IJSRET Volume 3 Issue 6, November-2017

Archive Volume 3 Issue 6

An Approach for Trusted Computing of Load Balancing in Cloud Environment

Authors: Manoj Kumar Selkare, Vimal Shukla

Abstract: Cloud computing is a novel approach in order to use the resource of computing where these resources may be hardware or software. This facility is delivered as a service in the communication network. This facility known as cloud, which occurred from the use of a service as a cloud, which is an abstraction for the complex infrastructure system containing diagrams. Services of cloud computing involve trusted remote user data, and computer software. This paper proposed to an approach to efficient load balancing in cloud computing

Low Power Three Input XOR Gate For Arithmetic And Logical Operation

Authors:Ms. Poojashree Sahu, Mr. Ashish Raghuwanshi

Abstract: With advancement of microelectronics technology scaling, the main objective of design i.e. low power consumption can be easily acquired. For any digital logic design the power consumption depends on; Supply voltage, number of transistors incorporated in circuit and scaling ratios of the same. As CMOS technology supports inversion logic designs; NAND & NOR structures are useful for converting any logic equation into physical level design that comprises of PMOS and NMOS transistors. In similar way, logic can be implemented in other styles as well, with the difference in number of transistors required. The conventional CMOS design for three input XOR logic can be possible with 10 or more than 10 transistors, with the methodology discussed in this paper, the same design for three inputs XOR logic can be made possible with 16 transistors. The proposed methodology consists of transmission gate and systematic cell design methodology (SCDM). This design consumes 45% (35%) less power dissipation than that of conventional LPHS-FA and SCDM based XO10 XOR logic design with CMOS technology. Since the design for XOR logic, is useful for variety of applications such as Data encryption, Arithmetic circuits, Binary to Gray encoding etc. the XOR logic has been selected for design. The design explained in this paper is simulated with 130nm technology.

Low Read Power Delay Product Based Differential Eight Transistor SRAM cell
Authors: Ms. Jaya Sahu,Mr. Ashish Raghuwanshi

Abstract: SRAM is designed to provide an temporary storage for Central Processing Unit and replace Dynamic systems that require very low power consumption. Low power SRAM design is critical aspect since it takes a large fraction of total power and die area in high performance processors. This paper include the work on eight transistor SRAM cell that of smaller read power delay product due to cascading of pull offers 28% (74%) smaller read ‘0’ (‘1’) than exiting 7T. The SRAM cell read and cycle is characterized at 45nm technology using SPICE EDA tool.

A Robust Classification Algorithm for Multiple Type of Dataset

Authors:M.Tech. Scholar Afshan Idrees, Prof. Avinash Sharma

Abstract: With the increase in different internet services number of users are also increasing. Although while taking service user may be on risk for sharing data. So this work focus on increasing the security of the user data while taking classification service. Here algorithm provide robustness by encrypting the data and send to server, while server classify the data in encrypted form. One more security issue is that instead of transferring whole encrypted data, features are extract from the data first then encrypt and send to server for classification. Here proposed work successfully classify all type of user data in form of text, image, numeric.

An Unsupervised TLBO Based Drought Prediction By Utilizing Various Features

Authors:M.Tech. Scholar Shikha Ranjan Patel, Prof. Priyanka Verma

Abstract: Agricultural vulnerability is generally referred to as the degree to which agricultural systems are likely to experience harm due to a stress. In this work, an existing analytical method to quantify vulnerability was adopted to assess the magnitude as well as the spatial pattern of agricultural vulnerability to varying drought conditions. Based on the standardized precipitation index (SPI) was used as a measure of drought severity. A number of features including normalized difference vegetation index (NDVI), vegetation condition index (VCI), and SPI will be use for classification. Here proposed modal use Teacher Learning Based Optimization genetic approach for classify the different location present in geospatial dataset. By use of  this TLBO approach prior knowledge is not required. Experiment results shows that proposed work is better as compare to previous work.

Optimizing Material Management through Advanced System Integration, Control Bus, and Scalable Architecture
Authors:RamaKrishna Manchana

Abstract:This paper presents an advanced approach to material management by leveraging modern system integration techniques and scalable microservices architecture. The proposed solution addresses the limitations of traditional monolithic systems by introducing microservices, control bus mechanisms, and event-driven designs that enhance operational efficiency and scalability. By utilizing advanced integration patterns, including synchronous and asynchronous services, the system improves real-time data processing and decision-making capabilities. This document outlines the technical architecture, key components, integration designs, and implementation strategies that underpin a robust and adaptable material management system, demonstrating significant improvements in scalability, performance, and responsiveness.

DOI: 10.61137/ijsret.vol.3.issue6.200

Optimizing Healthcare Data Warehouses for Future Scalability: Big Data and Cloud Strategies
Authors:Srinivasa Chakravarthy Seethala

Abstract:Healthcare organizations generate vast amounts of data, driven by regulatory compliance, patient care needs, and advances in medical technology. Legacy data warehouses, while central to healthcare data management, often struggle to accommodate escalating data volumes, new data types, and real-time processing demands. This paper presents strategic insights into leveraging Big Data and cloud computing to modernize healthcare data warehouses for future scalability. We examine technical approaches, review cloud and Big Data integration techniques, and propose a roadmap for healthcare data scalability, addressing concerns of security, compliance, and data interoperability.

DOI: 10.61137/ijsret.vol.3.issue6.201

Driving Business Decisions With Data: A Practical Framework For Successful Power BI Adoption

Authors: Anjali Thomas

 

Abstract: In today’s competitive business landscape, data-driven decision-making has become a strategic imperative. Organizations are increasingly turning to business intelligence (BI) platforms to transform raw data into actionable insights that guide growth, efficiency, and innovation. Among these platforms, Power BI stands out as a versatile solution that bridges the gap between technical complexity and user accessibility. This review article presents a comprehensive framework for successful Power BI adoption, emphasizing the interplay between governance, integration, scalability, and organizational readiness. The paper begins by outlining the challenges enterprises face when shifting from intuition-based management to data-centric practices, highlighting issues of data silos, inconsistent reporting, and resistance to cultural change. It then explores how Power BI’s architecture—spanning ETL processes, SQL integration, cloud deployment, and security mechanisms—can serve as the backbone for a sustainable BI strategy. The review further examines practical use cases across industries, DevOps-driven automation, and the role of training programs in fostering a self-service analytics culture. Through a critical discussion of opportunities and limitations, the article underscores that successful Power BI adoption requires more than technology; it demands alignment between people, processes, and platforms. By providing a structured roadmap, this study offers organizations a pragmatic guide to embedding Power BI within their BI lifecycle. The conclusion reaffirms that Power BI is not simply a reporting tool but a catalyst for building data-driven cultures that enhance agility, competitiveness, and long-term decision-making excellence.

DOI: https://doi.org/10.5281/zenodo.17275574

 

Creating A Single Source Of Truth: Data Governance With Power BI, SQL, And Effective ETL Processes

Authors: Vivek Sharma

 

Abstract: In contemporary enterprises, data fragmentation across multiple systems, departments, and formats poses significant challenges to decision-making, reporting accuracy, and operational efficiency. A Single Source of Truth (SSOT) addresses these challenges by consolidating heterogeneous data into a centralized, authoritative repository. This review examines the implementation of SSOT using SQL databases, robust ETL pipelines, and Power BI for visualization and governance. It explores the principles of data governance, including data ownership, quality control, role-based security, and regulatory compliance, emphasizing their critical role in maintaining data integrity and trustworthiness. The review also details best practices for relational database design, performance optimization, and ETL automation to ensure timely and accurate data delivery. Case studies across healthcare, financial services, and retail illustrate practical applications, demonstrating improved reporting efficiency, operational responsiveness, and decision-making capabilities. Furthermore, the integration of SSOT across enterprise workflows, combined with monitoring, audit trails, and automated alerts, underscores the value of a governed, centralized data ecosystem. The article highlights current challenges, including system complexity, adoption barriers, and legacy integration, and offers strategies for mitigation. Looking forward, emerging trends such as cloud-native architectures, real-time streaming, AI-enhanced analytics, and hybrid or federated data models suggest new avenues for enhancing SSOT utility and scalability. By providing a comprehensive framework, this review underscores the strategic, operational, and compliance benefits of SSOT, positioning it as a cornerstone for modern, data-driven enterprises seeking reliability, agility, and insight-driven decision-making.

DOI: https://doi.org/10.5281/zenodo.17275623

 

Tableau’s Secret Sauce: Leveraging RHEL And Centos For High-Performance Data Visualization

Authors: Kavya Menon

 

Abstract: Modern enterprises increasingly rely on business intelligence (BI) platforms to transform raw data into actionable insights. Tableau, as a leading BI tool, offers sophisticated visualization, analytics, and reporting capabilities. However, the underlying operating environment significantly impacts performance, scalability, security, and cost efficiency. This review explores the strategic advantages of deploying Tableau on Linux-based systems, specifically Red Hat Enterprise Linux (RHEL) and CentOS, for enterprise-grade BI implementations. It examines the role of Linux in enhancing system stability, providing robust security frameworks, supporting modular and automated workflows, and enabling high availability and scalability. The article analyzes data integration strategies, ETL pipelines, and dashboard optimization practices tailored to Linux environments, emphasizing both operational efficiency and user experience. Case studies across healthcare, finance, and retail illustrate real-world applications, demonstrating how Linux-based Tableau deployments support secure, high-performance analytics, regulatory compliance, and business agility. Furthermore, the review addresses monitoring, maintenance, and performance tuning, highlighting best practices for sustained system reliability. Future trends, including AI integration, real-time streaming, hybrid cloud architectures, and advanced automation, are discussed to illustrate the evolving landscape of enterprise BI. By combining Tableau’s visualization capabilities with Linux’s reliability and flexibility, organizations can achieve cost-effective, scalable, and secure BI solutions. This article underscores the importance of selecting an appropriate operating environment to maximize Tableau’s potential and provides a comprehensive guide for IT professionals, analysts, and business leaders seeking to optimize their BI infrastructure.

DOI: https://doi.org/10.5281/zenodo.17275816

 

Migrating Legacy Information Management Systems To AWS And GCP: Challenges, Hybrid Strategies, And A Dual-Cloud Readiness Playbook

Authors: Sudhir Vishnubhatla

Abstract: Legacy Information Management Systems (IMS) remain central to operations in banking, healthcare, public sector, and media, yet their monolithic design, proprietary data formats, and brittle integrations have become barriers to agility and intelligent analytics. Earlier literature identified the persistent costs and risks of legacy IMS and proposed incremental modernization through wrapping, service extraction, and reengineering, while empirical studies in the early 2010s established the feasibility and business value of infrastructure-as-a-service (IaaS) rehosting. As of late 2017, however, the migration decision space has widened: enterprises are not merely choosing whether to move to the cloud, but how to distribute workloads across multiple hyperscalers, primarily Amazon Web Services (AWS) and Google Cloud Platform (GCP). This article synthesizes more than a decade of academic and industrial work on legacy migration and proposes a Dual-Cloud Readiness Playbook tailored to IMS modernization. The playbook comprises a readiness scorecard, a five-phase migration lifecycle, and a layered hybrid architecture that balances compliance, cost, and capability while reducing vendor lock-in. The result is a pragmatic framework that aligns with the realities of petabyte-scale content archives, metadata-heavy workflows, and emerging regulatory constraints, offering a credible path from monolithic legacy platforms to modern, cloud-native information management

DOI: https://zenodo.org/records/17298069

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