System and method for providing emulation as a service framework for communication networks

1 . A processor-implemented method for providing an emulation as a service (EaaS) framework for a communication network comprising:

receiving, via an input/output interface, one or more configuration parameters of the communication network, a configuration file from a user and a historical data of at least one emulation from one or more database, wherein the communication network comprising one or more resources, wherein the one or more configuration parameters are number of access points (APs), number of stations connected to each AP, a channel number, a transmission power of the AP, a transmission mode, a data rate associated with a transmission control protocol (TCP) application, and a packet size;

parsing, via one or more hardware processors, the received one or more configuration parameters of the communication network to define a topology of the communication network based on the received configuration file;

generating, via the one or more hardware processors, an emulation script based on the defined topology of the communication network using a code generator;

executing, via the one or more hardware processors, the generated emulation script in an emulator to get one or more emulated nodes, wherein the emulator acts as a base layer with an Application Programming Interface (API);

configuring, via the one or more hardware processors, one or more virtual interfaces, one or more bridges, and one or more routes for connecting at least one physical device to the emulator;

integrating, via the one or more hardware processors, the one or more emulated nodes with the at least one physical device, wherein once the emulation script is started, then based on the one or more configuration parameters, the one or more emulated nodes are created along with one or more simulation nodes allowing the at least one physical device in a simulation, and allows the one or more simulation nodes to send and receive packets over a physical communication network in real-time,

wherein the one or more emulated nodes provide abstractions of computing nodes with applications to generate traffic, thereby real-time applications are used without assembling the physical communication network of the at least one physical device;

collecting, via the one or more hardware processors, one or more logs from the emulation in a predefined format, wherein the collected one or more logs are used for prescribing the communication network configuration;

training, via the one or more hardware processors, a machine learning (ML) module with the collected one or more logs to get a trained machine learning (ML) model;

analyzing, via the one or more hardware processors, the collected one or more logs and the historical data stored in a database using the trained ML model to get an analysis output; and

predicting, via the one or more hardware processors, at least one policy to enhance performance of the communication network by provisioning the one or more resources of the communication network based on the analysis output using the trained ML model,

wherein the EaaS framework dynamically creates data flow paths to allow distributed data collection and storage by individual nodes.

2 . The processor-implemented method of claim 1 , wherein the predefined format of the collected one or more logs is converted to a unified format based on a data model mapper.

3 . The processor-implemented method of claim 1 , wherein the one or more resources of the communication network comprising a frequency channel, a bandwidth, a node computational power, and a node transmission power.

4 . A system for providing an emulation as a service (EaaS) framework for a communication network comprising:

one or more hardware processors;

a memory in communication with the one or more hardware processors to execute programmed instructions stored in the memory, wherein the one or more hardware processors are configured by the programmed instructions to:

receive one or more configuration parameters of the communication network, a configuration file from a user and a historical data from a one or more databases, wherein the communication network comprising one or more resources, wherein the one or more configuration parameters are number of access points (APs), number of stations connected to each AP, a channel number, a transmission power of the AP, a transmission mode, a data rate associated with a transmission control protocol (TCP) application, and a packet size;

parse the received one or more configuration parameters of the communication network to define a topology of the communication network based on the received configuration file;

generate an emulation script based on the defined topology of the communication network;

execute the generated emulation script to get one or more emulated nodes,

wherein the emulator acts as a base layer with an Application Programming Interface (API),

wherein the emulator is used to configure one or more virtual interfaces, one or more bridges, and one or more routes to integrate the one or more emulated nodes with at least one physical device,

wherein once the emulation script is started, then based on the one or more configuration parameters, the one or more emulated nodes are created along with one or more simulation nodes allowing the at least one physical device to participate in a simulation, and allows the one or more simulation nodes to send and receive packets over a physical communication network in real-time,

wherein the one or more emulated nodes provide abstractions of computing nodes with applications to generate traffic, thereby real-time applications are used without assembling the physical communication network of the at least one physical device;

collect one or more logs from the emulation in a predefined format, wherein the collected one or more logs are used for prescribing the communication network configuration; and

train a machine learning module with the collected one or more logs to get a trained machine learning (ML) model, wherein the collected one or more logs and the historical data stored in a database is analyzed to predict at least one policy for enhancing performance of the communication network by provisioning the one or more resources of the communication network, wherein the EaaS framework dynamically creates data flow paths to allow distributed data collection and storage by individual nodes.

5 . The system of claim 4 , wherein the predefined format of the collected one or more logs is converted to a unified format based on the data model mapper.

6 . The system of claim 4 , wherein the one or more resources of the communication network comprising a frequency channel, a bandwidth, a node computational power, and a node transmission power.

7 . A non-transitory computer readable medium storing one or more instructions which when executed by one or more processors on a system, cause the one or more processors to perform method for providing an emulation as a service (EaaS) framework for a communication network comprising:

receiving, via an input/output interface, one or more configuration parameters of the communication network, a configuration file from a user and a historical data of at least one emulation from one or more database, wherein the communication network comprising one or more resources, wherein the one or more configuration parameters are number of access points (APs), number of stations connected to each AP, a channel number, a transmission power of the AP, a transmission mode, a data rate associated with a transmission control protocol (TCP) application, and a packet size;

parsing the received one or more configuration parameters of the communication network to define a topology of the communication network based on the received configuration file;

generating an emulation script based on the defined topology of the communication network using a code generator;

executing the generated emulation script in an emulator to get one or more emulated nodes, wherein the emulator acts as a base layer with an Application Programming Interface (API);

configuring one or more virtual interfaces, one or more bridges, and one or more routes for connecting at least one physical device to the emulator;

integrating the one or more emulated nodes with the at least one physical device, wherein once the emulation script is started, then based on the one or more configuration parameters, the one or more emulated nodes are created along with one or more simulation nodes allowing the at least one physical device in a simulation, and allows the one or more simulation nodes to send and receive packets over a physical communication network in real-time,

wherein the one or more emulated nodes provide abstractions of computing nodes with applications to generate traffic, thereby real-time applications are used without assembling the physical communication network of the at least one physical device;

collecting one or more logs from the emulation in a predefined format, wherein the collected one or more logs are used for prescribing the communication network configuration;

training a machine learning (ML) module with the collected one or more logs to get a trained machine learning (ML) model;

analyzing the collected one or more logs and the historical data stored in a database using the trained ML model; and

predicting at least one policy to enhance performance of the communication network by provisioning the one or more resources of the communication network based on the analysis output using the trained ML model,

wherein the EaaS framework dynamically creates data flow paths to allow distributed data collection and storage by individual nodes.