FM, PM integration costs and reducing OPEX

The upshot is a reduction of the amount of data or at least a hiding of the complexity of that data:

• In FM this is about the correlation and detection of root causes of problems. Alarms can be connected to each other via complex relationships - topology, time, etc. And automated actions can be triggered, based on findings

• In PM it is about the calculation of KPIs with reasonable granularity from the mass of raw data incoming. OES can be adapted for new network elements - or even other non-telco equipment - without the need for changes in the northbound interfaces.

Getting intelligent outputs by combining PM and FM data enhances network assurance for the future and simplifies integration and automation.

What does OES offer in FM and PM?

OES comes with an out-of-the-box, fault and performance management solution, open interfaces and GUIs which can be further extended to serve specific network management use cases. OES allows for rapid element adaptation and developers get easy access to FM/PM functionality via SDKs and open interfaces, further reducing costs for OSS functionality.

How does this relate to element abstraction?

The Element Abstraction Layer manages a multitude of models, interfaces and protocols at lower levels but gives a harmonized view at the higher levels simplifying service management and other upper layer functions. Reducing or hiding the amount data to be handled by higher level systems makes for leaner and simpler operations. This data reduction occurs through complex correlation in FM and data aggregation, and in KPI calculation in PM.

What is complex correlation?

Typically a single problem in a network can trigger anything from a single alarm to several hundred alarms. Correlation helps in identifying the root cause from a set of related alarms, and making only the relevant information visible to the end-user. So, instead of seeing ten alarms pointing to the same problem you see only one alarm. There are many ways to achieve this: filtering of unwanted alarms, compression and suppression of similar alarms etc., but a complex correlation considers the topology of the network, who is connected to whom and what services are defined for physical connections. OES lets you to easily define rules to consider these aspects.

What does this mean for automation of tasks?

Knowing the root, exact cause of a problem lets you react specifically to that problem. Correlation rules can trigger automated actions like the generation of trouble tickets, restarting a network element or any other action of your choice. Automation here further reduces operations costs.

And, an example of KPI calculation and aggregation?

Raw data available in the network needs to be analyzed to perform fault analysis or to forecast traffic etc. OES lets users to define mathematical formulas called KPIs that translate this raw data into meaningful views of network status. This concept - of taking masses of raw data and extracting simple statements - is called aggregation. Higher level systems rely on such aggregated KPI information to perform service management and similar tasks. OES still provides access to the raw data if needed.

What's different about Nokia Siemens Networks FM and PM?

While PM and FM can be managed together in a combined view, they can at the same time be adapted to specific user's needs for operations efficiency. This means we combine the advantages of element-centric systems with the features of typically specialized FM or PM tools on a network level.

What is the outlook for FM and PM?

Gaining intelligent outputs by combining PM and FM data enhances a network's assurance for the future. Creating this ability at a lower level simplifies integration and automation. OES studies Event Stream Processing based platforms to achieve this goal, a promising technology for the future.