Anritsu to give you the kind of insight you would get if you employed a team of experts to continuously monitor every possible data source. The difference is that these algorithms analyze all the data, all the time, in real-time
Anritsu’s eoMind SIRCA Algorithm
A highlight algorithm we are delivering on the eoMind platform is SIRCA (Subscriber Impact and Root Cause Analysis).
This algorithm attempts to automatically answer the following questions:
- How do I detect issues that really affect customers quickly (within milliseconds)?
- How do I localize the cause of issues that affect customers quickly?
- How do I do this across every network technology and all the data all the time?
- How do I do this without setting up complex thresholds and other baseline analyses? In short, SIRCA looks for negative event clouds – issues that are affecting a certain amount of users and then tries to look for common ‘co-occurrence’ features in the source data. We will show you some examples of these later on.
SIRCA Output Examples
We can see that there are two ndings SIRCA has posted to a user’s wall. The rst one shows an issue with MAP (roaming) interconnect records, where a spike of 1.148 individual subscribers are being affected by a roaming error. In the second one, you can see SIRCA has identi ed the common co-occurrence features (the root causes it thinks might be). You can see the trends for each possible cause, and also a list of them. By looking at these you can quickly tell what is likely to be related to the cause of the problem
Anritsu business expansion has occurred chiefly in the information and communication field. The company's flagship measuring instrument business provides products and services indispensable to the development, manufacture and maintenance of a range of communication systems as typified in mobile phones and the Internet on a global scale. In addition, Anritsu technologies have incorporated into a range of products in other fields, such as IP network equipment, inspection equipment for food and pharmaceutical products, and precision measuring instruments for electronic component. With a foundation afforded by the "Measuring Technologies" accumulated over its history of more than 120 years, Anritsu will continue to contribute to the realization of a safe, secure and comfortable society.
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