Abstract: A method is disclosed for downscaling a deep packet inspection service in a network apparatus. The method comprises receiving data flow in a gateway virtual machine via a software defined networking switch, and keeping track of data flow and control flow and their state per subscriber. If needed, a new deep packet inspection virtual machine is selected for the data flow. The software defined networking switch is informed on the selection of the new deep packet inspection virtual machine. The new deep packet inspection virtual machine is instructed to re-create a flow identification for the data flow to ensure deep packet inspection service continuity.

Abstract: There is provided allocating cloud computing resources to process a user session by a gateway in a mobile communications network, and allocating the cloud computing resources in pairs to user sessions. Rules for the pair of allocated resources are determined such that incoming control plane traffic associated with the session is forwarded to the both cloud computing resources forming the pair.

Abstract: In accordance with an example embodiment of the present invention, a method is provided for receiving (414) from a gateway apparatus an intercept request regarding user equipment in the communication system; creating or modifying a processing rule regarding the user equipment by including interception in the rule; transmitting (502) to a network switch processing user equipment connections a command to clone and encrypt each signalling or data packet of the user equipment connection and to transmit the encrypted signalling and data packets to a given network apparatus.

Abstract: Methods, systems, and apparatus for network monitoring and analytics are disclosed. The methods, systems, and apparatus for network monitoring and analytics perform highly probable identification of related messages using one or more sparse hash function sets. Highly probable identification of related messages enables a network monitoring and analytics system to trace the trajectory of a message traversing the network and measure the delay for the message between observation points. The sparse hash function value, or identity, enables a network monitoring and analytics system to identify the transit path, transit time, entry point, exit point, and/or other information about individual packets and to identify bottlenecks, broken paths, lost data, and other network analytics by aggregating individual message data.

Abstract: A method is disclosed for subscriber tracing in a communications system. The method comprises receiving, in a gateway apparatus (GGSN, PGW) from an O&M unit, a command message for triggering a subscriber tracing functionality. The gateway apparatus (GGSN, PGW) instructs a network node to clone each packet having a certain IP address or TEID value, in order the network node to replicate each user plane packet belonging to a session to be monitored and to send the replicated packets directly to the O&M unit for further analysis. The gateway apparatus (GGSN, PGW) collects control plane data related to the session to be monitored, and transmits the collected control plane data directly to the O&M unit in order the collected control plane data to be correlated in the O&M unit to user plane data.

Abstract: Methods, systems, and apparatus for network monitoring and analytics are disclosed. The methods, systems, and apparatus for network monitoring and analytics perform highly probable identification of related messages using one or more sparse hash function sets. Highly probable identification of related messages enables a network monitoring and analytics system to trace the trajectory of a message traversing the network and measure the delay for the message between observation points. The sparse hash function value, or identity, enables a network monitoring and analytics system to identify the transit path, transit time, entry point, exit point, and/or other information about individual packets and to identify bottlenecks, broken paths, lost data, and other network analytics by aggregating individual message data.

Abstract: A method including obtaining a plurality of data sets each describing a specific virtualized network function, acquiring and processing control information related to at least one of a communication traffic situation in a communication network for which at least one virtualized network function is implementable and a resource usage situation in a virtualization infrastructure in which at least one virtualized network function can be instantiated, and adjusting an amount and type of at least one virtualized network function instantiated in the virtualization infrastructure for usage in the communication network by, based on the processed control information, selecting at least one virtualized network function from the obtained data sets, instantiating the selected at least one virtualized network function.