Abstract: The present disclosure relates to a system (102) for assigning dynamic operation of devices in a communication network (106). The system (102) receives one or more behavioral attributes and one or more contextual attributes associated with one or more devices (232) in a communication network (106). The system (102) further determines one or more clusters (234) associated with each device from the one or more devices (232). The system (102) further determines, dynamically, one or more network slices, from a set of network slices associated with the one or more clusters (234). The system (102) further determines, dynamically, one or more analytics models associated with the one or more clusters (234). The system (102) further assigns dynamic operation of the one or more clusters (234) based on the one or more contextual attributes, the one or more network slices and the one or more analytics models.

Abstract: The present disclosure relates to system(s) and method(s) for generating an Omni-channel support platform. The method comprises integrating a multi-channel support system with a blockchain framework. Further, the method comprises generating an Omni-channel support platform based on the integration. The Omni-channel support platform comprises an Omni-channel support block for a user from a set of users. The Omni-channel support block comprises a support ledger and a support smart contract for the user. The Omni-channel support block further comprises capturing transaction data associated with the user from the multiple support channels. Further, the Omni-channel support block comprises recommending one or more resolutions to each user upon based on a support request.

Abstract: The present disclosure relates to a system (102) for assigning dynamic operation of devices in a communication network (106). The system (102) receives one or more behavioral attributes and one or more contextual attributes associated with one or more devices (232) in a communication network (106). The system (102) further determines one or more clusters (234) associated with each device from the one or more devices (232). The system (102) further determines, dynamically, one or more network slices, from a set of network slices associated with the one or more clusters (234). The system (102) further determines, dynamically, one or more analytics models associated with the one or more clusters (234). The system (102) further assigns dynamic operation of the one or more clusters (234) based on the one or more contextual attributes, the one or more network slices and the one or more analytics models.

Abstract: A method and system for rule based Internet Protocol version 4 (IPv4) to Internet Protocol version 6 (IPv6) migration assisting framework is disclosed. The method provides guidance and assistance for migrating a product, a system or the like to IPv6. The method views across the complete development life cycle, not restricting only to the impacted code base of the system artifacts. The method scans the system artifacts for IPv4 dependency detection and then provides IPv4 Dependency Removal Effort Estimation (IDRE). The IPv4 dependency detection is based on predefined Meta-rules constructed with respect to the context of product. The IDRE combines Analysis Effort (AE) and Project Execution Effort (PEE) to provide a user and/or the organization order of magnitude estimate based on the assessment of IPv4 dependencies, level of coupling with IPv4 dependencies against different parts of the system artifacts.

Abstract: A method and system for rule based Internet Protocol version 4 (IPv4) to Internet Protocol version 6 (IPv6) migration assisting framework is disclosed. The method provides guidance and assistance for migrating a product, a system or the like to IPv6. The method views across the complete development life cycle, not restricting only to the impacted code base of the system artifacts. The method scans the system artifacts for IPv4 dependency detection and then provides IPv4 Dependency Removal Effort Estimation (IDRE). The IPv4 dependency detection is based on predefined Meta-rules constructed with respect to the context of product. The IDRE combines Analysis Effort (AE) and Project Execution Effort (PEE) to provide a user and/or the organization order of magnitude estimate based on the assessment of IPv4 dependencies, level of coupling with IPv4 dependencies against different parts of the system artifacts.