Department of Computer Science and Information Systems

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2.5G MOBILE NETWORKS: GPRS and EDGE
(McGraw Hill, 2008) Narang, Nishit
his book culminates the trilogy of books written by Sumit Kasera and Nishit Narang on three key wireless technologies "2G. 2.5G and 3G Mobile Networks. Even though 2G and 2.5G technologies, as compared to 3G, are more than a decade old, the current corporate battle for 2G spectrum in India, indicates the significance and growth potential of these technologies including GSM and GPRS. 2.5G Mobile Networks is a complete coverage of GPRS and EDGE concepts presented in simple non-technical language without complex mathematics. An ideal primer for those working in or studying networking technologies, this book focuses mainly on procedures and basis of signaling exchanges. Readers will find a detailed treatment on GPRS network architecture, a healthy mix of concepts and protocols of Air Interface and Core Network, discussion on GPRS user-plane aspects with focus on user-plane protocols, important aspects of EDGE and much more. This book will be a valuable guide to both engineers as well as students working on GPRS and EDGE. It will also be a great follow up for those will knowledge on GSM and want to know more on the intermediate technologies before studying 3G UMTS.
2DInpaint: A novel privacy-preserving scheme for image inpainting in an encrypted domain over the cloud
(Elsevier, 2020-10) Rajput, Amitesh Singh
The low cost, agility, and mobility of cloud services for processing and storage data have attracted user’s attention today. Untrusted third parties support these services, and users are always concerned about utilizing them for personal data. Addressing these data-privacy issues for image inpainting over the cloud infrastructure(s), we propose a model, 2DInpaint, to perform image inpainting by protecting image information from an eavesdropping adversary. Inpainting is a technique for modifying an image in an undetectable manner with applications ranging from restoration of damaged photographs to object-removal and replacement of lost blocks in image coding and transmission. It can be accomplished by propagating the information in the isophotes direction of the desired region(s) from the neighborhood. Performing this propagation when the image is in the encrypted domain (ED) is a challenging dilemma. The challenge is addressed by employing a modified version of 2D-bicubic interpolation over the region to be inpainted in ED. The ramp secret sharing scheme is utilized to secure image information and to reduce storage overhead over the cloud server. 2DInpaint is proved to be information-theoretical secure in a probabilistic viewpoint and through various cryptographic attacks. The qualitative and quantitative results of 2DInpaint are analyzed under the scenarios of classical image inpainting, object-removal, and text-removal, and compared with the schemes in the plain domain. Moreover, no limitations related to the topology of the region to be inpainted are required using our approach. To the best of our knowledge, 2DInpaint is the first move towards image inpainting in the ED.
2G Mobile Networks Gsm & Hscsd
(McGraw Hill, 2007) Narang, Nishit
Readers will gain a thorough and quick understanding of GSM networks-from air interface to core network and the available services. The book provides an exhaustive coverage of protocol architecture and procedures, including radio resource and mobility management, as well as call handling. It begins by laying down the fundamentals of GSM technology ? cellular concepts, network and protocol architecture of GSM. This is followed by a discussion of GSM air interface that covers important topics including GSM frame hierarchy, burst structure, physical and logical channels. The discussion then moves onto the three logical parts of any basic wireless architecture-Mobile Station, Access and Core Networks. Important procedures of access and core networks are discussed next. The book ends with discussions of service aspects of GSM networks. These include voice transfer, SMS, cell broadcast service, location services and finally circuit switched data, and the more advanced high-speed circuit switched data. About The Author: Nishit Narang is Senior Technical Leader at Flextronics Software Systems India. He has a B. Tech. degree in Computer Science and Engineering from IIT, Delhi, India, and an M.S degree in Software Systems from Birla Institute of Technology and Science, Pilani, India. Nishit's current areas of interest include software development for GSM, GPRS and 3G networks & Sumit Kasera is Senior Technical Leader at Flextronics Software Systems (formerly Hughes Software Systems), India. He has a B. Tech degree in Computer Science and Engineering from IIT, Kharagpur, India and an M.S degree in Software Systems from Birla Institute of Technology and Science, Pilani, India. Table of Contents Part I: GSM Introduction and Background 1. GSM Overview 2. GSM Air Interface Part II: GSM Network Architecture 3.
3G Mobile Networks: Architecture, Protocols and Procedures
(McGraw Hill, 2004) Narang, Nishit
In India, the mobile subscriber baser is increasing at a phenomenal rate. After the successful adoption of Second Generation (2G) Technology GSM and 2.5G Technology GPRS, the industry is now rapidly moving towards Third Generation (3G) Networks. The book, written by two young engineers, touches almost every imaginable aspect of a 3G Network, spanning across topics such as: • UMTS Network Architecture (including Access Network and Core Network), • Protocols (including RRC, NBAP, RANAP, MM/GMM, MAP and GTP), • Procedures (including UTRAN Procedures, Mobility Management, Call/Session handling and Security Management), and • Services (including Supplementary Services and Value-added Services). Also the book covers topics like IP Multimedia Sub-system (IMS) and SIGTRAN. Besides these, the book includes the status of deployment of 3G UMTS Networks across the world and provides a brief introduction to 4G Networks setting the tone for future advancements. With this coverage, the book would serve the needs of telecom engineers and students.
3TAAV: A three-tier architecture for pseudonym-based anonymous authentication in VANETs
(IEEE, 2018) Bhatia, Ashutosh
Vehicular Ad-hoc Network (VANET) is an emerging communication framework to abet in day-to-day management of vehicular traffic and safety of vehicles. Anonymous authentication is one of the key requirements in VANET ensures the privacy of the origin of the message. Existing security protocols in VANETs, that provide anonymous authentication based on the two-tier architecture, consists of two VANET elements, namely vehicles and road side units (RSUs) working as the key generating server (KGS). These protocols rely heavily on RSU to provide anonymous identity to vehicles. In these protocols, with the movement of the vehicle from one RSU to another RSU, a fresh anonymous identity needs to be generated for every vehicle with additional handing over and taking over procedures. In this paper, we propose a novel security protocol for anonymous authentication based on three-tier architecture involving three VANET elements, viz., vehicle, RSU and pseudonym server (PSS) for achieving multiple levels of anonymity in VANETs. The proposed protocol reduces the overhead incurred by the RSU for certificate management and eliminates the requirement of handing over and taking over of vehicles while changing from one RSU to another. Considering the overhead of RSU in certificate management, the number of pseudonyms cached by each vehicle and blackout-time (duration for which vehicle is not part of VANET due to non-acquisition of pseudo-identity) as performance metrics for simulation, the simulation results demonstrate the efficacy of the proposed approach
Accelerating PUF-based UAV Authentication Protocols Using Programmable Switch
(IEEE, 2022) Alladi, Tejasvi
Many UAV technology use cases (e.g., traffic management) has ultra-low latency and strong security requirements. But achieving both simultaneously is challenging. In this work, we consider UAV device authentication as a use case and develop a fast and secure UAV device authentication system. Our key idea is to leverage highly secure Physically Unclonable Functions (PUFs) and high-speed programmable packet-processing data planes, and develop a practically deployable PUF-based authentication protocol for UAVs that is (a) robust to various security attacks, and (b) enables UAV authentication at network speed. In this work, we demonstrate the feasibility of our idea by offloading the authentication protocol to a Tofino-based highspeed programmable switch. Our preliminary experiments show that protocol offloading would reduce authentication latency significantly (approx. 100 %)
Accuracy Comparison of Predictive Algorithms of Data Mining: Application in Education Sector
(Springer, 2011) Mavani, Monali
Prediction is growing area of research which is attracting many researchers. Prediction is applied to almost all the sectors. Much commercial Business Intelligence software is available in which prediction is one of the features. With the advent of Open Source Technologies, it has become possible for education sector which normally has low IT budget, to take maximum advantage of Information and Communication Technologies(ICT). This paper describes the use of Open source Software Knime for prediction of students result based upon various independent(predictor) variables and value of dependent variable can be predicted using decision tree , SOTA (Self Organizing Tree Algorithm) and Naive Bayes This paper compares these three predictive algorithms present in Knime in terms of accuracy. Predicted results are compared with the actual result in order to measure accuracy and recommends best Predictive algorithm for forecasting. This paper also demonstrates the use of Moodle - Open Source Learning Management System (LMS) Logs as one of the attributes in predicting the student results.
Achieving Ambient Intelligence in Addressing the COVID-19 Pandemic Using Fog Computing-Driven IoT
(IGI Global, 2022) Gupta, Shashank
In this chapter, the authors present a comprehensive review on how the fog computing-based IoT can be utilized for the outbreak prevention and its existing control systems. The authors have also explained how numerous edge computing devices (e.g., sensors/actuators, RFID systems, webcams, drones, etc.) are playing a key role in controlling this disease using IoT protocols like 6LoWPAN. In addition, the authors also emphasize IoT security attacks and vulnerabilities which are prevalent in the existing infrastructure setup of smart cities. The key aspects of emerging uses of IoT (such as smart retail store automation, smart transportation, smart waste management, etc.) are described that played a key role in controlling this epidemic in the existing infrastructure of sustainable smart cities. Finally, some future research directions are also discussed that highlight the steps in mitigating the effect of this pandemic using fog-enabled IoT and AI techniques.
Achieving Fairness in IEEE 802.11ah Networks for IoT Applications with Different Requirements
(IEEE, 2019-07) Rajya Lakshmi, L.
The IEEE 802.11ah standard can provide cost-effective Internet access to a large number of devices in newly evolving Internet-of-Things (IoT) and machine-to-machine (M2M) networks. To handle high collision probability caused by a large number of devices, it adopts a group-based protocol at the MAC layer and divides nodes (or sensors) into a number of groups. The formed groups may not be uniform in terms of data rate requirements, since each group is a combination of sensors with different traffic characteristics. To achieve fair resource utilization across the groups which in turn maximizes the channel utilization, this paper formulates fair grouping in IEEE 802.11ah networks as an optimization problem, and we develop a heuristic method to solve the problem in real-time. In addition, to ensure fair channel utilization by the nodes in each group, a contention window selection and adjustment method is proposed. Results from extensive simulations conducted in a dense IoT network show that the proposed fairness model achieves a superior performance than the existing methods in terms of throughput, packet delay, energy efficiency, and fairness.
Achieving Fairness in IEEE 802.11ah Networks for IoT Applications with Different Requirements
(IEEE, 2019) Lakshmi, L.R.
The IEEE 802.11ah standard can provide cost-effective Internet access to a large number of devices in newly evolving Internet-of-Things (IoT) and machine-to-machine (M2M) networks. To handle high collision probability caused by a large number of devices, it adopts a group-based protocol at the MAC layer and divides nodes (or sensors) into a number of groups. The formed groups may not be uniform in terms of data rate requirements, since each group is a combination of sensors with different traffic characteristics. To achieve fair resource utilization across the groups which in turn maximizes the channel utilization, this paper formulates fair grouping in IEEE 802.11ah networks as an optimization problem, and we develop a heuristic method to solve the problem in real-time. In addition, to ensure fair channel utilization by the nodes in each group, a contention window selection and adjustment method is proposed. Results from extensive simulations conducted in a dense IoT network show that the proposed fairness model achieves a superior performance than the existing methods in terms of throughput, packet delay, energy efficiency, and fairness.
Achieving waypoint enforcement in multi-VLAN hybrid SDN
(IEEE, 2018) Haribabu, K; Bhatia, Ashutosh
The waypoint enforcement in a network can be seen as the act of diverting the path of packets flowing in the network towards a predefined checkpoint to gain a higher degree of control over the network. Most of the existing solutions which perform waypoint enforcement in hybrid-SDN either disturb the existing VLAN configurations or possess certain limitation in terms of placement of SDN switches in the network. In this paper, we address the problem of achieving waypoint enforcement in a multi-VLAN hybrid software defined network (hybrid-SDN), which does not have these limitations. In particular, the proposed method uses the concept of gratuitous ARP (Address Resolution Protocol) to poison the ARP table of all the hosts in the network to divert the traffic packet towards an SDN switch.
Adaptable Similarity Search using Non-Relevant Information
(Elsevier, 2002-08) Ghosal, Sugata
This chapter presents a novel technique for improving the accuracy of adaptable similarity based retrieval by incorporating negative relevance judgment, and demonstrates excellent performance and robustness of the proposed scheme with a large number of experiments. Many modern database applications require content-based similarity search capability in numeric attribute space. Therefore, online techniques for adaptively refining the similarity metric based on relevance feedback from the user are necessary. Existing methods use retrieved items marked relevant by the user to refine the similarity metric, without taking into account the information about non-relevant (or unsatisfactory) items. Consequently, items in database close to non-relevant ones continue to be retrieved in further iterations. A decision surface is determined to split the attribute space into relevant and non-relevant regions. The decision surface is composed of hyperplanes, each of which is normal to the minimum distance vector from a non-relevant point to the convex hull of the relevant points.
An Adaptive Hierarchical Method for Anytime Set-wise Clustering of Variable and High-Speed Data Streams
(IEEE, 2023) Challa, Jagat Sesh; Goyal, Poonam; Goyal, Navneet
Set-wise Clustering is a clustering technique for data streams that groups sets of objects based on distribution patterns, applicable in contexts like retail chain clustering, text-based community clustering, restaurant categorization, etc. The existing set-wise clustering method cannot handle variable and high-speed streams with reasonable accuracy. This paper presents an Anytime Set-wise Clustering method for data streams known as ANYSETCLUS. The method handles the variable inter-arrival rates of stream objects using a proposed indexing structure called AnySetClusTree, which stores a hierarchy of micro-clusters of multi-set entities at varying granularity. ANYSETCLUS is highly adaptive as it supports incremental model updates, segregates outliers, enables outlier-to-concept transition, and captures concept drift. The method also enables anytime offline clustering wherein it can generate multiple clusterings of varying granularity and purity depending upon the available time allowance for final clustering. The experimental results affirm the superior efficacy of the proposed method in handling variable and high-speed streams compared to the state-of-the-art method. The experimental results also showcase its effectiveness in achieving significantly higher micro-cluster purity for low and high-speed streams. This contrasts with the state-of-the-art method, which is unable to generate valid clustering results for high-speed streams. The experiments further validate the proposed method’s capability for anytime offline clustering.
Adaptive lookup for unstructured peer-to-peer overlays
(IEEE, 2008) Haribabu, K
Scalability and efficient global search in unstructured peer-to-peer overlays have been extensively studied in the literature. The global search comes at the expense of local interactions between peers. Most of the unstructured peer-to-peer overlays do not provide any performance guarantee. In this work we propose a novel Quality of Service enabled lookup for unstructured peer-to-peer overlays that will allow the userpsilas query to traverse only those overlay links which satisfy the given constraints. Additionally, it also improves the scalability by judiciously using the overlay resources. Our approach selectively forwards the queries using QoS metrics like latency, bandwidth, and overlay link status so as to ensure improved performance in a scenario where the degree of peer joins and leaves are high. User is given only those results which can be downloaded with the given constraints. Also, the protocol aims at minimizing the message overhead over the overlay network.
Adaptive Radial Basis Functions Neural Network For Motor Imagery Task Classification
(IEEE, 2019) Agarwal, Vandana
Classification of Electroencephalogram (EEG) signals for motor imagery task has been a challenge for researchers due to the complex and highly non-separable structure of the data across different thought classes. For each specific thought in human brain, the EEG signals display a nonstationary behavior. Despite the non-similarity of EEG patterns within a motor imagery class, it is observed that they display some similarity across few samples. In this study, the similar behavior of training patterns of a motor imagery task is captured and patterns are grouped together to form sub-clusters. The sub-cluster centers are obtained using an evolutionary algorithm inspired by the attractiveness of the fireflies. Radial basis functions neural networks, with the sub-cluster centers thus obtained are used for classification. In this study, the convergence of the algorithm is analyzed for BCI Competition IV 2A data set and classification of the two motor imagery classes, left hand and tongue movement, is investigated.
Adaptive RIS design and optimization for cooperative ris-assisted wireless systems
(IEEE, 2025-07) Bitragunta, Sainath; Bhatia, Ashutosh
We propose an adaptive RIS-based cooperative transmission strategy that jointly selects one of two RIS paths and dynamically optimizes the number of active meta-atoms to maximize physical layer (PHY) secrecy capacity under a total average power constraint. Unlike existing approaches that fix the RIS size K or assume identical fading on all links, our framework uses long-term statistics to probabilistically choose between two RISs (upper or lower) with arbitrary first-hop fading, and leverages instantaneous channel state information (CSI) on the selected path to solve a convex K-sizing problem via a Lagrangian multiplier approach. We derive and present the solution for optimal K, and numerically evaluate the average PHY secrecy capacity and average PHY secrecy efficiency for the proposed optimal strategy. Numerical results show that the proposed optimal-K strategy achieves up to 35% higher average PHY secrecy capacity and 50% improvement in average PHY secrecy efficiency compared to a fixed-K benchmark strategy across moderate power thresholds. Furthermore, we present an insightful asymptotic analysis for average PHY secrecy capacity in an interesting scaling regime. Our findings demonstrate the practical benefits of adaptive RIS for cooperative PHY secure and energy-efficient beyond fifth generation (B5G) wireless systems
Adaptive Zone Size Selection Method for IEEE 802.16j Mobile Multihop Relay Networks
(Springer, 2017-08) Rajya Lakshmi, L.
IEEE 802.16j relay networks are capable of extending the coverage areas of IEEE 802.16 networks and can support the data rate requirements of users at cell edges. In these networks, each frame is divided into various zones to facilitate data transmission between various types of nodes. As the link qualities in the network change, accordingly the zone sizes should also change to support the Quality of Service (QoS) requirements of flows and to avoid bandwidth wastage. To address this issue, in this paper, we propose an adaptive zone size selection method for IEEE 802.16j networks. With this method, zone sizes of scheduling nodes are adaptively changed in accordance with their changing link qualities. As the link qualities degrade, the scheduling nodes may not be able to support the QoS requirements of flows due to the lack of free bandwidth availability in the corresponding zones. To handle this issue with less control overhead, we propose a cross-zone bandwidth allocation method. A zone size reselection method is also proposed to handle the situations where the cross-zone bandwidth allocation is not possible. Performance of the proposed method is compared with the performance of a fixed zone size selection method and a zone size selection method proposed in the literature. The proposed method shows significantly better performance than the other two methods in terms of traffic admittance, bandwidth utilization, and satisfaction ratios of flows.
Adaptive Zone Size Selection Method for IEEE 802.16j Mobile Multihop Relay Networks
(Springer, 2017-08) Lakshmi, L.R.
IEEE 802.16j relay networks are capable of extending the coverage areas of IEEE 802.16 networks and can support the data rate requirements of users at cell edges. In these networks, each frame is divided into various zones to facilitate data transmission between various types of nodes. As the link qualities in the network change, accordingly the zone sizes should also change to support the Quality of Service (QoS) requirements of flows and to avoid bandwidth wastage. To address this issue, in this paper, we propose an adaptive zone size selection method for IEEE 802.16j networks. With this method, zone sizes of scheduling nodes are adaptively changed in accordance with their changing link qualities. As the link qualities degrade, the scheduling nodes may not be able to support the QoS requirements of flows due to the lack of free bandwidth availability in the corresponding zones. To handle this issue with less control overhead, we propose a cross-zone bandwidth allocation method. A zone size reselection method is also proposed to handle the situations where the cross-zone bandwidth allocation is not possible. Performance of the proposed method is compared with the performance of a fixed zone size selection method and a zone size selection method proposed in the literature. The proposed method shows significantly better performance than the other two methods in terms of traffic admittance, bandwidth utilization, and satisfaction ratios of flows.
Addressing Challenges in Browser Based P2P Content Sharing Framework Using WebRTC
(IEEE, 2016) Haribabu, K; Sinha, Yash
Most of the content sharing applications use the client/server model in which all of group managements are done by the server and this sometimes becomes a communication bottleneck. Installing specialized software for different purposes such as file sharing, video conferencing etc., becomes a barrier for the user. Recent technologies like NodeJs and Socket.io have fostered new ideas the ways web browsers can be used. Moreover, the emerging standards of WebRTC open up new paradigm of direct communication channel between web browsers without relaying the data through a web server. But there are certain issues such as lack of full-fledged threading/concurrency support in the JavaScript language, reliance on synchronous loading etc. that restricts modern day browsers to take full advantage of current multiprocessing capabilities. Although, on one hand there are advantages of using web browsers, such as no requirement of specialized software, benefits of emerging technologies etc., the aforementioned issues pose challenges in implementation in certain areas. In this paper, we have tried to couple the benefits of peer-to-peer (P2P) architecture (elimination of centralized dependency, better scalability, shareability etc.) along with the advantages of recent web technologies (NodeJs, WebRTC etc.) by designing and implementing a browser based P2P content sharing framework. We have addressed the aforementioned challenges of a browser based P2P architecture by providing a mechanism to exchange messages asynchronously and facilitating new peer joins via existing peers in the network, thus reducing the dependency on bootstrap server. Our prototypical implementation demonstrates the feasibility, efficiency and scalability of this lightweight framework, on the top of which a variety of applications can be added as a layer of functionality.
AdQuestA: knowledge-guided visual question answer framework for advertisements
(IEEE, 2025) Goyal, Poonam
In the rapidly evolving landscape of digital marketing, effective customer engagement through advertisements is crucial for brands. Thus, computational understanding of ads is pivotal for recommendation, authoring, and customer behaviour simulation. Despite advancements in knowledge-guided visual-question-answering (VQA) models, existing frameworks often lack domain-specific responses and suffer from a dearth of benchmark datasets for advertisements. To address this gap, we introduce ADVQA, the first dataset for ad-related VQA sourced from Facebook and X (twitter), which facilitates further research in ad comprehension. It comprises open-ended questions and detailed context obtained automatically from web articles. Moreover, we present AdQuestA, a novel multimodal framework for knowledge-guided open-ended question-answering tailored to advertisements. AdQuestA leverages a Retrieval Augmented Generation (RAG) to obtain question-aware ad context as explicit knowledge and image-grounded implicit knowledge, effectively exploiting inherent relationships for reasoning. Extensive experiments corroborate its efficacy, yielding state-of-the-art performance on the AD-VQA dataset, even surpassing 10X larger models such as GPT-4 on this task. Our framework not only enhances understanding of ad content but also advances the broader landscape of knowledge-guided VQA models.