Telefonaktiebolaget Lm Ericsson (publ)

Saravanan Mohan

Perepu Satheesh Kumar

Arindam Banerjee

Divya Sundar

Kumaresh Sreedhar

JayaKrishnan Kizhakke Pullarappillil

P V K Ravikumar

Nadhira Abdul Rasheed

Ishwarya Sridhar

V S Kumaresh

Nalini Srinivasan

T Balamurugan

Vijay Raajaa Sundara Raja Moorhty

The embodiments herein relate to a method performed by a cloud node. The cloud node obtains measurements from at least some of the sensor nodes. The cloud node mathematically determines a minimum number of sensor nodes and their optimal locations. Based on the obtained measurements and the mathematically determined optimal locations, the cloud node graphically determines an optimal location for each of the minimum number of sensor nodes. The cloud node compares the mathematically and the graphically determined optimal locations. When the comparison indicates that the mathematically and graphically determined optimal locations are the same, the cloud node determines a minimum number of fog nodes. Based on the optimal location of sensor nodes, the cloud node determines an optimal location for each of the minimum number of fog nodes.

Method and node for handling sensor nodes and fog nodes in a communications system

A method for managing computation load of a fog node is disclosed, wherein a computation capacity of the fog node is predicted to become unavailable to a fog network. The method comprises identifying a candidate set of nodes for computational load transfer from the fog node. The method further comprises obtaining a computation graph representing computation in the fog network, and using a learning model to identify a morphism from the obtained computation graph to a new computation graph, in which the fog node is not included. The identified morphism comprises a sequence of one or more morphing operations that replaces the fog node in the obtained computation graph with a topology of one or more nodes selected from the candidate set. The method further comprises causing computation performed at the fog node to be transferred to one or more nodes of the candidate set.

Managing computation load in a fog network

In one aspect, a method performed by a network node for predicting a probability of state change of a node (e.g., a fog node) in a network is provided. The network node determines a set of weights based on attributes of the node. The network node estimates the probability of state change of the node using the determined set of weights and a set of one or more attribute values related to the node where determining the set of weights includes maximizing an evaluation value associated to the node.

System and method for predicting the state changes of network nodes

A method () for managing access to a database is disclosed. The method comprises receiving a database query, (), executing the query on the database to obtain a result, (), generating a noise value, (), perturbing the result with the generated noise value, (), and outputting the perturbed result, (). The noise value is generated from a bimodal probability distribution having a minimum probability at zero noise. Also disclosed is an access management processing element, () for a database.

Method and apparatus for managing access to a database

A method of processing a data stream of a communication network in a distributed processing architecture comprising a plurality of processing units comprises the steps of extracting data from the data stream, wherein the data is extracted for a particular time window of a sliding time window. The extracted data is converted into a format suitable for graphical representation. A graphical representation of the converted extracted data is generated, and an estimated value of at least one structural property of the graphical representation of the data determined. The estimated value of the at least one structural property is compared with a threshold value, and a change condition reported based on the outcome of the comparison step. The change condition may be used, for example, to change a location based quality of service parameter.

Apparatus and method for processing data streams in a communication network

A behavior investigating device of a system investigating arrangement in a communication network continuously obtains statistical network usage data of users, analyzes the statistical network usage data with regard to the pattern of behavior of the users, prioritizes the users based on the analysis and informs a traffic prioritizing function about the priority of at least one of the users. The traffic prioritizing function, which may be provided in the traffic prioritizing node, determines that there is network congestion, identifies a communication session of a user in the communication network, obtains a priority of the user from a behavior investigating device and determine whether the user is to be allowed to use the communication network based on the priority and the congestion determination.

User prioritization in a congested network

A method for improving performance of a network includes identifying at least two communities of users within the network, analysing a structure of each community and clustering the communities according to community performance. The method further includes comparing a structure of a lower performing community with a structure of a higher performing community, and changing the structure of the lower performing community substantially to resemble the structure of the higher performing community. Related computer program product for carrying out a method of introducing connections among users of a network and an apparatus configured to introduce connections among users in a network are disclosed.

Method and apparatus for improving network performance

In one particular aspect a method for categorizing a user of a communication service as a churner or non-churner is provided. In some embodiments, the method includes obtaining call data for the user. Next, the call data is used to determine a value (v) for a graph parameter for the user, the graph parameter being one of: (a) an out-degree parameter, (b) a Shapley Value parameter, (c) a proximity prestige parameter, and (d) closeness centrality parameter. Next, the determined value (v) is used to determine a churn value (cv). The churn value (cv) is then used to categorize the user as a churner or a non-churner.

Methods and systems for categorizing a customer of a service as a churner of a non-churner

Methods and apparatuses for assessing user interest scores of users of a mobile network are provided. A method includes for each of a plurality of users (A) determining initial interest scores corresponding to user's interests and interest scores of friends of the user for the user's interests, based on browsing information, and (B) assessing user's interest scores based on the initial interest scores, the interest scores of the friends and friends' influence. The method further includes outputting a list including a subset of the users selected based on the user's interest scores.

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Chennai, India

Saravanan Mohan