Abstract: The invention generally relates to a method and system for distribution of computational capacity for a plurality of end-devices in different localities using a decentralized edge architecture. The method and system clusters a plurality of moving nodes capable of offering highly virtualized computational and storage resources utilizing an Artificial Intelligence (AI) model. The clustering is performed by utilizing two prediction models: a mobility prediction model and a theoretical framework. The mobility prediction model learns timing and direction of movements such as mobility patterns of each of the plurality of moving nodes, as to ascertain computational capacity for the given locale at a certain time. The theoretical framework performs sequential to parallel conversion in learning, optimization and caching algorithms of the AI model under contingent circumstances.

Abstract: The invention generally relates to a method and system for enabling low-latency data communication by aggregating a plurality of network interfaces, each network interface associated with a different network. The method and system measures in real-time, network performance capabilities associated with the networks via the respective network interfaces. The method and system then assigns two or more multi-threading processors in a multi-processor architecture configured to execute a plurality of threads for processing one or more data streams. The threading in each processor is interlinked with two or more network interfaces based on the measured network performance capabilities and network performance capability requirements of the one or more data streams, thereby enabling threading-based cooperation among multi-core processors in the multi-processor architecture and the plurality of network interfaces.

Abstract: The invention provides a method and system for automatically managing a plurality of Wi-Fi access points using a network management cloud. In order to manage the plurality of Wi-Fi access points, a connection is established between one or more Wi-Fi access points and a client device using the network management cloud. The network management cloud, then, receives and analyzes information from the client device related to controlling one or more Wi-Fi access points. Thereafter, the network management cloud determines one or more operation settings for the one or more Wi-Fi access points based on the analyzed information. The one or more operation settings of the one or more Wi-Fi access points are then configured using the network management cloud. Thus, the one or more Wi-Fi access points are configured by the client device through the network management cloud.

Abstract: The invention provides a method and system for managing a plurality of Wi-Fi access points using a cloud based adaptive software defined network (A-SDN). In order to manage the plurality of Wi-Fi access points, measurement data corresponding to a plurality of network variables are collected from one or more Wi-Fi access points and one or more client devices using a cloud based network application. Once the measurement data are collected, one or more optimal settings of one or more decision variables are derived for the one or more Wi-Fi access points using one or more network variables from the plurality of network variables. The one or more optimal settings are derived by formulation of optimization problems through heuristic solutions and a machine learning based optimization using the one or more network variables.

Abstract: The invention provides a method and system for establishing a connection between a client device of a plurality of client devices and a Wi-Fi access point of a plurality of Wi-Fi access points using a cloud platform. In an embodiment, the cloud platform identifies one or more target Wi-Fi access points and transmits an SSID-password tuple associated with the client device to the one or more target Wi-Fi access points. The one or more target Wi-Fi access points, then, broadcast an SSID of the client device and upon detecting the broadcast, the client device selects a target Wi-Fi access point and transmits a message with a pre-stored SSID-password tuple to the target Wi-Fi access point. Thereafter, the target Wi-Fi access point authorizes the client device to access the target Wi-Fi access point based on a comparison of the pre-stored SSID-password tuple and the SSID-password tuple received from the cloud platform.

Abstract: The invention provides a method and system for sharing Wi-Fi in a Wi-Fi network using a cloud platform. To start with, the method and system enables registration of one or more Wi-Fi access points on the cloud platform and enables a client device to rent a Wi-Fi connection from owner of a Wi-Fi access point. Subsequently, the method and system enables the client device to select a Wi-Fi access point registered on the cloud platform based on usage fee, properties and signal quality. Further, the method and system performs offload optimization using an AI module by deciding whether data offloading from licensed spectrum to unlicensed spectrum is desirable or not. In response to deciding that data offload is desirable, the client device is allowed to connect to the selected Wi-Fi access point and transact with the Wi-Fi access point owner using cryptocurrencies in a blockchain-based network.

Abstract: The invention provides a method and system for controlling a plurality of Wi-Fi access points in a wireless network using a cloud platform. To start with, a connection is established between one or more Wi-Fi access points of the plurality of Wi-Fi access points and a client device using the cloud platform. Subsequently, details pertaining to the plurality of Wi-Fi access points are collected and analyzed using an Artificial Intelligence (AI) model. The AI model then derives configurations for the plurality of Wi-Fi access points in response to analyzing the details. Thereafter, the derived configurations are transmitted to the client device. The transmitted configurations are finally implemented at the plurality of access points using either the cloud platform or the client device. The derived configurations include optimization of Wi-Fi access point network parameters based on a frequency and a set of constraints.

Abstract: A method and system for determining an optimal wireless channel for a Wi-Fi access point in a cloud-based software defined network (SDN) using an Application Programming Interface (API) is described. Initially, the API collects the measurement information and media access control (MAC) addresses from a plurality of nearby Wi-Fi access points to a client device. The measurement information is analyzed to determine a location of the client device using an Artificial Intelligence (AI) model. To determine the location of the client device, the API creates a plurality of clusters of Wi-Fi access points and updates the plurality of clusters with one or more newly identified Wi-Fi access points. Thereafter, the API calculates an optimal wireless channel for a Wi-Fi access point from the cluster using the AI model and enables the client device to automatically switch to the optimal wireless channel for connecting with the Wi-Fi access point.

Abstract: The invention provides a method and system for tracking a position of one or more Wi-Fi devices of a plurality of Wi-Fi devices. For tracking the position of the one or more Wi-Fi devices, a Triggering Router triggers the one or more Wi-Fi devices to transmit one of a broadcast probe and a directed probe through broadcasting hidden SSID networks and common SSIDs that increase a probing tendency of the one or more Wi-Fi devices. The plurality of Wi-Fi sniffers, then, collect measurement data associated with the one or more Wi-Fi devices in response to detecting the broadcast probe transmission and the directed probe transmission. Thereafter, the position of the one or more Wi-Fi devices is estimated using an adaptive machine learning model based on an indoor model whose parameters are tuned based on radio frequency (RF) measurements from the plurality of Wi-Fi devices and the measurement data.

Abstract: The invention provides a method and system for establishing a connection between a client device of a plurality of client devices and a Wi-Fi access point of a plurality of Wi-Fi access points using a cloud platform. One or more cellular devices and one or more non-Subscriber Identity Module (non-SIM) devices of a user are registered at the cloud platform. The one or more non-SIM devices are then associated to the one or more cellular devices. Further, each Wi-Fi access point of the plurality of Wi-Fi access points is also registered at the cloud platform. A location of the client device is identified and one or more Wi-Fi access points that are closest to the client device is identified. The one or more Wi-Fi access points then authorize the client device to access the one or more Wi-Fi access points based on the information provided by the cloud platform.

Abstract: The invention provides a method and system for enhancing signal qualities within a Wi-Fi network using an adaptive-software defined network (A-SDN) and a cloud platform. The Wi-Fi network includes client devices connected to a Wi-Fi access point and a plurality of nearby Wi-Fi access points to the one or more client devices. The method and system collects radio frequency (RF) measurements pertaining to each client device, the connected Wi-Fi access point, and the plurality of nearby Wi-Fi access points, and an Artificial Intelligence (AI) model is utilized to derive interference measurements based on the RF measurements. The AI model then derives configurations related to Wi-Fi network parameters associated with the connected Wi-Fi access point based on the RF measurements and the interference measurements by solving a complex optimization problem. The Wi-Fi network parameters are then updated based on the derived configurations.

Abstract: The invention provides a method and system for establishing a connection between a client device of a plurality of client devices and a Wi-Fi access point of a plurality of Wi-Fi access points using a cloud platform. To start with, the plurality of client devices and the plurality of Wi-Fi access points are registered with the cloud platform. Subsequently, the client device transmits a network demand request to one or more target Wi-Fi access points. The one or more target Wi-Fi access points receive account details containing pre-registered credentials associated with the client device from the cloud platform. Upon receiving the account details, the one or more target Wi-Fi access points authorize the client device and broadcast a personalized SSID. The client device uses the personalized SSID to access a Wi-Fi access point of the one or more target Wi-Fi access points using the pre-registered credentials.

Abstract: The invention provides a method and system for managing a plurality of Wi-Fi access points using a cloud based adaptive software defined network (A-SDN). The measurement data corresponding to a plurality of network variables are collected from one or more Wi-Fi access points and one or more client devices. Once the measurement data are collected, optimal operating channels and optimal transmit power for the one or more Wi-Fi access points are derived based on one or more network variables, backhaul limits corresponding to the one or more Wi-Fi access points and a download behavior of the one or more client devices using a real-time optimization. The real-time optimization includes deriving the optimal settings through heuristic solutions of an optimization problem formulated as a Mixed Integer Nonlinear Programming (MINLP) and a machine learning based optimization.

Abstract: The invention provides a method and system for assigning one or more optimal wireless channels to a Wi-Fi access point of a plurality of Wi-Fi access points using a cloud-based orchestrator through a software defined network (SDN). To start with, RF measurements are collected from a plurality of client devices in the cloud using a RF measurement module. The RF measurements include received signal strength indicator (RSSI) measured by the plurality of client devices and a transmission channel from connected or nearby Wi-Fi access points. The one or more optimal wireless channels for the Wi-Fi access point are then derived by solving a complex optimization problem. This process employs an artificial intelligence (AI) module integrated with a global continuous optimization algorithm. The AI module utilizes the collected RF measurements and a plurality of measured variables for determining the one or more optimal wireless channels for the Wi-Fi access point using the optimization formulation.

Abstract: The invention provides a method and system for routing delay-tolerant communication messages to a destination device. The method and system creates an ad-hoc communication network for transmitting and/or receiving a delay-tolerant communication message by clustering a plurality of devices to form a social community. The delay-tolerant communication message received from a device connected to an ad-hoc hotspot is transmitted to the destination device using one or more moving subscribers/nodes. The method and system selects the one or more moving subscribers/nodes using a deep learning algorithm based on an MRC feature of the one or more moving subscribers/nodes, and transmits the delay-tolerant communication message from a device in the social community to the selected one or more moving subscribers/nodes.