Tata Consultancy Services Limited

Soumitra Naskar

Prateep Misra

Sumanta Ghosh

Nilanjan Roy

Arpan Pal

Balamuralidhar Purushothaman

Chirabrata Bhaumik

Deepak N Swamy

Venkatramanan Siva Subrahmanian

Satanik Panda

Ankur Chakraborty

Debnarayan Kar

Suman Adak

Satnik Panda

This disclosure relates to a distributed state exchanging model for assets of an organization or entity for an identified task in a domain of interest. The model provides a context aware autonomous Internet of things (IoT) based cognitive edge network, wherein each node is aware of the state of the other nodes based on a subscription. The state information is seamlessly updated and maintained by a certifying node of each group. The nodes are grouped based on associated capability definitions such that at least some of the groups form a hierarchy within the cognitive edge network for completing the identified task. Since the network is context aware, a new sub-task towards completing the identified task is autonomously selected by either groups or by the nodes based on the context thereby obviating a need for centralized scheduling.

Autonomous context aware state exchanging hierarchical cognitive edge network

A method and system for real-time analytics of sensor-based data is disclosed. Also disclosed is a Cloud-based Paltform-as-a-Service (PaaS) offering for sensor driven applications with services and features for their complete life-cycle management including prompt development, testing, deployment and so forth. The method of the present disclosure enables real-time tracking of various physical parameters and attributes related to smart-spaces using sensor devices implemented in the premises of the smart-space environment and using crowd-sourced user input data. Further, the parameters obtained are sent to the cloud-computing server, wherein the analytics are performed in real-time based on the obtained parameters.

Computer platform for development and deployment of sensor data based applications and services

A system and method for consolidating a plurality of heterogeneous storage systems in a data center comprising collecting data from a plurality of heterogeneous storage devices using data collection tools, using Data Preparation Tool for extracting and translating the collected data, populating a Data Model stored in source storage configuration unit suitable for analysis, analyzing and classifying the collected data by an analysis unit based upon a plurality of attributes, comprising of a Consolidation Advisor that uses the analyzed data and candidate Target System Configurations, Preferences & Constraints for generating optimum number, specification & configuration of the Consolidate Target State infrastructure and mappings of logical units from as-is data center storage infrastructure to the target state, and iteratively validating the same in a Validation task till the final desired consolidation and objectives are met.

Method and system for consolidating a plurality of heterogeneous storage systems in a data center

A highly reliable data archival and retrieval method that enables fine grained control over data availability is implemented across a Quality of Service driven archival system, configured to fragment the data into data and parity chunks for storing onto the storage node. The technique employed by the archival system enables files to be read without having need to access any metadata, thereby tolerating complete loss of such metadata. Further, the Quality of Service driven system architecture improves upon the system performance and throughput by means of a storage node regeneration process which ensures balanced load on participating storage node during various storage, retrieval and regeneration operations.

Archival storage and retrieval system

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West Bengal, India

Soumitra Naskar