Method and apparatus for organizing and detecting swarms in a network

An apparatus for detecting swarms in a network,

• the apparatus comprising:
• a memory to store instructions;
• and
• at least one processor, by executing the instructions, configured to:
• receive input characteristics of nodes in the network,
• generate a matrix representing a connectivity graph of devices based on the input characteristics comprising proximity among the nodes and homogeneity of the nodes,
• detect swarms based on an analysis of the input characteristics and the matrix, and
• select at least one algorithm based on at least one predefined parameter, type of nodes, or network characteristics,
• wherein the analysis of the input characteristics and the matrix comprises:
• comparing the input characteristics against validation thresholds, when the input characteristics are value pairs, and representing and processing the input characteristics as a neural network, when the input characteristics are multi-dimensional parameters, and
• comparing the input characteristics against at least one validation threshold, when the input characteristics are value pairs, and representing and processing the input characteristics as a neural network, when the input characteristics are uni-dimensional parameters,
• wherein the at least one algorithm comprises a pluggable algorithm which is plugged-in using a container-based algorithm plug-in architecture,
• wherein the container-based algorithm plug-in architecture enables binary level reuse of the at least one algorithm in different applications, and
• wherein the at least one algorithm comprises a generic swarm detection algorithm using a set inclusion and a node degree representing a number of edges connected to at least one node among the nodes.

A non-transitory computer readable medium embodying a computer program for operating an electronic device including a memory and at least one processor, the computer program comprising computer readable program code that, when executed by the at least one processor, causes the electronic device to:

• receive input characteristics of nodes in a network;
• generate a matrix representing a connectivity graph of devices based on the input characteristics comprising proximity among the nodes and homogeneity of the nodes;
• detect swarms based on an analysis of the input characteristics and the matrix;
• and
• select at least one algorithm based on at least one predefined parameter, type of nodes, or network characteristics,
• wherein the analysis of the input characteristics and the matrix comprises:
• comparing the input characteristics against validation thresholds, when the input characteristics are value pairs, and representing and processing the input characteristics as a neural network, when the input characteristics are
• multi-dimensional parameters;
• and
• comparing the input characteristics against at least one validation
• threshold, when the input characteristics are value pairs, and representing and processing the input characteristics as a neural network, when the input characteristics are uni-dimensional parameters,
• wherein the at least one algorithm comprises a pluggable algorithm which is plugged-in using a container-based algorithm plug-in architecture,
• wherein the container-based algorithm plug-in architecture enables binary level reuse of the at least one algorithm in different applications, and
• wherein the at least one algorithm comprises a generic swarm detection algorithm using a set inclusion and a node degree representing a number of edges connected to at least one node among the nodes.