Abstract: In a communication system, a first network node is configured to execute at least one service application executing a first service and at least one analytics application executing at least part of a distributed analytics service. The first network node obtains information about a new telecommunication service and transmits, to a second network node in the communication system, a request for a policy for the new telecommunication service. The first network node receives, from the second network node, the policy for the new telecommunication service and updates a currently applied policy on the basis of the received policy. The updated policy rebalances resources allocated from a shared computing resource pool of the first network node between the new telecommunication service and the at least one analytics application such that the new telecommunication service maintains adherence to the one or more requirements of a service level agreement.

Abstract: A master node, a local node, a service assurance system, and a respective method performed thereby for predicting one or more metrics associated with a communication network are provided. The method performed by the master node operable in the communication network comprises receiving prediction(s) based on training data from local nodes in the communication network; and determining weight parameter(s) associated with the local nodes based on the current received prediction(s) and past received predictions. The method further comprises adjusting a respective local reporting policy for one or more local nodes based on the determined weight parameter(s).

Abstract: Embodiments herein disclose e.g. a method performed by a network node (12) for handling operation in a communication network, wherein the network node comprises at least one power supply unit, and one or more additional power units for supplying power to the network node. The network node (12) obtains an output from a computational model; and sets an output voltage from the at least one power supply unit based on the obtained output.

Abstract: An automated improving of quality of service of a data center. Transients of a power grid fed to a power supply unit are monitored by a probe. Information on transients is provided across an interface to a server of the data center. Based on characteristics of the transients, a reliability of the data center is subjected to automated updating. A request for migration of workload requiring a higher reliability than the updated reliability can be sent to a central management. When the central management has identified another data center that can meet the required reliability, the central management migrates or relocates the workload to the another data center.

Abstract: A computer-implemented method and apparatus for monitoring the performance of a plurality of network nodes interconnected in a multi-hop arrangement using at least one node performance assessment threshold is described. A plurality of data sets is obtained. A data set comprises a respective value of a performance metric for each of the plurality of network nodes. Each of the plurality of data sets is classified as normal or abnormal by comparing the respective values of the performance metric of each of the plurality of network nodes to a corresponding normality threshold, thus providing a plurality of classified data sets. The plurality of classified data sets is processed using a machine-learning algorithm in order to derive, for at least one network node of the plurality of network nodes, a node performance assessment threshold indicative of a value of the performance metric of the at least one node at which the plurality of network nodes has a predetermined likelihood of being classified as normal.

Abstract: Embodiments herein disclose, e.g., a method performed by a control network node in a communications network for handling machine learning (ML) models in the communications network. The control network node determines whether or not to transmit to a network node in the communications network a ML model based on a signature and/or a loss value of the network node, wherein the signature and/or the loss value is related to ML modelling. In case where it is determined to transmit, the control network node transmits the ML model to the network node.

Abstract: In a communication system, a first network node is configured to execute at least one service application executing a first service and at least one analytics application executing at least part of a distributed analytics service. The first network node obtains information about a new telecommunication service and transmits, to a second network node in the communication system, a request for a policy for the new telecommunication service. The first network node receives, from the second network node, the policy for the new telecommunication service and updates a currently applied policy on the basis of the received policy. The updated policy rebalances resources allocated from a shared computing resource pool of the first network node between the new telecommunication service and the at least one analytics application such that the new telecommunication service maintains adherence to the one or more requirements of a service level agreement.

Abstract: It is disclosed a network node (200, 220, 300, 400, 500, 600, 80) and a method for executing an analytics task. The network node is adapted to reside in a telecommunication network, and to be supported by a distributed cloud infrastructure. The network node is adapted to execute at least one service application (202) executing a first service and at least one analytics application (204) executing at least part of a distributed analytics service, where the network node further is adapted to comprise a node policy agent (206, 226, 304, 504, 606) and a node manager (210, 230, 306, 406, 506, 608). By applying a policy restrictions on the analytics task executed on the same network node as a service application, service level agreements for the service application in a telecommunication cloud can be upheld.

Abstract: A method for predicting a location of a fault in a system is described. The method includes obtaining a faulty unit pertaining to a Supervised Self-Organizing Map (SSOM), wherein the faulty unit has been derived from a sample of machine-level metrics for the system and the SSOM has been trained with a first layer of machine-level metrics and a second layer of service-level metrics. The method further includes expanding a circle originating at the faulty unit until a number of normal units of the SSOM falls within the circle, computing, for each machine-level metric, a score based on differences between the faulty and normal units, wherein a set of scores comprises the respective score for each machine-level metric, and selecting a sub-set of the set, wherein the sub-set comprises the greatest scores of the set, whereby the fault is predicted as located according to metrics represented by the sub-set.

Abstract: A method performed by a vehicle manager (150) for managing a remote-controlled vehicle (160). The vehicle manager (150) obtains an original route to the destination passing a sequence of radio access points in a wireless network that a wireless device in the vehicle (160) will connect to in a communication with the vehicle manager (150) when the vehicle (160) travels along the original route. The vehicle manager (150) detects at least one deficient radio access point of the original route. The vehicle manager (150) then instructs the vehicle (160) to adapt its behaviour based on said detecting.

Abstract: Systems and methods are provided for generating a data driven target model associated with a service having a first configuration. The method including: determining if there is an existing data driven source model for the service having a second configuration which is different from the first configuration; wherein if there is an existing data driven source model, determining whether a level of differences between the first configuration and the second configuration enables the existing data driven source model to be used as a source model for the data driven target model being generated; wherein if there is no existing data driven source model or if the level of differences for the existing data driven source model does not enable the existing data driven source model for the first configuration to be used, then requesting a source domain.

Abstract: An automated improving of quality of service of a data center. Transients of a power grid fed to a power supply unit are monitored by a probe. Information on transients is provided across an interface to a server of the data center. Based on characteristics of the transients, a reliability of the data center is subjected to automated updating. A request for migration of workload requiring a higher reliability than the updated reliability can be sent to a central management. When the central management has identified another data center that can meet the required reliability, the central management migrates or relocates the workload to the another data center.

Abstract: A method and a network node for localizing a fault causing performance degradation of a service. The network node calculates a first, a second and a third set of correlation values for a first time interval. Similarly, the network node calculates a fourth, fifth and sixth correlation value for a second time interval in which the fault has been detected. The sets of correlation values are taken between resource metrics, virtual execution environments, types of said each resource metric and/or servers. When at least one of the absolute values is above the threshold value, the network node adds each resource metric to a list of resource metrics, wherein the list indicates resource metric from which the fault potentially originates. Next, the network node sends the list to an entity configured to manage resources available to the set of servers, thereby enabling the entity to mitigate Service Level Agreement violation.

Abstract: A method for predicting a location of a fault in a system is described. The method includes obtaining a faulty unit pertaining to a Supervised Self-Organizing Map (SSOM), wherein the faulty unit has been derived from a sample of machine-level metrics for the system and the SSOM has been trained with a first layer of machine-level metrics and a second layer of service-level metrics. The method further includes expanding a circle originating at the faulty unit until a number of normal units of the SSOM falls within the circle, computing, for each machine-level metric, a score based on differences between the faulty and normal units, wherein a set of scores comprises the respective score for each machine-level metric, and selecting a sub-set of the set, wherein the sub-set comprises the greatest scores of the set, whereby the fault is predicted as located according to metrics represented by the sub-set.

Abstract: A master node, a local node, a service assurance system, and a respective method performed thereby for predicting one or more metrics associated with a communication network are provided. The method performed by the master node operable in the communication network comprises receiving prediction(s) based on training data from local nodes in the communication network; and determining weight parameter(s) associated with the local nodes based on the current received prediction(s) and past received predictions. The method further comprises adjusting a respective local reporting policy for one or more local nodes based on the determined weight parameter(s).

Abstract: A method and a network node for localizing a fault causing performance degradation of a service. The network node calculates a first, a second and a third set of correlation values for a first time interval. Similarly, the network node calculates a fourth, fifth and sixth correlation value for a second time interval in which the fault has been detected. The sets of correlation values are taken between resource metrics, virtual execution environments, types of said each resource metric and/or servers. When at least one of the absolute values is above the threshold value, the network node adds each resource metric to a list of resource metrics, wherein the list indicates resource metric from which the fault potentially originates. Next, the network node sends the list to an entity configured to manage resources available to the set of servers, thereby enabling the entity to mitigate Service Level Agreement violation.

Abstract: It is disclosed a network node (200,220, 300, 400, 500, 600, 80) and a method for executing an analytics task. The network node is adapted to reside in a telecommunication network, and to be supported by a distributed cloud infrastructure. The network node is adapted to execute at least one service application (202) executing a first service and at least one analytics application (204) executing at least part of a distributed analytics service, where the network node further is adapted to comprise a node policy agent (206, 226,304, 504, 606) and a node manager (210, 230, 306, 406, 506, 608). By applying a policy restrictions on the analytics task executed on the same network node as a service application, service level agreements for the service application in a telecommunication cloud can be upheld.