Dr S A Kalaiselvan
@stpetershyd.com
Professor & Department of Computer Science and Engineering
St Peters Engineering College
Sivalingam Ambigapthi Kalaiselvan currently works at the Department of Computer Science and Engineering, Engineering College (NAAC A & UGC-Autonomous), Hyderabad. Kalaiselvan does research in Computer Communications (Networks) and Fine Automata Theory(WSN). Their current project is 'Under Water
EDUCATION
B.E(CSE), M.E(CSE), PhD(CSE)
RESEARCH INTERESTS
Network Communication, Wireless Sensor Networks, Optimization Algorithms, Sensor Networks, Routing Protocols, ACO, UWSN
Scopus Publications
Scopus Publications
S.K. Mahaboob Basha and S.A. Kalaiselvan
IOS Press
Quality of Experience (QoE) is a critical aspect of multimedia applications, which directly impacts user satisfaction and adoption. QoE predictions are used to optimize various parameters such as video quality, bitrate, and network bandwidth to enhance the user experience. However, accurate QoE prediction is a challenging task, as it involves various factors such as network conditions, video content, and user preferences. Therefore, there is a need for enhancing QoE predictions with advanced techniques to improve user satisfaction and adoption. This paper proposes incorporating more complex neural network architectures and using more diverse datasets to improve the accuracy and generalization of Quality of Experience (QoE) predictions. The paper suggests experimenting with more advanced architectures such as convolutional neural networks and recurrent neural networks, which have been shown to be effective in various applications. Additionally, the paper highlights the limitation of using a single dataset and proposes using more diverse datasets that capture different types of video content and network conditions. Enhancing QoE predictions with complex neural networks and diverse datasets include improved accuracy, better generalization, more sophisticated models, enhanced user satisfaction and increased adoption. These enhancements are expected to lead to more accurate and reliable QoE predictions, which are crucial for improving user experience in multimedia applications.
Teena Joseph, S. A. Kalaiselvan, S. U. Aswathy, R. Radhakrishnan, and A. R. Shamna
Springer Science and Business Media LLC
Kooragayala Sukeerthi, R. Kesavan, and S. A. Kalaiselvan
IEEE
When it comes to delivering IT services to businesses or consumers, the cloud provides a scalable, reliable, and cost-effective option. However, there is an increased risk associated with cloud computing due to the fact that critical operations frequently go to another organization, making it more difficult to preserve privacy and security of data, sustain data and availability, and prove compliance. It is a difficult issue in cloud computing to ensure the security of outsourced data. Data integrity should be verified by the client or an external auditor before being outsourced. Many methods using various techniques, including Proof of Retrievability, proved data ownership, privacy preservation, etc., have been developed for this goal. Various security strategies to address the current security vulnerabilities have been offered in the literature by researchers and impacted companies. Security and privacy concerns in cloud computing are also well reviewed in the literature. Unfortunately, the literature presented works lack the adaptability to counter diverse attacks without undermining cloud security goals. As a corollary, the literature has highlighted security and privacy vulnerabilities without giving suitable technological techniques to alleviate both security and privacy risks. However, studies that provide technological responses to security issues have not provided enough reasoning for the existence of these dangers. The purpose of this article is to discuss potential cloud security and privacy challenges that might arise and need a flexible approach to finding a workable solution. This study provides a comprehensive review of the relevant literature, discussing how safe cloud conflicts have made the suggested models from prior works obsolete while also taking into consideration the works' adaptability to handle future threats. The STRIDE methodology is then used to convey, from the user's point of view, the security concerns associated with cloud computing. It also analyzes the literature's many ineffective solutions and gives guidance on how to set up a safe, flexible cloud infrastructure.
B. Swathi, M. Amanullah, and S. A. Kalaiselvan
IEEE
WSNs, or wireless sensor networks, play a significant role in today's factories. Environmental tracking, preparedness, monitoring of health, intelligence tracking, and security recognition are just some of the possible areas of use for WSNs. It is challenging to replace sensor nodes (SNs) after they have been fully deployed in such applications because of the large number of SNs required for the deployment. Since most SNs are portable computers powered by batteries, it is crucial to keep an eye on each node's power usage to ensure the network lasts as long as possible. There have been several suggestions made in research throughout the years for cost-effective and energy-balanced routing strategies. The goal of the routing protocols designed to save energy inside an SN is to extend the life of the network as a whole. However, by distributing power between nodes in the network more evenly, energy-balanced routing approaches may keep the network operational for longer. Researchers have submitted many survey papers to investigate and document the different energy-efficient routing options for WSNs. While WSN load-balanced power routing methods are becoming more important, there does not seem to have a simple survey available to emphasize their importance, concepts, and principles. This research provides a comprehensive explanation of the energy-efficient along with energy-balanced routing algorithms for WSNs.
SK. Mahaboob Basha, C. Parthasarathy, S. A. Kalaiselvan, and J. Senthil Murugan
IEEE
Adaptive HTTP streaming has emerged as a new trend to aid in the adaptive delivery of video. An HTTP streaming consumer wants an exact estimate of the number of available resources and the name of the resources they'll be using. A lot of people are interested in HTTP adaptive streaming (HAS) these days, and it's now employed by most video streaming services, including Netflix and YouTube. HAS, the use of dependable delivery protocols, together with TCP , does not be troubled by way of photograph artifacts because of packet losses, that are common place in the traditional streaming era. For that reason, the QoE fashions advanced for different streaming eras by myself aren't sufficient on this paper, we attended at the maximum critical resource it really is bandwidth with the manner of neural network. A modern and current component for throughput estimation is provided by considering prior values of instantaneous throughput and round experience time. However, for the first time in HTTP streaming, we introduce the usage of bit rate estimate. Experiments show that our method can handle significant changes in bandwidth and video bit rate.
Saritha Mahankali, R. Kesavan, and S. A. Kalaiselvan
IEEE
We seek efficient as well as inexpensive strategies that reveal novel methods and concepts in the target sector, since the focus of contemporary technological and scientific endeavors, particularly Wireless Sensor Networks (WSNs), focuses on the enhancement of already-existing systems. Research based on questionnaires is a fast and thorough way to get exposure to such ideas in the intended context. For this reason, and because of the part that clusters plays in regulating and monitoring WSNs' power consumption, we present a comprehensive evaluation of clustering as well as cluster-based multi-hop protocols for routing. Network-layer navigation technologies plays a crucial role in the design of sensor networks that are wireless. Cluster-based routing algorithms are a dynamic subfield of transportation technologies that has achieved notable success in areas such as network structure administration, energy savings, collection of data, as well as so on. This study examines the pros and cons of cluster-based transport techniques in WSNs. The three main methods used by clusters-based routing protocols are cluster head choosing, clusters creation, and information transfer. Through these lenses, we examine and contrast the features and uses of certain cutting-edge cluster-based protocols for routing. Lastly, several directions for further study are suggested.
S.A. Kalaiselvan, R. Kesavan, Somasundaram, and E. Gurumoorthi
IEEE
Efficient communication is paramount in wireless sensor networks, particularly when faced with the constraints of limited node power. Underwater Acoustic Sensor Networks (UASNs) hold a crucial role in environmental observing, disaster prediction, and ocean studies. The challenge lies in maintaining seamless data transmission while conserving energy, necessitating robust routing protocols. This study introduces a Hybrid Optimized Energy Efficient Routing Protocol (HOEERP), combining the strengths of the Grey Wolf Optimization (GWO) and Bat Algorithm (BA). HOEERP initializes a diverse population with solutions from GWO and BA. The GWO phase refines communication paths using grey wolf hierarchy, while the BA phase utilizes bats' echolocation-inspired exploration. A dynamic hybridization mechanism adjusts algorithm balance over time, enhancing adaptability. Mutual learning between wolves and bats enhances solution quality. Fitness aggregation and selection merge solutions, guiding the search towards optimal energy-efficient routing paths. Solutions are decoded into paths, considering node energy levels and distances. Simulations demonstrate HOEERP's superiority over individual GWO, BA, and existing methods, enhancing metrics like energy consumption, packet delivery, throughput, and data loss. HOEERP is a significant UASN advancement, maximizing communication reliability, minimizing energy consumption, and adapting to changing conditions. This hybrid methodology paves the way for more efficient underwater communication networks, contributing to enhance environmental monitoring and marine research endeavors.
Teena Joseph, S. A. Kalaiselvan, S. U. Aswathy, R. Radhakrishnan, and A. R. Shamna
Springer Science and Business Media LLC
In recent days, due to the advent of advanced technologies such as cloud computing, accessing data can be done anywhere at any time. Meanwhile, ensuring the data security is highly significant. Authentication plays a major role in preserving security via different access control mechanisms. As a recent trend, the biological information of the individual user is considered as verification scheme for the authentication process. Traits such as fingerprint, iris, ear or palm print are widely used to develop the authentication systems from its patterns. But, to increase the complexity of the user authentication and to ensure high security, more than a trait is combined together. In this paper, a multimodal authentication system is proposed by fusing the feature points of fingerprint, iris and palm print traits. Each trait has undergone the following procedures of image processing techniques such as pre-processing, normalization and feature extraction. From the extracted features, a unique secret key is generated by fusing the traits in two stages. False Acceptance Rate (FAR) and False Rejection Rate (FRR) metrics are used to measure the robustness of the system. This performance of the model is evaluated using three standard symmetric cryptographic algorithms such as AES, DES and Blowfish. This proposed model provides better security and access control over data in cloud environment.
G. Venkata Swaroop, G. Murugaboopathi, and S. A. Kalaiselvan
IEEE
One of the main issues in MANET is security. Since MANET characteristics are dynamic, it make vulnerable to various severe attacks. Cryptography can provide a strong solution for most vulnerability. Various approaches are discussed in the literature review. From them, ID-based cryptography and key management approaches are utilized for reducing the cost and time. This paper presents a UDRPG - [Unique-Dynamic-Random-Password-Generation] method to generate unique IDs for entire nodes in the network. Each node should submit their unique random key while communication in the network. The simulation results show that UDRPG can give better results than the existing approaches.