Hemant Kumar Rath

Universal caching model and Markov-based cache analysis for information centric networks

Information Centric Networks (ICN) is proposed as an alternative design for content-based communication rather than host-to-host-based communication. In ICN architecture, the data are cached or stored at intermediate routers to satisfy future demands locally without repeatedly getting it from the original source. For ICN architecture to work efficiently, caching policies must be defined such that most of the requests are satisfied locally. In this paper, we propose Universal Caching, a novel caching algorithm which takes into account multiple parameters like distance from the content source, frequency of fetching the content, number of outgoing links at the intermediate router. We further propose a discrete time Markov model and entropy-based analysis to determine the cache size for a given cache hit requirement at a router in ICN networks. We have also established that Universal Caching policy is in fact an optimal caching policy and have calculated the bounds for the same as well. To validate the proposed caching policy and the analytical model, we have conducted extensive MATLAB-based simulations. Our simulation results show that the Universal Caching outperforms other caching policies like Least Recently Used, First In, First Out in terms of cache hits, access delay, etc.

A novel overlay architecture for Information Centric Networking

Information Centric Networks (ICN) has emerged as a new Internet paradigm where the users are being provided seamless access to contents rather than the host as in classical approach. For ICN realization, the current Internet requires architectural changes. These changes must be incorporated such that existing applications continue running without any difficulties. In this paper, we introduce a novel ICN architecture, called Overlay Information Centric Networks (O-ICN), which separates the data plane from the control plane activities of the network. Unlike the usual ICN architectures, in our approach naming and routing (control plane) functionalities have been segregated from the caching (data plane) functionality at each ICN router. We introduce a new module called an ICN Manager which is an extended version of Domain Name System (DNS) server and performs name resolution along with routing functionalities for ICN type of requests as well as the normal DNS resolution for non-ICN type of requests. The O-ICN architecture can be deployed incrementally over the current Internet and can operate both as ICN and non-ICN/legacy network simultaneously. This can also be implemented both in Software Defined Networks (SDN) as well as non-SDN networks without much modifications. The proposed architecture provides benefits in terms of simplification of network management, vendor independent solution, better use of network resources in terms of bandwidth and delay, and reduction of deployment/operational cost of the network.

Interference-aware discovery and optimal uplink scheduling for D2D communication in LTE networks

Device-to-Device (D2D) communication underlaying a cellular infrastructure has recently gained tremendous interest not only by the researchers but also by cellular operators and equipment manufacturers. In this paper, we have introduced a novel D2D communication scheme which can be realized by a D2D discovery mechanism along with a two-phase interference-aware optimal D2D uplink scheduling scheme for Long Term Evolution (LTE) networks. Our proposed scheme is different from the D2D emergency communication use-case being proposed by 3rd Generation Partnership Project (3GPP) in (i) reuse of Resource Blocks (RBs) and (ii) network assisted D2D communication, because of which commercial use of the proposed scheme can be made possible. To validate the proposed scheme, we have conducted extensive simulations usingMatlab and emulations in a test-bed created for this purpose. Both simulation and emulation results demonstrate that by allowing D2D communication along with cellular communication, network performance is improved significantly. However, implementing D2D along with the cellular transmissions requires certain changes in the 3GPP standards and should be reflected in the future releases of LTE.

A novel approach for an enterprise network transformation and optimization

It is well known that an enterprise network design and transform are highly skill based and iterative exercises carried out by a network engineer. To make this process simpler, we propose a collect-analyze-plan enterprise network transformation framework in this paper. We also extend this approach to optimize an existing network in a systematic way. While this paper gives inputs on how to transform/optimize the network to meet the revised needs of the enterprise, it does not propose alternate technologies either in the Local Area or Wide Area Network. We assume that the transformed network continues to use the same technology as the non-transformed one.

Monotonic Signed Graph approach for cross-layer congestion control in wireless ad-hoc networks

In this paper, we propose a Monotonic Signed Graph (MSG)-based cross-layer congestion control technique for wireless ad-hoc networks. This is a practically implementable self re-configurable distributed solution which runs independently on each wireless nodes. Moreover, it is an alternative approach to Joint Optimal Congestion control and Power control (JOCP) which solves a dual of social optimization problem in-terms of individual optimization functions. Our simulation results demonstrate that the proposed MSG scheme performs at-par (in-terms of throughput and transmission power) with JOCP scheme. Our scheme is a novel scalable approach as there is no message passing involved which is prevalent in JOCP. Though the rate of convergence of MSG approach is bit slower as compared to that of JOCP, it is within 4–5 Round Trip Times (RTTs). Hence it is a major candidate for implementing cross-layer congestion control in wireless ad-hoc networks, where long-flows are of importance. We also verify the robustness of our scheme.

Resource optimization in fog enabled IoT deployments

Internet of Things (IoT) devices are typically deployed in resource (energy, computational capacity) constrained environments. Connecting such devices to the cloud is not practical due to variable network behavior as well as high latency overheads. Fog computing refers to a scalable, distributed computing architecture which moves computational tasks closer to Edge devices or smart gateways. As an example of mobile IoT scenarios, in robotic deployments, computationally intensive tasks such as run time mapping may be performed on peer robots or smart gateways. Most of these computational tasks involve running optimization algorithms inside compute nodes at run time and taking rapid decisions based on results. In this paper, we incorporate optimization libraries within the Robot Operating System (ROS) deployed on robotic sensor-actuators. Using the ROS based simulation environment Gazebo, we demonstrate case-study scenarios for runtime optimization. The use of optimized distributed computations are shown to provide significant improvement in latency and battery saving for large computational loads. The possibility to perform run time optimization opens up a wide range of use-cases in mobile IoT deployments.

Dynamic relay selection and channel adaptive uplink for LTE Device-to-Device (D2D) communication

With the advancement of smart phone technologies cellular communication has come to a stage where available bandwidth has surpassed the user demands. Moreover, the well organized yet stubborn architecture of cellular networks sometimes creates hindrance to the optimal usage of the network resources. Due to this, a User Equipment (UE) experiencing a poor channel to the evolved NodeB (eNB) suffers with either low-rates or failed transmissions. However, Device-to-Device (D2D) offload/relay underlying the cellular network provides a unique solution where the poor channel UE can find a close proximity relay UE to relay its data to the eNB. In this paper, we have proposed a joint solution for dynamic selection of an optimal relay UE and then adaptive modulation based D2D scheduling scheme. We have considered the dynamic behavior of random wireless channel and mobility of the UEs. We have validated our proposed model using MATLAB simulations. The simulation based observations show significant improvements in network performance.

Novel self-learning based crawling and data mining for automatic information extraction

In this paper, we propose techniques using a novel combination of self-learning based crawling and rule based data mining. Using the crawling techniques smaller relevant data sets can be obtained pertaining to a domain from multi-dimensional data sets available in on-line as well as off-line sources. We then process the crawled data sets and mine to extract meaningful information. Our techniques are generic in nature and can be used for automatic information extraction in different domains such as biomedical, health-care, enterprise infrastructure planning, etc. The proposed schemes are of reduced time, space and processor complexity due to the assisted and learning nature of the crawling. The data mining is based on configurable classification rules and decision trees, which are scalable and easy to implement in practice. We evaluate our proposed techniques through Java based implementation and integration with TCS in-house enterprise network design tool NetDes.

An open source based network as a service (NaaS) platform for cloud provisioning

Cloud provisioning is an emerging area and highly embraced by Enterprises. There are several commercial and open source solutions available in the market. We discuss the problem areas in NaaS with respect to the available solutions and our approach to address the concerns by means of an open source middle layer single umbrella platform called “TCS Network as a Service (TNaaS)”. This platform is modular in nature and provides a vendor agnostic NaaS for cloud provisioning. We also provide a lab based evaluation comprising of OpenStack cloud software, TNaaS, open vSwitches and Floodlight Software Defined Network (SDN) controller.

Arima - Asymmetric Receiver Initiated Multiple Access Power Control Protocol for Wireless Ad-Hoc Networks

In a distributed control wireless ad-hoc network, network performance is significantly effected by multi-user interference. In such networks, transmit power control can enhance the energy usage as well as the QoS performance. Although, the effects of hidden/exposed terminals on the system throughput in wireless ad-hoc networks have been studied extensively, the IEEE 802.11 with variable transmit power has to be re-looked in order to optimize the energy and other QoS measures (e.g, bandwidth, throughput). In this paper, we capture the drawbacks of the existing fixed and variable transmission-power control Medium Access Control (MAC) protocols and propose an efficient energy aware receiver initiated variable transmission-power control protocol called Asymmetric Receiver Initiated Multiple Access (ARIMA). It minimizes interference due to the exposed terminal carrier sense nodes at the receiver and hence offers higher network performance. We compare the performance of our proposed protocol with the existing protocols analytically and through exhaustive simulation studies and observe that ARIMA outperforms the existing protocols in terms of throughput and packet transmission probability. This is a simple protocol and can be used in practice.