Abstract: State of the art networking solutions are tightly coupled and proprietary in nature due to multiple vendors in the networking domain. Embodiments of the present disclosure provide a method and system for management and orchestration of heterogeneous network environment using dynamic, robust and network aware microservices. The method enables a platform for automatically and dynamically identifying appropriate group of microservices in accordance with network type and service type specified by the user, thus providing a solution that generates network aware microservices for each network in the heterogeneous network landscape. Furthermore, the system manages the identified microservices for each of the network by managing the life cycle of these microservices. The right life cycle management and co-ordination of the microservices for the network is in-line with desired goals/business logic, in a reliable and scalable manner, in heterogeneous network environments.

Abstract: State of the art networking solutions are tightly coupled and proprietary in nature due to multiple vendors in the networking domain. Embodiments of the present disclosure provide a method and system for management and orchestration of heterogeneous network environment using dynamic, robust and network aware microservices. The method enables a platform for automatically and dynamically identifying appropriate group of microservices in accordance with network type and service type specified by the user, thus providing a solution that generates network aware microservices for each network in the heterogeneous network landscape. Furthermore, the system manages the identified microservices for each of the network by managing the life cycle of these microservices. The right life cycle management and coordination of the microservices for the network is in-line with desired goals/business logic, in a reliable and scalable manner, in heterogeneous network environments.

Abstract: Robotic applications are important in both indoor and outdoor environments. Establishing reliable end-to-end communication among robots in such environments are inevitable. Many real-time challenges in robotic communications are mainly due to the dynamic movement of robots, battery constraints, absence of Global Position System (GPS), etc. Systems and methods of the present disclosure provide assisted link prediction (ALP) protocol for communication between robots that resolves real-time challenges link ambiguity, prediction accuracy, improving Packet Reception Ratio (PRR) and reducing energy consumption in-terms of lesser retransmissions by computing link matrix between robots and determining status of a Collaborative Robotic based Link Prediction (CRLP) link prediction based on a comparison of link matrix value with a predefined covariance link matrix threshold. Based on determined status, robots either transmit or receive packet, and the predefined covariance link matrix threshold is dynamically updated.

Abstract: This disclosure relates generally to distributed robotic networks, and more particularly to communication link-prediction in the distributed robotic networks. In one embodiment, robots in a robotic network, which are mobile, can establish communication with a cloud network through a fog node, wherein the fog node is a static node. A robot can directly communicate with a fog node (R2F) if the fog node is in the communication range of the robot. If there is no fog node in the communication range of the robot, then the robot can establish communication with another robot (R2R) and indirectly communicate with the fog node through the connected robot. Communication link prediction is used to identify one or more communication links that can be used by a robot for establishing communication with the cloud network. A link that satisfies requirements in terms of link quality and any other parameter is used for communication purpose.

Abstract: Robotic applications are important in both indoor and outdoor environments. Establishing reliable end-to-end communication among robots in such environments are inevitable. Many real-time challenges in robotic communications are mainly due to the dynamic movement of robots, battery constraints, absence of Global Position System (GPS), etc. Systems and methods of the present disclosure provide assisted link prediction (ALP) protocol for communication between robots that resolves real-time challenges link ambiguity, prediction accuracy, improving Packet Reception Ratio (PRR) and reducing energy consumption in-terms of lesser retransmissions by computing link matrix between robots and determining status of a Collaborative Robotic based Link Prediction (CRLP) link prediction based on a comparison of link matrix value with a predefined covariance link matrix threshold. Based on determined status, robots either transmit or receive packet, and the predefined covariance link matrix threshold is dynamically updated.

Abstract: This disclosure relates generally to distributed robotic networks, and more particularly to communication link-prediction in the distributed robotic networks. In one embodiment, robots in a robotic network, which are mobile, can establish communication with a cloud network through a fog node, wherein the fog node is a static node. A robot can directly communicate with a fog node (R2F) if the fog node is in the communication range of the robot. If there is no fog node in the communication range of the robot, then the robot can establish communication with another robot (R2R) and indirectly communicate with the fog node through the connected robot. Communication link prediction is used to identify one or more communication links that can be used by a robot for establishing communication with the cloud network. A link that satisfies requirements in terms of link quality and any other parameter is used for communication purpose.