P.Sivasankar

Dr. P. Sivasankar, is working as Associate Professor in Electronics Engineering, Department of Electrical, Electronics and Communication Engineering, National Institute of Technical Teachers Training and Research, Chennai, (Ministry of Education, Government of India) India, since 2006. He was born on 23rd July 1980 at Tiruvannamalai, Tamilnadu, India. He published around 36 articles like papers / book chapters etc. in various reputed International, National Journals and Conferences; published two books titled "LabVIEW Programming Concepts with Examples", Co-authored by G.A.Rathy, in Sci Tech publications, Year : 2015 and "NG Smartphone Users Activity and Direction Detection using MQTT in IoT" with the authors of Kothandaraman, D, and Nagendar, in LAMBERT Academic Publisher, Year : 2019. He coordinated around 130 Faculty Development Programmes, serving as Member of various committees and professional bodies; Evaluated UG, PG, and PHD Thesis works.

EDUCATION

B.E. in Electronics and Communication Engineering at Thanthai Periyar Govt. Inst. of Tech, Vellore-2, UNIVERSITY OF MADRAS, Average marks: 66.13%, completed at 2001

M.E. in Applied Electronics at College of Engineering Guindy, Chennai –25, ANNA UNIVERSITY, CHENNAI, CGPA: 7.804 in 10 point scale completed at 2005

Ph.D. in the Major area of Wireless Communication, with the title "Studying and Improving Energy Efficient On-Demand Routing Protocols in MANET", College of Engineering Guindy, Chennai –25, ANNA UNIVERSITY, CHENNAI, Guide : , 2013

RESEARCH INTERESTS

Wireless Communication, Signal Processing, Embedded Systems, Developing or Applying Bio-inspired Optimization Algorithms in various Engineering Domain according to its scope, Industry 4.0, Society 5.0, Cyber Physical System, Engineering Education by Blooms Taxonomy, Outcome Based Education and CDIO

Scopus Publications

Detecting pattern irregularities in astronomical images using deep learning
Shankar T, Bada Deekshitha, Vempalli Rohini, Venkataraman Muthiah Nakarajan, Sivasankar P, and J Murali
IEEE
Classification of astronomical images is a field of long standing interest. With modern technology, we have been able to obtain many techniques and consequently generated huge amounts and type of data. This amount of new and variety in astronomical data along with the complexities presents itself as a affair that a human analysis is not possible. In our project, we use deep learning techniques to explore the various challenges faced by astronomers when processing huge amounts of data, looking for information relevant to each target. We have implemented existing methods like InceptionV3 and CNN to detect and classify galaxies. Then we proposed to use VGG16, VGG19, and MobileNetV2 for classification and image segmentation to detect and classify galaxies. And we compared the performance of existing and proposed methods. Our proposal was approximately 20% more accurate than existing methods CNN and InceptionV3.


Prediction of Parkinson's disease with various ML and DL techniques on speech data
T Shankar, Gummadapu Sreelekha, Challa Sai Tejaswini, P Sivasankar, N Lavanya, and J Murali
IEEE
Parkinson’s disease(PD) is a degenerative peripheral nervous system syndrome that influences muscle movement. It is incurable. Parkinson’s disease impacts more than one million people in India each year. Because of the disease’s degenerative nature, symptoms usually appear gradually and are barely perceptible, ranging from ordinary trembling of the hand to apparent speech, and voice, as well as writing alterations to serious symptoms such as loss of automatic movements. This research aims to contribute to the improvement of medical technology by assisting in the advanced and premature identification of PD, permitting experimental therapy by the use of a voice dataset from UCI Machine Learning(ML) database. We reviewed the current state of PD discernment in this study and discussed the prototype for quick identification of PD using several classifier propositions of ML and Deep Learning(DL). The best accuracy of about 94.8% was achieved by the usage of the CNN model with optimizer. We have also further built a web-based GUI for the web-based prediction of PD using model build.


Design of high sensitive hybrid honeycomb photonic crystal fiber for sensing C<inf>8</inf>H<inf>8</inf>O<inf>3</inf>/AsCl<inf>3</inf>/C<inf>8</inf>H<inf>10</inf> analyte
Shankar Thangavelu, A. Rajesh, Sivasankar Perumal, Sai Sravan, and Chandini Mani
Springer Science and Business Media LLC



Unmanned aerial vehicle localization for device-to-device communication in fifth generation networks using modified penguin search optimization
Shankar Thangavelu, Rajesh Anbazhagan, Sivasankar Perumal, Eeswar Gopikrishna, and Muppalla Siddartha
Elsevier BV



AI based DDOS Attack Detection of SDN Network in Mininet Emulator
Aditya Raj Yadav, Anant P Jain, Shankar T, A. Rajesh, Sivasankar Perumal, and Geoffrey Eappen
IEEE
Software Defined Networking (SDN) is a network architecture of controlling the network devices through software applications. With SDN the network control can be achieve remotely without affecting network devices and reducing expenses of deploying infrastructure. Mininet SDN emulator and controllers provide a lightweight virtual platform for simulating network devices. Mininet emulator and Pox controller based on Transmission Control Protocol (TCP), Iperf3 and Hping3 can be use in testing scenarios which will depend upon throttling bandwidth to evaluate the performance of the emulator and controller by monitoring the throughput. Although having advantage of controlling the network, SDN exposes the network to vulnerable attacks which can be worse than traditional networks. Through this project we want to study the Artificial Intelligence (AI) Distributed Denial of Service (DDoS) attack on SDN network and explore a possible solution to prevent DDoS attacks using Machine Learning (ML). DDoS attack is type of DoS attack which make use of numerous distributed attack sources. Since every network in the system has an entropy and increase in the randomness causes entropy to decrease, we can use this concept to create ML classifiers to interpret the attack.


Vulnerabilities Detection in Cybersecurity Using Deep Learning–Based Information Security and Event Management
D Kothandaraman, S Shiva Prasad, and P Sivasankar
Chapman and Hall/CRC



A Novel Technique to Improve Latency and Response Time of AI Models using Serverless Infrastructure
Bhanu Sankar Ravi, Chepuri Madhukanthi, P Sivasankar, and John Deva Prasanna
IEEE
Response time for AI-based models in time-critical applications is always a matter of concern. The situation is challenging when the model is deployed in a cloud-based infrastructure. To address this issue, a cloud-native development methodology called serverless infrastructure enables developers to create and execute applications without having to worry about managing servers. Generally, traditional systems require manual scaling, constant maintenance, and dedicated hardware resulting in high costs. To solve this, the AI model is deployed in serverless infrastructure services for hosting APIs that is to identify marine animals which have the potential to attack human beings at the seashores. The serverless infrastructure suffers from an initializing delay called cold start for occasional requests and hence the response time will be delayed even if the lambda function is free. The problem of cold starts is mitigated using the scheduler in the lambda function. The scheduler sends dummy requests to the server to keep the server warm and active. The AI model used as a test case utilizes Convolutional Neural Network Algorithms and Transfer Learning Technique, for detecting predators near the seashore. The model is deployed in a serverless infrastructure and has the benefits of automatic scaling, pay-per-use pricing, and decreased operational costs. The AI model is implemented in both serverless infrastructure and in Elastic Cloud Compute EC2. The performance of both systems was done for cost, latency, and response time. The proposed system provides promising results when compared to traditional server systems.


A Battery Monitoring System based on IoT for Electric Vehicles
P Sasirekha, E Sneka, B Velmurugan, M Sahul Hameed, and P Sivasankar
IEEE
Electric vehicles (EVs), which are considered as dynamic electrical energy storage units, are widely used because of their outstanding electrical characteristics and versatility. However, their widespread adoption has a significant adverse effect on the grid and carries the risk of harming their batteries when they become profoundly discharged. EV batteries require a precise state of charge estimation to minimize the lisk of damage, prolong their lifespan, and in order to safeguard the equipment power. Based on simplicity of implementation and reduced overall complexity, this study suggests a real-time Battery Monitoring System (BMS) employing the coulomb method of counting for SOC estimation and MQTT which is messaging-based as an internal communication protocol. Utilizing an ade quate central CPU, interfacing devices, and sensor technology, the proposed BMS is implemented. In order to monitor and regulate the discharging and charging of rechargeable battery packs, which increases the operational efficiency, battery management systems are important in electric vehide technology. Monitoring involves keeping a close eye on the important operating factors including voltage, current, fire, and temperature while charging and draining a battery. This is a hardware-timed sensor system that tracks various variables, like temperature, voltage, and fire and reports them on IOT so you can see exactly when everything has reached the right value.


CDS-Based Routing in MANET Using Q Learning with Extended Episodic Length
D. S. John Deva Prasanna, D. John Aravindhar, and P. Sivasankar
Springer Singapore



Block Chain based Grey Hole Detection Q Learning based CDS Environment in Cloud - MANET
D.S. John Deva Prasanna, Dr.D. John Aravindhar, and Dr.P. Sivasankar
NeuroQuantology Journal
Cloud MANET is a latest technique in which individual smart devices joins the Cloud MANET and can communicate in a distributed fashion. This is advantageous, as the Smart device does not need any infrastructural establishments. These nodes communicate together. Several MANETS formed in manner can be connected to cloud and can avail cloud services in real time. In this paper we attempt to establish a virtual backbone of Cloud MANET nodes using the concept Connected Dominating Sets, we also introduced a lightweight security scheme in order to avoid blackhole and greyhole attacks. The algorithm uses Q learning technique for learning about the capacity of nodes and establishes the CDS in Cloud MANET. The entire set up is established with public key infrastructure to emulate block chain based security. The concept of smart contract is used to ensure that every transaction is recorded and any compromised nodes in the CDS is discovered and eliminated.


3-Axis Robot Arm Using Micro-Stepping with Closed-Loop Control
G. A. Rathy, P. Sivasankar, Aravind Balaji, and K. Gunasekaran
Springer Singapore
Robot arm is one of the most buzzing words in industrial automation. The challenge of designing a robot arm is anticipating and controlling its system dynamics. This paper focuses on developing of robot arm with 3 degrees of freedom (DoF) with high speed and precision. The position of the robotic arm is determined from the accelerometer using closed-loop feedback system. The stepper motor in the arm of the robot decides the direction; the desired movements will be controlled by PWM pulses through the controller, as per the requirement of the user. A4988 stepper motor driver is used instead of rotary encoder to control the movements of robotic arm by stepper motor. The step angle of the arm is controlled by micro-stepping using 200 steps to 3200 steps resolution which provides a smooth movement and precision degree of accuracy. A graphical user interface is designed using LabVIEW to display and control the position of arm. Finally, 3-axis robot arm with micro-stepping is developed by integrating the electronic circuitry and mechanical parts.


Hybrid PSO-HSA and PSO-GA algorithm for 3D path planning in autonomous UAVs
B. Abhishek, S. Ranjit, T. Shankar, Geoffrey Eappen, P. Sivasankar, and A. Rajesh
Springer Science and Business Media LLC
Unmanned aerial vehicles (UAVs) are a quintessential example of automation in the field of avionics. UAVs provide a platform for performing a wide variety of tasks, but in each case the concept of path planning plays an integral role. It helps to generate a pathway free of obstacles, having minimum length leading to lesser fuel consumption, lesser traversal time and helps in steering the aircraft and its corresponding antenna power signature safely around the hostile antenna to avoid detection. To optimize path planning to incorporate all the above-mentioned constraints, this paper presents two new hybrid algorithms particle swarm optimization (PSO) with harmony search algorithm and PSO with genetic algorithm. The hybrid algorithms perform both an exploratory and exploitative search, unlike the existing algorithms which are biased, towards either an exploitative search or an exploratory search. Furthermore, the hybrid algorithms are compared to the existing optimization algorithms and in all cases the hybrid algorithms give a minimum of 7% better result against PSO with up to a 40% better result against Invasive Weed optimization algorithm for a fixed computational time, suggesting better real-time applications.


Developing a knowledge structure using Outcome based Education in Power Electronics Engineering
Rathy G.A., Sivasankar P, and Gnanasambandhan T.G.
Elsevier BV
Abstract Outcome based education (OBE) is student-centered instruction model that stresses on judging student performance through outcomes. Outcomes include knowledge, skills and behavior. Outcome-Based Education model is being adopted at a fast pace at Technical institutions all over the world. It is considered as a massive leap forward to convalesce technical education and help Engineers compete with their global counterparts. OBE gives more weightage on what the students will be able to ‘do instead of what they will ‘know’. Hence it is important to develop the instructional model to improve knowledge, skill, behaviour of the students. Knowledge structure is the micro level component and the part of the course outcome which will enable the student to gain the confidence of ‘doing’ instead of ‘knowing’. This paper proposes an Instructional Model by developing a knowledge structure in Power Electronics Engineering.


Reinforcement learning based virtual backbone construction in manet using connected dominating sets
D. Prasanna, D. Aravindhar, P. Sivasankar and Karthickeyan Perumal
SynthesisHub Advance Scientific Research
Construction of virtual backbones in MANETs for establishing the routes using Connected Dominating Set (CDS), is an prominent area of research in wireless networks. In addition, Reinforcement Learning (RL) is becoming popular due to its effective exploration process. MANET routing is highly challenging, as the network topology is highly dynamic. The broadcast of route request packet creates broadcast storm due to multiple retransmission of the packet. Due to the constant movement of the nodes, routing decisions are harder to resolve. Hence, this paper proposes an efficient routing technique in MANET using Graph Connected Dominating Sets and Reinforcement Learning. The Q Learning algorithm is used to measure and find the best nodes for constructing the CDS. Link stability and residual energy are the parameters used for estimating the reward values. The algorithm is implemented in NS2 and results are found to be promising and improve the performance of the network.


Treatment of Textile Wastewater by Coagulation–Flocculation Process Using Gossypium herbaceum and Polyaniline Coagulants
Prakasam Arulmathi, Chellappa Jeyaprabha, Periandavan Sivasankar, and Vadivel Rajkumar
Wiley



Context-aware energy conserving routing algorithm for internet of things
Kothandaraman D, Chellappan C, Sivasankar P, and Syed Nawaz Pasha
Academy and Industry Research Collaboration Center (AIRCC)
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smartphones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR.


Successful computer forensics analysis on the cyber attack botnet
Kavisankar Leelasankar, Chellappan C., and Sivasankar P.
IGI Global
The success of computer forensics lies in the complete analysis of the evidence that is available. This is done by not only analyzing the evidence which is available but also searching for new concrete evidence. The evidence is obtained through the logs of the data during the cyberattack. When performing analysis of the cyberattack especially the botnet attacks, there are many challenges. First and the foremost is that it hides the identity of the mastermind, the botmaster. It issues the command to be executed using its subordinate, the command and control (C&amp;C). The traceback of C&amp;C itself is a complex task. Secondly, it victimizes the innocent compromised device zombies. This chapter discusses the analysis done in both proactive and reactive ways to resolve these challenges. The chapter ends by discussing the analysis to find the real mastermind to protect the innocent compromised system and to protect the victim system/organization affected by the botnet cyberattack.


Enhanced efficient SYN spoofing detection and mitigation scheme for DDoS attacks
L. Kavisankar, C. Chellappan, S. Venkatesan, and P. Sivasankar
Inderscience Publishers



Efficient SYN spoofing detection and mitigation scheme for ddos attack
L. Kavisankar, C. Chellappan, S. Venkatesan, and P. Sivasankar
IEEE
Protection of critical server from cyber attacks is vital, especially in the case of active attacks like Distributed Denial of Service (DDoS). Seamless services are provided by the constant availability of the server which plays an important factor in providing the customer good Quality of Service (QoS). Monitoring and rate limiting the flow of packets will protect the victim systems by allowing only trusted users during the DDoS attack. The job of the security professionals becomes complex, when the attacks are launched from trusted IP addresses, using Synchronization (SYN) spoofing. The work presented in this paper is experimented with Efficient Spoofed Mitigation Scheme (ESMS) which uses the TCP probing method along with the bloom filter trust model. The proposed scheme provides accurate and robust information for the detection and controlling of the spoofed packets, during the DDoS attacks.


Hybrid approach for optimal cluster head selection in wsn using leach and monkey search algorithms




Ppssm:push/pull smooth video streaming multicast protocol design and implementation for an overlay network
T. Ruso, C. Chellappan, and P. Sivasankar
Springer Science and Business Media LLC
IP multicast is one of the best techniques for video streaming on the Internet. It faces issues with respect to address allocation, routing, authorization, group management, security, and scalability. By default, local Internet Service Providers did not enable IP multicast services, because of the cost incurred in using multicast-enabled routers. To solve these issues some of the IP layer functionalities have been shifted to the Application Layer, thus leading to Application Layer Multicast (ALM) protocols. However, ALM protocols face issues related to synchronous data delivery, scalability, link stress, link stretch and node failures. Some of the existing protocols are CoolStreaming, and mTreebone. A novel ALM protocol based Push/Pull Smooth video Streaming Multicast (PPSSM) protocol is proposed in this paper, to increase the throughput and reduce the packet loss rate. The PPSSM protocol involves three stages, such as tree-mesh construction, dynamic buffer management and network coding techniques. In the tree-mesh construction, a tree consists of stable nodes and a mesh consists of unstable nodes. The proposed PPSSM optimizes the stable nodes in the tree, which minimizes or eliminates the pull operations from the unstable mesh overlay nodes, by exploring the potential of the stable nodes. Dynamic buffer management is achieved by setting the optimal buffer threshold value, using the optimization of the sensitivity parameters, such as packet loss and packet workload/delay by the Infinitesimal Perturbation Analysis and Stochastic Approximation algorithms. In addition to the tree-mesh construction and buffer management, the introduction of the network coding technique will enhance the throughput and minimize the packet loss and delay. Finally, the performance of the proposed PPSSM protocol is compared with those of CoolStreaming, and mTreebone, and it shows improvement in respect of throughput, packet loss, and average decoding time.


A pioneer scheme in the detection and defense of DrDoS attack involving spoofed flooding packets
L. Kavisankar, C. Chellappan, P. Sivasankar, A. Karthi and A. Srinivas
Korean Society for Internet Information (KSII)
DDoS (Distributed Denial of Service) has been a continuous threat to the cyber world with the growth in cyber technology. This technical evolution has given rise to a number of ultra-sophisticated ways for the attackers to perform their DDoS attack. In general, the attackers who generate the denial of service, use the vulnerabilities of the TCP. Some of the vulnerabilities like SYN (synchronization) flooding, and IP spoofing are used by the attacker to create these Distributed Reflected Denial of Service (DrDoS) attacks. An attacker, with the assistance of IP spoofing creates a number of attack packets, which reflects the flooded packets to an attacker’s intended victim system, known as the primary target. The proposed scheme, Efficient Spoofed Flooding Defense (ESFD) provides two level checks which, consist of probing and non-repudiation, before allocating a service to the clients. The probing is used to determine the availability of the requested client. Non-repudiation is taken care of by the timestamp enabled in the packet, which is our major contribution. The real time experimental results showed the efficiency of our proposed ESFD scheme, by increasing the performance of the CPU up to 40%, the memory up to 52% and the network bandwidth up to 67%. This proves the fact that the proposed ESFD scheme is fast and efficient, negating the impact on the network, victim and primary target.


Performance evaluation of energy efficient on-demand routing algorithms for MANET
P. Sivasankar, C. Chellappan, and S. Balaji
IEEE
Mobile ad hoc networks are a class of dynamic networks without any centralized administration. A major bottleneck in mobile ad hoc networks (MANETs) is the energy consumption since nodes are usually mobile and battery operated. To maximize the lifetime of mobile ad hoc networks (i.e., the lifetime of the nodes themselves) the power depletion of network must be evenly distributed, i.e., there must be a uniform drain of energy from the nodes, and the overall transmission power requirement for each connection request must be minimized. This paper proposes two algorithms called energy efficient delay time routing (EEDTR) and maximised energy efficient routing (MEER), which try to increase the operational lifetime of mobile ad hoc networks. These algorithms are modified versions of the existing dynamic source routing (DSR) algorithm. These algorithms select fully distributed routes, thus balancing power consumption of the entire network. The first algorithm(EEDTR) introduces a delay in forwarding the packets by nodes, which is inversely proportional to the remaining energy level of the node. The second algorithm includes energy information on the route request packet and select the routes based on this information (MEER). These algorithms are designed and implemented using global mobile simulator (GloMoSim), a scalable, simulation environment for network simulation. Based on the results obtained, this paper concludes that the proposed algorithms increase the lifetime of mobile ad hoc networks, at the expense of end to end delay and control overhead.


Cache based energy efficient strategies in mobile ad hoc networks

RECENT SCHOLAR PUBLICATIONS

Detecting pattern irregularities in astronomical images using deep learning
T Shankar, B Deekshitha, V Rohini, VM Nakarajan, P Sivasankar, J Murali
2024 3rd International Conference on Artificial Intelligence For Internet of 2024



Prediction of Parkinson’s disease with various ML and DL techniques on speech data
T Shankar, G Sreelekha, CS Tejaswini, P Sivasankar, N Lavanya, J Murali
2024 3rd International Conference on Artificial Intelligence For Internet of 2024



A Novel Technique to Improve Latency and Response Time of AI Models using Serverless Infrastructure
BS Ravi, C Madhukanthi, P Sivasankar, JD Prasanna
2023 International Conference on Inventive Computation Technologies (ICICT 2023



A Battery Monitoring System based on IoT for Electric Vehicles
P Sasirekha, E Sneka, B Velmurugan, MS Hameed, P Sivasankar
2023 5th International Conference on Smart Systems and Inventive Technology 2023



Vulnerabilities detection in cybersecurity using deep learning–based information security and event management
D Kothandaraman, SS Prasad, P Sivasankar
Artificial intelligence and deep learning for computer network, 81-98 2023



CDS-Based Routing in MANET Using Q Learning with Extended Episodic Length
DS John Deva Prasanna, D John Aravindhar, P Sivasankar
Inventive Computation and Information Technologies: Proceedings of ICICIT 2021



Block Chain based Grey Hole Detection Q Learning based CDS Environment in Cloud-MANET.
DSJD Prasanna, DJ Aravindhar, P Sivasankar
Webology 18 (SI01), 88-106 2021



Successful Computer Forensics Analysis on the Cyber Attack Botnet
K Leelasankar, C Chellappan, P Sivasankar
Research Anthology on Combating Denial-of-Service Attacks, 151-166 2021



An efficient IoT based biomedical health monitoring and diagnosing system using myRIO
GA Rathy, P Sivasankar, ZF Tamara
TELKOMNIKA (Telecommunication Computing Electronics and Control) 18 (6 2020



Hybrid PSO-HSA and PSO-GA algorithm for 3D path planning in autonomous UAVs
B Abhishek, S Ranjit, T Shankar, G Eappen, P Sivasankar, A Rajesh
SN Applied Sciences 2, 1-16 2020



IoT Based Smart Controlled Inverter
SP GA Rathy , Gunasekaran K, Karthekeyan Perumal
International Journal of Computer Trends and Technology 68 (4) 2020



Reinforcement Learning Based Virtual Backbone Construction in MANET using Connected Dominating Sets
Sivasankar. P, John Deva Prasanna. D. S, John Aravindhar, Karthikeyan Perumal
Journal of Critical Reviews 7 (9), 146-152 2020



Estimation of SoC using SVM regression technique for an Efficient Electric Vehicle Battery Management System using c-RIO DAQ
GK P.Sivasankar, G.A.Rathy, Karthikeyan Perumal
American Journal of Research, 89-103 2020



A Study on Charging Infrastructure and the Topologies of Fast Charging Techniques in Electric Vehicle
GAR P.Sivasankar
International Journal of Engineering Applied Sciences and Technology 5 (2 2020



Developing a knowledge structure using Outcome based Education in Power Electronics Engineering
GA Rathy, P Sivasankar, TG Gnanasambandhan
Elsevier Procedia Computer Science 172, 1026-1032 2020



3-Axis Robot Arm Using Micro-Stepping with Closed-Loop Control
GA Rathy, P Sivasankar, A Balaji, K Gunasekaran
International Conference on Advanced Communication and Computational 2019



Context-aware energy conserving routing algorithm for internet of things
D Kothandaraman, C Chellappan, P Sivasankar, SN Pasha
International Journal of Computer Networks & Communications (IJCNC) Vol 11 2019



3 axis robot arm using micro-stepping with closed loop control
P Sivasankar, GA Rathy, AB Gunasekaran.K
ICACCT 2019 2019



IoT based Classroom Automation using Zigbee
GA Rathy, P and Sivasankar
International Journal of Innovative Science, Engineering & Technology 6 (3) 2019



NG Smartphone Users Activity and Direction Detection using MQTT in IoT
Y Kothandaraman, D, P.Sivasankar, and Nagendar
2019

MOST CITED SCHOLAR PUBLICATIONS

Hybrid PSO-HSA and PSO-GA algorithm for 3D path planning in autonomous UAVs
B Abhishek, S Ranjit, T Shankar, G Eappen, P Sivasankar, A Rajesh
SN Applied Sciences 2, 1-16 2020
Citations: 71



Developing a knowledge structure using Outcome based Education in Power Electronics Engineering
GA Rathy, P Sivasankar, TG Gnanasambandhan
Elsevier Procedia Computer Science 172, 1026-1032 2020
Citations: 23



Performance evaluation of energy efficient on-demand routing algorithms for MANET
P Sivasankar, C Chellappan, S Balaji
2008 IEEE Region 10 and the Third international Conference on Industrial and 2008
Citations: 19



An efficient IoT based biomedical health monitoring and diagnosing system using myRIO
GA Rathy, P Sivasankar, ZF Tamara
TELKOMNIKA (Telecommunication Computing Electronics and Control) 18 (6 2020
Citations: 16



Hybrid approach for optimal cluster head selection in WSN using leach and monkey search algorithms
T Shankar, A Karthikeyan, P Sivasankar, A Rajesh
Journal of Engineering Science and Technology 12 (2), 506-517 2017
Citations: 15



Performance evaluation of energy efficient routing protocols for MANET
P Sivasankar, C Chellappan, S Balaji
International Journal of Computer Applications 975, 8887 2011
Citations: 15



Context-aware energy conserving routing algorithm for internet of things
D Kothandaraman, C Chellappan, P Sivasankar, SN Pasha
International Journal of Computer Networks & Communications (IJCNC) Vol 11 2019
Citations: 13



Efficient syn spoofing detection and mitigation scheme for ddos attack
L Kavisankar, C Chellappan, S Venkatesan, P Sivasankar
2017 second international conference on recent trends and challenges in 2017
Citations: 12



Implementation of Smart Sleep Mechanism and Hybrid Data Collection Technique for Maximizing Network Lifetime in WSN's
T Shankar, A Karthikeyan, P Sivasankar, RR Neha
Indian Journal of Science and Technology 8, 1 2015
Citations: 10



Cache based energy efficient strategies in mobile ad hoc networks
K Murugan, S Balaji, P Sivasankar, S Shanmugavel
2005 IEEE International Conference on Personal Wireless Communications, 2005 2005
Citations: 9



A Battery Monitoring System based on IoT for Electric Vehicles
P Sasirekha, E Sneka, B Velmurugan, MS Hameed, P Sivasankar
2023 5th International Conference on Smart Systems and Inventive Technology 2023
Citations: 8



IOT based traffic monitoring using raspberry Pi
P Sivasankar, B Brindhavathy
Int. J. Res. Eng. Sci. Technol.(IJRESTs) 1 (7) 2016
Citations: 6



Block Chain based Grey Hole Detection Q Learning based CDS Environment in Cloud-MANET.
DSJD Prasanna, DJ Aravindhar, P Sivasankar
Webology 18 (SI01), 88-106 2021
Citations: 5



A Study on Charging Infrastructure and the Topologies of Fast Charging Techniques in Electric Vehicle
GAR P.Sivasankar
International Journal of Engineering Applied Sciences and Technology 5 (2 2020
Citations: 5



3-Axis Robot Arm Using Micro-Stepping with Closed-Loop Control
GA Rathy, P Sivasankar, A Balaji, K Gunasekaran
International Conference on Advanced Communication and Computational 2019
Citations: 5



Ppssm: push/pull smooth video streaming multicast protocol design and implementation for an overlay network
T Ruso, C Chellappan, P Sivasankar
Multimedia Tools and Applications 75, 17097-17119 2016
Citations: 5



A pioneer scheme in the detection and defense of DrDoS attack involving spoofed flooding packets
L Kavisankar, C Chellappan, P Sivasankar, A Karthi, A Srinivas
KSII Transactions on Internet and Information Systems (TIIS) 8 (5), 1726-1743 2014
Citations: 5



Reinforcement Learning Based Virtual Backbone Construction in MANET using Connected Dominating Sets
Sivasankar. P, John Deva Prasanna. D. S, John Aravindhar, Karthikeyan Perumal
Journal of Critical Reviews 7 (9), 146-152 2020
Citations: 4



Optimized energy efficient routing protocols and their performance comparison for MANET
P Sivasankar, C Chellappan, S Balaji
Eur. J. Sci. Res 90 (1), 136-148 2012
Citations: 4



Vulnerabilities detection in cybersecurity using deep learning–based information security and event management
D Kothandaraman, SS Prasad, P Sivasankar
Artificial intelligence and deep learning for computer network, 81-98 2023
Citations: 3

Publications

Books Published : 2 , Title of the Book : LabVIEW Programming Concepts with Examples, Authors : P.Sivasankar, G.A.Rathy, Publisher: Sci Tech publications, Year : 2015
Title of the Book : NG Smartphone Users Activity and Direction Detection using MQTT in IoT, Authors : Kothandaraman, D, P.Sivasankar, and Nagendar, Y Publisher: LAMBERT Academic Publishing, Year : 2019