Telefonaktiebolaget Lm Ericsson (publ)

Christofer Flinta

Andreas Johnsson

Bob Melander

Jan-Erik Mångs

Svante Ekelin

Farnaz Moradi

Konstantinos Vandikas

Lackis Eleftheriadis

Catalin Meirosu

Valentin Kulyk

Steve Baillargeon

Jawwad Ahmed

Abhishek Sarkar

Amos Kao

Lars Westberg

Athanasios Karapantelakis

Aneta Vulgarakis Feljan

Arne Norefors

Wolfgang John

Djamel Sadok

Johan Christer Wilhelm Granath

Pontus Sköldström

Johan Granath

Karl-Åke Persson

Rolf Stadler

Jans-Erik Mangs

Jan-Erik M{dot Over (a)}ngs

Erik Bergfeldt

Pal Dammvik

Bertrand Pechenot

Ramide A S Dantas

Mathew Clegg

Christian Rohner

Tim Josefsson

Rafael Pasquini

Pontus SKÖLDSTRÖM

Pål Dammvik

Ramide AS Dantas

A method by a first wireless device, for determining a status of a first cell is described herein. The first wireless device operates in a communications network. The first wireless device sends a request to a plurality of second wireless devices operating in the communications network. The plurality of second wireless devices is within radio range. The request inquires whether or not the first cell is in sleeping state. The first wireless device receives, in response to the sent request, one or more responses from the plurality of second wireless devices. The first wireless device determines whether or not the first cell is in sleeping state, based on the received responses. The methods by a network node and another wireless device receiving an indication indicating a result of the determination are also described.

First wireless device, first network node, second wireless device, and methods performed thereby, for determining a status of a cell

Methods and devices optimize backup power management for network devices connected to backup power sources including two different batteries. Machine learning techniques are used to predict upcoming power outages affecting the network device based on power-related historic information and current conditions. A backup-power operation plan prescribing usage of the backup power sources during the predicted power outages is then generated. The backup-power operation plan schedules a battery among the backup power devices to be used at least twice without being recharged.

Method and devices for optimizing backup power control using machine learning

Embodiments described herein provided methods and apparatus for controlling switching a power supply of a first network node between an electrical power grid and an alternative power supply in which the first network node is configured to transmit data to a second network node over a data transmission link. The method includes receiving first information indicative of a predicted decrease in a transmission rate of data transmitted by the first network node over the data transmission link. Responsive to receiving the first information, a first request is transmitted to the first network node to switch the power supply of the first network node from the electrical power grid to the alternative power supply.

Methods and apparatus for controlling the power supply of a network node

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).

Master node, a local node and respective methods performed thereby for predicting one or more metrics associated with a communication network

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.

Method and system for fault localization in a cloud environment

A monitoring controller and a method for monitoring network performance are provided. The comprises determining, by a monitoring controller of a first host, a change in a communication between a first and a second application instance by observing application traffic exchanged between the first and second application instance, the first application instance being executed on the first host and the second application instance being executed on a second host. The method further comprises initiating, by the monitoring controller, a monitoring instance in the first host for exchanging test packets between the first host and the second host for monitoring network performance.

Monitoring controller and a method performed thereby for monitoring network performance

A method in a power system infrastructure for controlling power supplied to a plurality of data processing machines, wherein the power system infrastructure comprises a plurality of power supply units, comprises receiving a plurality of power demand values, wherein the power demand values are associated with a respective plurality of data processing instances to be executed on the plurality of data processing machines. The method comprises estimating a total power demand value based on the received power demand values. The method comprises controlling the power system infrastructure to provide power to the plurality of data processing machines based on the estimated total power demand value.

Apparatus, method and system for controlling power supply

A method and network device for resource-aware dynamic monitoring of application units is described. Instantiation of a monitoring element is caused. A first usage status of resources is obtained. Configuration parameters of the monitoring element are set based upon the first usage status of the resources. The monitoring element is scheduled based upon the first usage status of the resources. A second usage status of the resources is obtained. A determination is performed of whether to update the monitoring element based upon the second usage status of the resources. Responsive to determining that the monitoring element is to be updated, at least one of the following is performed: (i) updating the one or more configuration parameters of the monitoring element based upon the second usage status of the resources, and (ii) rescheduling the monitoring element based upon the second usage status of the resources.

Dynamic management of monitoring tasks in a cloud environment

A first network device enables active measurement in a network path between a second network device acting as a controller of a network performance observability protocol and a wireless device. The first network device captures a measurement packet from the second network device; determines a destination of the measurement packet; and determines a measurement model associated with the destination. The measurement model represents a correspondence between one or more parameters related to the wireless device and estimated values of a measurement for the wireless device. The first network device determines a current value of a parameter related to the wireless device; determines, based on the current value of the parameter and the measurement model, a current estimation of the measurement for the wireless device; and responds to the measurement packet based on the current estimation of the measurement while avoiding to transmit the measurement packet to the wireless device.

Method and apparatus for enabling active measurements in internet of things (IoT) systems

A method and a node for distributed performance monitoring in a communication network comprising a set of nodes. Each node in the set is configured to operate alternatively as a monitor node or as a sensor node and wherein each monitor node in the network is configured to perform measurements together with a corresponding sensor node. The monitor node determines (from a priority list) the sensor node which has the highest priority and sends a first query to that sensor node. The sensor node on its side has a listening period for receiving queries. When the listening period expires, the sensor node selects the monitor node having the highest query priority and performs measurements together with said selected monitor node.

Method and node for distributed network performance monitoring

A compute infrastructure interconnected with a network configured for allotting a benchmark message. The benchmark message comprises program code, or references to program code, to be executed on a reflecting entity. The reflecting entity is able to execute program code. The program code requests capabilities of the reflecting entity when being executed. The compute infrastructure is further configured for sending of the benchmark message to the reflecting entity. The compute infrastructure is further configured for receiving the benchmark message and for executing, in the reflecting entity, the program code. The compute infrastructure is further configured for providing a benchmark reply message. The benchmark reply message comprises execution time and optionally execution result of the execution of said program code. The compute infrastructure is further configured for returning the benchmark reply message from the reflecting entity.

Compute infrastructure resource monitoring method and entities

A processor implemented method for monitoring the performance of a message queue for communication between processes is described. The method includes, by an initiating process, publishing a trigger message to a first topic in the message queue, wherein the trigger message identifies one or more performance metrics and at least two processes that communicate via the message queue. The method further includes, by one or more of the at least two processes, retrieving the trigger message from the first topic in the message queue; performing a measurement on one or more messages exchanged between the processes over the message queue, wherein the measurement determines the one or more performance metrics; and publishing the one or more determined performance metrics to a second topic in the message queue. The method also includes, at a receiving process, retrieving the published performance metrics from the second topic in the message queue.

Message queue performance monitoring

A method for managing active measurements for determining performance parameters in a communication network comprises obtaining of a maximum permitted subsession duration and obtaining of time margins. The method further comprises determining whether or not a critical resource involved in the active measurement is active due to other activities than active measurements. If the determination concluded that the critical resource is active, a sending of an ensemble of packets of a subsession of an active measurement session is initiated. If there is an intended next subsession of the active measurement session and if a time since a last ensemble of packets was sent exceeds a sleep-init time comprised in the time margins, at least the determining and, if permitted, the initiating a sending of an ensemble of packets of the next subsession of the active measurement session is repeated.

Methods and arrangements for active measurements

A method performed by a hypervisor executing a virtual machine for enabling a performance measurement between the virtual machine and a peer node, and a method performed by a physical machine comprising the hypervisor are provided. The method performed by the hypervisor comprises intercepting a packet transmitted from, or destined to, the virtual machine, the packet comprising a destination address to the virtual machine or to the peer node, and determining whether to insert a hypervisor time stamp or not in the packet. The method further comprises, when it is determined to insert the hypervisor time stamp in the packet, inserting a hypervisor time stamp in the packet, and forwarding the packet to its destination according to the destination address.

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Stockholm, Sweden

Christofer Flinta