Abstract: The present invention relates to an arrangement for network management and adapted to be provided in or associated with a network node to be managed. It comprises, or is in communication with, modeling means adapted to, using substantially non-formal descriptions, model network domain and behavior using formal ontologies comprising inference capabilities by means of an inference engine, thus providing a formal ontology model describing domain and behavior. It also comprises annotating means adapted to add semantic information to the formal domain and behavior ontology model, generating means adapted to, using said formal ontology model and said inference engine, elaborate an algorithm adapted to generate and update a probabilistic causal network graph structure representing the domain and its behavior.

Abstract: The present invention relates to an arrangement for monitoring performance in a network comprising a number of network devices or nodes, services and users, in real-time. The arrangement comprising information collecting means, generating means for generating performance KPI indicators depending on a number of definition performance parameters for one or more of said network nodes. The generating means comprise or communicate with decision graph generating means adapted to generate decision graph structures representing respective KPI values and combination probabilities in dependence of KPI definition performance parameters and in dependence of additional or correlation parameters.

Abstract: Method for forecasting instable policy enforcement, is described, wherein a behavior dynamic Bayesian network (DBN) model and a policy finite state transducers extended with tautness functions and identities (TFFST) model is analytically composed to derive predictions of the consequences of enforcing a given policy, in particular to detect flip-flop configuration changes in a system.

Abstract: The present invention relates to an arrangement for monitoring performance in a network comprising a number of network devices or nodes, services and users, in real-time. The arrangement comprising information collecting means, generating means for generating performance KPI indicators depending on a number of definition performance parameters for one or more of said network nodes. The generating means comprise or communicate with decision graph generating means adapted to generate decision graph structures representing respective KPI values and combination probabilities in dependence of KPI definition performance parameters and in dependence of additional or correlation parameters.

Abstract: The present invention relates to an arrangement for network management and adapted to be provided in or associated with a network node to be managed. It comprises, or is in communication with, modeling means adapted to, using substantially non-formal descriptions, model network domain and behavior using formal ontologies comprising inference capabilities by means of an inference engine, thus providing a formal ontology model describing domain and behavior. It also comprises annotating means adapted to add semantic information to the formal domain and behavior ontology model, generating means adapted to, using said formal ontology model and said inference engine, elaborate an algorithm adapted to generate and update a probabilistic causal network graph structure representing the domain and its behavior.

Abstract: Method for forecasting instable policy enforcement, is described, wherein a behavior dynamic Bayesian network (DBN) model and a policy finite state transducers extended with tautness functions and identities (TFFST) model is analytically composed to derive predictions of the consequences of enforcing a given policy, in particular to detect flip-flop configuration changes in a system.

Abstract: In a fault management system, a method and a converting unit for converting correlated sequences of network alarms into a high level language format are disclosed. The method comprises receiving episodic alarm sequence for the correlated sequences obtaining a high level language scheme, and converting the episodic alarm sequence using the accessed high level language scheme into a high level language format, to enable more efficient and reliable fault management using the converted episodic alarm sequence in high level language format.