Fault detection in Induction motor using WPT and Multiple SVM

Aravindh Kumar.B,Saranya G,Selvakumar R,Swetha Shree R,Saranya M,Sumesh.E.P 보안공학연구지원센터 2010 International Journal of Control and Automation Vol.3 No.2

Dynamic Data Replication and Scheduling Using Fuzzy-CSO Algorithm for IoT-Clouds

Saranya M.,Ramesh R. 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.5

Data replication and task scheduling are two strategies to enhance the performance of data-intensive applications. One of the main issues in the Internet of Things (IoT)-Cloud scenario is uploading data from the sensor gateways and replicating it across multiple cloud data centres (DCs) for high availability. To avoid such problems, there is a need to adaptively determine the number of replicas and their optimum locations. Although data replication ensures availability and reliability, keeping many copies of each data will increase storage space use. To overcome this problem, a minimal number of replicas need to be maintained for these files. Most of the existing works consider the system as non-faulty, but in real-time, various faults may occur at every data centre (DC). Hence, the main objectives of this research work are to adaptively determine the number of replicas and their optimum locations, as well as to design a fault-tolerant scheduling algorithm for IoT-based Cloud. This paper deals with the design of dynamic data replication and scheduling framework using the Hybrid Fuzzy-CSO algorithm for the IoT-Cloud. It uses the Cat Swarm Optimization (CSO) algorithm to find the optimal locations for replications. The fitness function is derived from the distance between the main DC and the other DCs. A Fuzzy logic decision model was designed to determine the optimal number of replicas. During task scheduling, data replication was performed in the selected replication points and scheduled accordingly. The experimental results have indicated that the proposed Fuzzy-CSO framework attains minimum data transfer time, minimum response delay, and higher bandwidth utilization than the existing algorithms.

A Study on the Public Auditing Mechanisms for Privacy Preserving and Maintaining Data Integrity in Cloud Computing

V.Saranya,R.G. Suresh Kumar,T. Nalini 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.6

Cloud computing in its various forms allows users to store their information at remote location and reduce the burden at their local systems. Even though this is an advantage for users but there are also many drawbacks because of this remote storage. The main drawback which needs to be dealt with is security. Recently, security is the major concern which most of the cloud service providers are facing. The users store their information in remote location with the hope of maintaining the privacy and integrity of data. In order, to maintain the privacy and integrity of users’ data auditing has to be done by the Cloud Service Providers (CSP). CSP uses the Third Party Auditor (TPA) for performing the auditing. The TPA performs auditing on behalf of the data owner using different auditing mechanisms. Many auditing mechanisms have been introduced in literature. Each mechanism varies from one another in one or more characteristics. In this paper we have provided a study on the different auditing mechanisms required to preserve the privacy and integrity of data in cloud. We have presented the advantages and flaws in each mechanism compared to another. Many auditing mechanisms are arising in literature with the aim to maintain the integrity of users’ data and preserve the privacy. This paper remains as the basis for different auditing mechanisms that are arising in literature. With the help of auditing mechanisms the TPA can best satisfy the needs of the users.

Efficient and Parallel Data Processing and Resource Allocation in the Cloud by using Nephele’s Data Processing Framework

V.Saranya,S.Ramya,R.G. Suresh Kumar,T.Nalini 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.3

Cloud computing is a technology in which the Cloud Service Providers (CSP) provide many virtual servers to the users to store their information in the cloud. The faults occurring on the assignment and dismission of the virtual machines, the processing cost in the allocation of resources must also be considered. The parallel processing of the information on the virtual machines must be done effectively and in an efficient manner. A variety of systems were developed to facilitate Many Task Computing (MTC). These systems aim to hide the issues of parallelism and fault tolerant and they are used in many applications. In this paper, we introduced Nephele, a data processing framework to exploit dynamic resource provisioning offered by IaaS clouds. The performance evaluation of the virtual machines has been evaluated and the allocation and de-allocation of job tasks to the specific virtual machines has also been considered. A performance comparison with the well known data processing framework hadoop has been done. Thus this paper tells about the effective and efficient manner of processing the data by parallel processing and allocating the correct resources for the desired task. It also helps to reduce the cost of resource utilization by exploiting the dynamic resource utilization.

Predicting the habitat suitability of Dipterocarpus indicus: an endemic and endangered species in the Western Ghats, India

Kritika Malik,K. R. L. Saranya,C. Sudhakar Reddy,A. O. Varghese 대한공간정보학회 2022 Spatial Information Research Vol.30 No.6

Species distribution models provide habitat mapping tools and produce scalable information to inform policy decisions. Integrating spatial statistical modelling with bioclimatic information identifies the contribution of the most critical variable in species occurrence and distribution. In the present study a suitable bioclimatic model, MaxEnt modelling algorithm is used for Dipterocarpus indicus, an endemic and endangered species by incorporating field inventory data.This model predicted a high probability of potential distribution area in the forests of Uttara Kannada, Chikmagalur, Shivamogga and Kannur. The highly suitable hábitats are distributed in protected áreas, namely Kudremukh, Mookambika, Pushpagiri, Sharavathi Valley, Shettihalli, Someshwara, Parambikulam, Peechi-Vazhani, Shendurney, Thattekadu Bird, Indira Gandhi (Anamalai), Kalakad, Mundanthurai and Kanyakumari. The Area Under Curve value for the potential distribution of species is observed at 0.894 for training data. The highest fractional predicted area was in the low elevation tropical wet evergreen forest region between 50 and 700 m. The contributions of the climatic variables in the model showed that precipitation in the coldest quarter was the most influential, followed by annual mean temperature and annual precipitation. This study aids in long-term conservation planning, monitoring, and managing potential habitats of endemic and endangered tree species.

Harnessing essential biodiversity variables and remote sensing of earth observations - synthesizing biodiversity insights

Reddy C. Sudhakar,Satish K. V.,Saranya K. R.L.,Sri Surya N. Nitish,Neha P. A.,Rajashekar G. 대한공간정보학회 2024 Spatial Information Research Vol.32 No.3

There are major gaps remaining in understanding of species distribution and how relationships between biodiversity, environment and scales change over space and time. This review explores the significance, challenges, future directions, and the potential contribution of Earth Observations based Essential Biodiversity Variables (EBVs) to enhance our understanding of biodiversity. Integrating EBVs with Remote Sensing of Earth Observations (RS-EO) is found to be an effective approach to quantify and monitor changes in biodiversity over space and time. Species serves as the fundamental taxonomic units of biodiversity and are the focal points of conservation policies. Prioritizing the utilization of species-level metrics and their seamless integration into the EBV framework is crucial. The current study has contributed 11 potential EBVs to the existing knowledge base. Integrating multiple data sources and methodologies is essential for overcoming the constraints and obtaining a more comprehensive understanding of biodiversity patterns. This synergy offers a holistic approach for monitoring, assessing, and managing biodiversity, to contribute significantly to global conservation efforts and sustainable development goals.

Analytical Modeling and Simulation of Dual Material Gate Tunnel Field Effect Transistors

Samuel, T.S.Arun,Balamurugan, N.B.,Sibitha, S.,Saranya, R.,Vanisri, D. The Korean Institute of Electrical Engineers 2013 Journal of Electrical Engineering & Technology Vol.8 No.6

In this paper, a new two dimensional (2D) analytical model of a Dual Material Gate tunnel field effect transistor (DMG TFET) is presented. The parabolic approximation technique is used to solve the 2-D Poisson equation with suitable boundary conditions. The simple and accurate analytical expressions for surface potential and electric field are derived. The electric field distribution can be used to calculate the tunneling generation rate and numerically extract tunneling current. The results show a significant improvement of on-current and reduction in short channel effects. Effectiveness of the proposed method has been confirmed by comparing the analytical results with the TCAD simulation results.

Analytical Modeling and Simulation of Dual Material Gate Tunnel Field Effect Transistors

T.S.Arun Samuel,N.B.Balamurugan,S.Sibitha,R.Saranya,D.Vanisri 대한전기학회 2013 Journal of Electrical Engineering & Technology Vol.8 No.6

In this paper, a new two dimensional (2D) analytical model of a Dual Material Gate tunnel field effect transistor (DMG TFET) is presented. The parabolic approximation technique is used to solve the 2-D Poisson equation with suitable boundary conditions. The simple and accurate analytical expressions for surface potential and electric field are derived. The electric field distribution can be used to calculate the tunneling generation rate and numerically extract tunneling current. The results show a significant improvement of on-current and reduction in short channel effects. Effectiveness of the proposed method has been confirmed by comparing the analytical results with the TCAD simulation results.