Tata Consultancy Services Limited

Tata Consultancy Sendees Limited

Hemant Kumar Rath

Anantha Simha

Bighnaraj Panigrahi

Samar Shailendra

Shameemraj Mohinuddin Nadaf

Arpan Pal

Jyotirmoy Karjee

Garima Mishra

Abhijan Bhattacharyya

Ajay Kattepur

Sipra Behera

Vishvesh Revoori

Arun Kumar A V

Suvrat Agrawal

Sumanta Patro

Nikita Trivedi

Balamuralidhar Purushothaman

Arijit Mukherjee

Rajan Mindigal Alasingara Bhattachar

Aniruddh Rao Kabbinale

Prasant Kumar Misra

Munmun Sengupta

Alok Ranjan

Visali Mushunuri

Senthilmurugan Sengottuvelan

Balamurlidhar Purushothaman

Rashmi Ramamohan

K N R Surya Vara Prasad

Ashwini Kumar Varma

Shameem Raj Mohinuddin Nadaf

Bighnaraj Panig Rahi

Samar Shaile Ndra

Anantha Shimha

Vishvesh Revoorsi

Jyotirm Karjee

Bighnaraj Panigrah I

Fifth generation and beyond (5G+) systems are expected to adopt new network architectures, services, and deployment schemes for compatibility with the latest technologies and end user's needs. With increase in user equipment (UE), also come variety of advanced applications and use-cases, wherein each application type has its own KPI requirements. Existing resource allocation schemes in cellular networks are not able to handle such dynamic requirements due to which network slice can lead to unwanted mismanagement of resources. Present application provides systems and methods for application-aware dynamic slicing in radio access network (RAN), wherein RAN slicing is proactively managed by learning historical slice demands and consumptions. Once slices are created, the system allocates resources to user equipment by following optimal inter-slice and intra-slice mechanisms based on application type(s), traffic demand(s) and wireless characteristics of UE. Upon resource allocation the UE are further monitored to avoid resource misutilization and resource wastage.

Systems and methods for application-aware dynamic slicing in radio access network (RAN)

This disclosure relates to method and system for improving Wi-Fi performance in co-existing communication networks using learning methodologies. In recent times, most of telecom operators have expressed interest in deploying LTE (Long-Term Evolution) over the unlicensed spectrum. However, simultaneous use of unlicensed band (by operators using LTE and other Wi-Fi) presents coexistence challenges in terms of network performance especially for the Wi-Fi. The disclosed techniques enable improving the Wi-Fi performance in the co-existing communication networks based on learning methodologies. The disclosed techniques improve Wi-Fi performance based on several steps that includes detecting an interfering channel, and further identifying an optimal channel to mitigate the interference caused by the detected interfering channel. The optimal channel is identified based on an optimization technique, wherein the optimization technique is a reinforcement learning technique based on a Q-learning.

Method and system for improving Wi-Fi performance in co-existing communication networks

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.

Management and orchestration of heterogeneous network environment using dynamic, robust and network aware microservices

Video conferencing involves transmission of video as well as audio over a network between people involved in the video conferencing, over a network. Typically, quality of conference sessions are affected by quality of network connection. If the bandwidth of the network is low, that that may cause call quality issues or call drops, which is not desirable especially in certain applications such as a surgery over video conferencing. Disclosed herein is a Conference Manager (CM) that can facilitate video conferencing over a low bandwidth network. The CM uses a producer unit and a consumer unit, for video capture and transmission, and a communication device for audio capture and transmission. The CM captures and combines audio and video data at a receiving end of the communication network. The CM also uses a fast block-wise data transfer mechanism for facilitating communication between the transmitting end and the receiving end.

Conference manager (CM) for low bandwidth video conferencing

In the field of Internet of Things understanding need of applications and translating them to network parameters and protocol parameters is a major challenge. This disclosure addresses problem of enabling network services by cognitive sense-analyze-decide-respond framework. A processor implemented method is provided for enabling network aware applications and applications aware networks by a sense analyze decide respond (SADR) framework. The processor implemented method includes sensing, at least one application parameter and at least one network parameter to obtain a plurality of sensed information; analyzing, the plurality of sensed information is filtered and synchronized to generate a plurality of derived parameters; determining, a plurality of rules based on the plurality of derived parameters; validating, the plurality of rules for a plurality of scenarios to obtain plurality of decisions; and enabling, at least one of (i) network, (ii) application and (iii) protocol control based on the plurality of decisions.

System and method for enabling intelligent network services by cognitive sense-analyze-decide-respond framework

This disclosure relates generally to a method and system for multi-hop path selection for mobile robots based on cloud platform providing an optimal path for end-to-end communication in the multi-hop network. Multi-hop path selection for mobile robots, conventionally performed at mobile robot end, may not provide an optimal path as mobile robots are unaware of the global scenario of the multi-hop network. Further, computation at mobile robot end is not an energy efficient solution. The disclosed cloud system communicates the optimal path to the source mobile robot to reach the destination mobile robot through the plurality of Access Points (APs). Multi-hop path selection for mobile robots, currently performed at mobile robot end, may not provide an optimal path as mobile robots are unaware of the global scenario of the multi-hop network. The optimal path computed at cloud system increases the life-time of robotics network there by increasing the efficiency.

Method and system for multi-hop path selection for mobile robots based on cloud platform

Conventional protocols for live media streaming are not lightweight and hence not suitable for constrained video transmitting devices. The protocols are poor in terms of delay performance under lossy conditions and need to maintain a lot of states at the constrained transmitting end leading to load on the memory and draining energy of the devices. The conventionally used protocols do not perform well for intermittent connectivity. Usually the existing streaming solutions act either in completely reliable manner, using reliable transport protocol like TCP, or in completely unreliable manner using best effort unreliable transport protocol like UDP. The present disclosure provides a single streaming solution which can change the protocol semantics and maintains a balance between reliability and delay-performance, thereby optimizing the overall system goodput. The protocol does this intelligently by inferring the criticality of the segment in flight and enable live video streaming for Internet of Things (IoT).

Adaptive restful real-time live media streaming

This disclosure relates generally to telecommunication networks, and more particularly to a method and system for delay aware uplink scheduling in a communication network. The telecommunication network performs data uplink and data downlink associated with data communication between multiple transmitter-receiver pairs connected to the network, by using specific scheduling schema as part of the data processing. Disclosed are method and system for performing a delay-aware uplink scheduling in the communication network. For an uplink request received from a transmitter, the system estimates downlink delay at the corresponding receiver side. The system further estimates a processing delay for the received uplink request. Based on the estimated downlink delay and the processing delay, the system determines an uplink delay budget for the transmitter. Further, based on the uplink delay budget and an achievable data rate computed for the transmitter, the system schedules uplink for the transmitter.

Method and system for delay aware uplink scheduling in a communication network

In order to make use of computational resources available at runtime through fog networked robotics paradigm, it is critical to estimate average performance capacities of deployment hardware that is generally heterogeneous. It is also not feasible to replicate runtime deployment framework, collected sensor data and realistic offloading conditions for robotic environments. In accordance with an embodiment of the present disclosure, computational algorithms are dynamically profiled on a development testbed, combined with benchmarking techniques to estimate compute times over the deployment hardware. Estimation in accordance with the present disclosure is based both on Gustafson's law as well as embedded processor benchmarks. Systems and methods of the present disclosure realistically capture parallel processing, cache capacities and differing processing times across hardware.

Systems and methods for estimating computation times a-priori in fog computing robotics

Methods and Systems for automatic information extraction by performing self-learning crawling and rule-based data mining is provided. The method determines existence of crawl policy within input information and performs at least one of front-end crawling, assisted crawling and recursive crawling. Downloaded data set is pre-processed to remove noisy data and subjected to classification rules and decision tree based data mining to extract meaningful information. Performing crawling techniques leads to smaller relevant datasets pertaining to a specific domain from multi-dimensional datasets available in online and offline sources.

Self-learning based crawling and rule-based data mining for automatic information extraction

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. If the link to be predicted is unavailable, the system resolves ambiguity thereby enabling communication between robots.

System and method for assisted link prediction mechanism in robotic communications

A method and a system is disclosed herein for co-operative on-path and off-path caching policy for information centric networks (ICN). In an embodiment, a computer implemented method and system is provided for cooperative on-path and off-path caching policy for information centric networks in which the edge routers or on-path routers optimally store the requested ICN contents and are supported by a strategically placed central off-path cache router for additional level of caching. A heuristic mechanism has also been provided to offload and to optimally store the contents from the on-path routers to off-path central cache router. The present scheme optimally stores the requested ICN contents either in the on-path edge routers or in strategically located off-path central cache router. The present scheme also ensures optimal formulation resulting in reduced cache duplication, delay and network usage.

Method and system for co-operative on-path and off-path caching policy for information centric networks

Internet of Things (IoT) devices (A) continuously capture raw data over a regular interval of time. The captured raw data is transmitted to gateway devices (B) deployed in an environment, for example, a warehouse. Continuous transmission of such data leads to data redundancy, continuous channel utilization and bandwidth usage, etc. To overcome this problem, present disclosure implements a Compressive Sensing based Data Prediction (CS-DP) model that predicts data at the gateway devices by learning the data pattern received from IoT devices, estimates and computes, using a Compressive Sensing based Data Estimation (CS-DE) model, optimal data instead of considering the overall data captured at the gateway devices and reconstructs, using a Compressive Sensing based Data Reconstruction (CS-DR) model, missing data and/or corrupted data using the partial information received at the gateway devices.

Data analyses using compressive sensing for internet of things (IoT) networks

In LTE Random Access Channel (RACH) mechanism, devices use slotted ALOHA based protocol for RACH message exchange. During these messages exchange, if a device does not get a response from a base-station (BS), the device assumes that it is not able to reach base station due to insufficient transmission power and increases transmit power to reach to the base station. However, at higher density most of requests are lost due to collision. In existing RACH procedure, device unnecessarily ramps power in next RACH process which leads to power wastage in already resource constrained device. When there is failure of reception of RACH process, the present disclosure computes time delays (TD) based on a RSSI value obtained from a message transmitted by the BS, and initiates RACH process accordingly. The embodiments further enable requests transmission from device to BS by ramping power of the devices based on the computed TD.

Systems and methods for delay based power ramping of devices

This disclosure relates to managing Fog computations between a coordinating node and Fog nodes. In one embodiment, a method for managing Fog computations includes receiving a task data and a request for allocation of at least a subset of a computational task. The task data includes data subset and task constraints associated with at least the subset of the computational task. The Fog nodes capable of performing the computational task are characterized with node characteristics to obtain resource data associated with the Fog nodes. Based on the task data and the resource data, an optimization model is derived to perform the computational task by the Fog nodes. The optimization model includes node constraints including battery degradation constraint, communication path loss constraint, and heterogeneous computational capacities of Fog nodes. Based on the optimization model, at least the subset of the computational task is offloaded to a set of Fog nodes.

Growing community of inventors

Bengaluru, India

Hemant Kumar Rath