Kamal Kumar
@igdtuw.ac.in
Associate Professor, Department of Information Technology
Indira Gandhi Delhi Technical University for Women
Dr Kamal Kumar is working as Associate
Professor in the Department of Information Technology,
IGDTW since December 2023. Previously, He was
associated with NIT Uttarakhand, Srinagar
(Uttarakhand). He served at NIT Uttarakhand from July
2018 to Dec 2023. He was also associated with University of Petroleum as
Associate Professor (July 2015 to June 2018) and
Maharishi Markandeshwar University, Mullana as
Associate Professor (Sep 2000 to June 2015). His total
experience is more than 24 years. He has served
several administrative responsibilities including HoD
CSE at NIT Uttarakhand, PTP Coordinator (NIT
Uttarakhand), Head Academics (UPES) among many
other. He has guided 04 PhD and supervising 04 PhD
scholars. He has guided 33 PG (M. Tech) students as
supervisor. He has published more than 60 Research
papers (18 SCI, 08 SCOPUS, 10 Referred, and 35
Conferences). He has published 01 Design Patent and
submitted 01 Patent with IPR for patent grant. He has
served as Chair NGCT 2018, TPC Chair NG
EDUCATION
PD, M. Tech. B. Tech.
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Vision and Pattern Recognition
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Arun Singh Bhadwal, Kamal Kumar, and Neeraj Kumar
Elsevier BV
Soni Chaurasia and Kamal Kumar
Wiley
SummaryIn wireless sensor networks, sensor nodes (SNs) are placed throughout a wide area and gather information from the surroundings. SN used to detect and send data consumes a lot of energy and dies instantly, which causes network overhead issues. Due to network overhead, network faults occur and do not cover a significant region for data transmission. A meta‐heuristic‐based adaptive routing for large‐scale opportunistic networks (MH‐ARO) is proposed in this work to overcome these problems. The network exploits the dragonfly approach (DA) with opportunistic routing in this protocol. The DA is based on local and global search (GS) optimization. In local search (LS), each node assigns/uses a rank for data transmission and selects the forwarder node after applying the decision level matrix in a single group. In GS, an opportunistic network has multiple groups. Each group sends optimal data to the next group. Each group assigns a relay ranking based on the forwarder node's highest rank. The BS receives critical data from the relay and increases the survival of the node. Based on LS and GS, MH‐ARO is categorized into two parts: (1) optimal forwarder opt (OFO) and (2) optimal route selection (ORS). In OFO, forwarder node selection is based on the following factors: relay ranking, node density, group ranking, residual energy, forwarder distance, and relay distance. ORS follows the adaptive routing and sends the data to BS using the best optimal route. The BS receives critical data without network failure and increases the survival of the node. The maximum active node participates in the network and consumes less energy so that a node covers a large region for communication. Comparing MH‐ARO's performance to competing routing protocols, key performance indicators such as PDR, MSR, alive node, survivability, AEC, AD, and throughput are examined. The results demonstrate that the MH‐ARO performs noticeably better than its rivals regarding energy efficiency.
Soni Chaurasia, Kamal Kumar, and Neeraj Kumar
Institute of Electrical and Electronics Engineers (IEEE)
Wireless sensor network (WSN) is an infrastructure-less network that deploys many interconnected sensors to monitor physical environmental conditions and sends data to the cloud/base station. Sensors monitor, analyze, and route data in Internet of Things (IoT)/WSNs. Nodes consume maximum energy for processing and routing the data from the physical environment. This article proposes an energy-efficient meta-heuristic cluster-based routing protocol (EEM-CRP) for WSNs to address energy issues. EEM-CRP protocol exploits dragonfly meta-heuristic algorithm for selecting optimal cluster head (CH) and route. The dragonfly algorithm (DA) is a kind of decision-making approach (DMA) where it works for exploitation and exploration. DA-based EEM-CRP protocol is divided into two parts: 1) optimal cluster head selection (OCHS) and 2) optimal route selection (ORS). OCHS is based on the exploitation aspect of DA and it selects the CH based on parameters such as node density, residual energy, and distance. ORS is based on exploration and choosing an optimal path based on the random walk/levy distribution function. It covers a large region with reduced energy consumption and overcomes network overhead issues. EEM-CRP ensures the participation of the maximum number of active sensor nodes’ inflow of data without much or no delay. EEM-CRP performance is compared with LEACH, whale and gray wolves (WGWO), and hybridization of metaheuristic algorithm for dynamic cluster-based routing protocol (HMBCR) algorithms on important factors including packet delivery ratio (PDR), delay, number of active nodes, and average residual energy (ARE). According to the simulation results, the EEM-CRP significantly exceeds the methodologies used by its rivals in terms of energy efficiency.
Soni Chaurasia and Kamal Kumar
Springer Science and Business Media LLC
Rajeev Tiwari, Premkumar Chithaluru, Kamal Kumar, Manoj Kumar, and Thompson Stephan
Springer Science and Business Media LLC
Soni Chaurasia and Kamal kumar
Springer Science and Business Media LLC
Arun Singh Bhadwal, Kamal Kumar, and Neeraj Kumar
Elsevier BV
Soni Chaurasia, Kamal Kumar, and Neeraj Kumar
Elsevier BV
Ravi Ranjan Kumar, Kamal Kumar, Anuj Kumar Jain, Vikrant Sharma, Neha Sharma, and Nitin Jain
IEEE
With increasing camera enabled devices huge video data is generated every second. With unlimited storage offered by cloud, most of this video data is moved to cloud storage directly or indirectly. But manually querying such a huge data is challenging for most of the people. We have proposed an indexing method where from tokens of query we can find related frames and videos in a short amount of time. Queries could be very specific e.g. “car accident in area * at time*” Thus video summarization is used to produce short summary of long videos. Manually checking these summaries is again challenging task. This work aims to generate algorithm to query any video database in fraction of time, with few keywords related to video. Aim of generating a comprehensive algorithm is achieved by creating summary of each video. And the aim is also to achieve to Generate caption for each frame and then generating cumulative summary from summarized video frames using LSTM. This is achieved by searching user keywords in these summaries and ranking related summaries using CNN.
Soni Chaurasia and Kamal Kumar
Springer Science and Business Media LLC
Kamal Kumar, Anuj Kumar Jain, Raj Gaurang Tiwari, Nitin Jain, Deden Witarsyah, and Alok Misra
IEEE
In computer science, substring search or string Matching is a vulnerable problem when text resources are very large. Productivity of diverse scraping applications depend on the effectiveness of searching algorithms. Palindrome string finding is one of these problems which has its use in many applications. The problem is about finding the number of palindrome substrings within a string. This paper discusses a naive and dynamic programming-based algorithm for finding several palindrome strings. The time complexity of algorithm has also been analyzed and an effort has been made to improve it.
Anuj Kumar Jain, Kamal Kumar, Raj Gaurang Tiwari, Nitin Jain, Vinay Gautam, and Naresh Kumar Trivedi
IEEE
The application of ameliorative datasets to foretell chronic diseases has grasped considerable attention amongst data scientists all around the globe. The study is based on the Cardiovascular disease dataset. Cardiovascular disease is a broad term concerning disorders of the heart and blood vessels and is ranked to be the topmost cause of demise worldwide. Various feature selection techniques have been applied to each of the given classification algorithms and the features which give the best accuracy are then utilized for that particular algorithm.
Kamal Kumar, Anuj Kumar Jain, Raj Gaurang Tiwari, Nitin Jain, Vinay Gautam, and Naresh Kumar Trivedi
IEEE
Web services provided by various companies in the form of various APIs (Application Programming Interfaces) have increased to a very large extent in recent years. Service Oriented Architectures (SOA) and a message exchange protocol SOAP (Simple Object Access Protocol) have become prominent methods to serve the data exchange process for web services. But Recent reports state that a large number of companies are migrating from SOAP-based architecture to Representational State Transfer or REST. REST architecture is a resourceoriented architecture where resources are the entities of the system. The APIs are implemented around these resources. Also, REST architecture is stateless architecture as the client and server do not store. RESTful services return resources in some representation format. REST is a way by which a company provides a method to use its services that is provided by them exclusively. Various websites that were SOAP oriented went to REST implementation to simplify and modernize their operations. It was found that APIs were using simple HTTP verbs with no headers. REST web APIs are developed using HTTP protocol. Therefore, it makes use of all the HTTP properties like HTTP verbs, HTTP responses, header information, etc. The work presented here elaborates on the analysis of APIs using HTTP protocols and how the APIs are validated.
Hukam Singh Rana, Thipendra P Singh, Kamal Kumar, and Krishan Kumar
Informa UK Limited
Soni Chaurasia and Kamal Kumar
IEEE
In WSNs, the most crucial matters for the research are extending the network's lifespan and improving energy efficiency. Therefore it is essential to provide an energy-efficient method for overcoming the challenges associated with optimized routing protocols for forwarder node selection. The forwarder node selection is an integral part of the process. This survey paper offers an overview of meta-heuristic techniques for minimizing energy consumption by evaluating optimized routing protocols. Here we compare opportunistic routing protocols such as ExOR, SOAR, EEOR, ENSOR, EEOR-FL, NA-TORA, ARIOR, QoS-aware OR and BOR. The use of opportunistic routing improves the efficiency, accuracy, and dependability of sensor networks. Moreover, we analyze the state-of-the-art meta-heuristics opportunistic routing protocols such as DyMORA, BMOOR, EBAR, EESCP, FPU-DA, EPO-BES, and CORP.A detailed analysis of the related methods is performed, and conclusively, the paper ends with guidelines for the forthcoming research on the energy efficiency platform/directions in WSNs.
Soni Chaurasia and Kamal Kumar
IEEE
WSNs provide fine-grained measurements of the real world. A WSN comprises of several battery-operated sensor nodes with computing, communication, and processing capabilities. Data is collected by sensors, such as those that measure temperature, air pollution, pressure, etc. To construct an entire sensor node, some supporting components, such as power supply, are required. They're widely dispersed; each can sense the physical surroundings, collect aggregated data, and transmit it to the base station or sensor nodes. The researched proposal on Dragon Fly inspired Cluster based Energy Efficient Opportunistic Routing Protocol for WSNs (DCEE-ORP) is based on the Dragonfly algorithm. It is used to filter signals or data and optimize the route. The performance of DCEE-ORP is compared to that of rival routing protocols on crucial criteria such as average energy usage and packet delivery ratio. The results demonstrate that the DCEE-ORP performs much better than its competitors in terms of energy efficiency.
Kamal Kumar, Anuj Kumar Jain, Raj Gaurang Tiwari, Nitin Jain, Vinay Gautam, and Neha Ujjwal
IEEE
The submerged pictures are gaining significance as the exploration of the world covered up in the profundity of the sea has to be known. There is extensive research work going on in this area and for that, pictures are significant because of the different components. It is somewhat hard to get accurate and specific pictures due to the submerged environment and the obstacles undersea. This poses a lot of challenges in the investigations of submerged life and finding distinguished proof of marine creatures. There are loads of cameras used to capture the images of the ocean bottom, but they are fitted within the robots which can go submerged or the sensors that can work submerged. As there are numerous issues with the cameras and sensor due to the submerged environment, so it should be taken care of. Since light changes its property as per the profundity of the submerged world and the biotic action on the ocean bottom, the captured pictures are commonly influenced by the dimness and grains because of dispersing. Besides, many more things make a commotion in the picture. Over the years, various procedures are presented and tested which can either capture better pictures or process post-captured ones for improvements. In this paper, we review various procedures which can do target improvement sought for some specific purpose. It comprises shading recreation and checking the improvement of pictures through various measures. The review work presents a comparative outcome of recent works in the area of underwater image enhancements and future scopes in this field.
Arun Singh Bhadwal and Kamal Kumar
IEEE
Molecule generation refers to the process of designing new chemicals with certain chemical properties and then optimising these properties. Following prior research, we encode chemicals as continuous vectors and decode the embedding vectors back into molecules using the variational autoencoder architecture. The encoder and decoder of the proposed variational atoencoder are based on gated recurrent unit cells. The gated recurrent unit cells limit the amount of learnable parameters in the variational autoencoder. The variational autoencoder based on gated recurrent units provides validity of 92.32 % and reconstruction accuracy of 89.63% percent, which is superior to other state-of-the-art techniques. The proposed model is effective in generating compounds with diverse properties.
Rajeev Tiwari, Kamal Kumar, Satyam Kumar, and Shelly
Springer Singapore
Chelimilla Natraj Naveen and Kamal Kumar
Springer International Publishing
Daud Ibrahim Dewan, Sandeep Chand Kumain, and Kamal Kumar
Springer International Publishing
Sandeep Chand Kumain and Kamal Kumar
Springer International Publishing
Premkumar Chithaluru, Rajeev Tiwari, and Kamal Kumar
Springer Science and Business Media LLC
Premkumar Chithaluru, Rajeev Tiwari, and Kamal Kumar
Bentham Science Publishers Ltd.
Background: Energy Efficient wireless routing has been an area of research particularly to mitigate challenges surrounding performance in category of Wireless Networks. Objectives: The Opportunistic Routing (OR) technique was explored in recent times and exhibits benefits over many existing protocols and can significantly reduce energy consumption during data communication with very limited compromise on performance. Methods : Using broadcasting nature of the wireless medium, OR practices to discourse two foremost issues of variable link quality and unpredictable node agility in constrained WSNs. OR has a potential to reduce delay in order to increase the consistency of data delivery in network. Results : Various OR based routing protocols have shown varying performances. In this paper, a detailed conceptual and experimental analysis is carried out on different protocols that uses OR technique for providing more clear and definitive view on performance parameters like Message Success Rate, Packet Delivery Ratio and Energy Consumption.