Volume-4 Issue-4, June 2024 – Indian Journal of Data Communication and Networking (IJDCN)

D503704040624

IJDCN Journal — Wed, 26 Jun 2024 05:35:17 +0000

The Indian Journal of Data Communication and Networking (IJDCN) has ISSN 2582-760X (Online), an open-access, peer-reviewed, periodical bi-monthly international journal, which is published by Lattice Science Publication (LSP) in February, April, June, August, October and December. The aim of the journal is to publish high quality peer–reviewed original articles in the area of Data Communication and Networking that covers Addressing, Routing, Switching and Location Management, Broadband, Mobile, Wired, Wireless Internet, Networks, Adhoc and Sensor Networks, High Speed Networks, Mobile and Wireless Networks, Network Architectures, Network Based Applications, Network Protocols, Network Operations & Management, Network Security Trust & Privacy, Cross Layer Design and Optimization, Internet and Web Applications, Network Measurement & Performance Analysis, Next Generation Internet & Web Architectures, Peer to Peer and Overlay Networks, QOS And Resource Management, Recent Trends & Developments in Computer Networks, Self-Organizing Networks and Networked Systems, Ubiquitous Networks, Virtual & Overlay Networks, Wireless Mesh Networks and Protocols, Wireless Multimedia Systems, Personal and Wearable Networks, Embedded Networks, Delay-Tolerant Networks, Cognitive Radio Networks, Vehicular Networks, Smart Grid Communications, Underwater Sensor Networks, Cyber-Physical Systems, Social Networks, Green Networking, Overlay and Peer-to-Peer Networks, Local-area and Metropolitan-Area Networks, Storage-Area Networks, Routing and Transport Protocols, Internet of Things, Link Technologies, Authentication, Authorization, Accounting, Security and Privacy, Cross-Layer Optimization, Multimedia and Real-Time Communication, Machine-to-Machine Communications for Smart Environments, Smart Cities, Network Traffic Characterization and Measurements, Network Management, Reliability and QoS, Performance Evaluation of Networks, Testbeds for Network Experiments, Network Coding, Optical and High-Speed access Networks, High Performance Computing, Digital System and Logic Design, Networked-Driven Multicourse Chips, Information-centric Networking, Opportunistic Networking, Mobile and Ubiquitous Networking, Big Data Networking, Cloud Computing and Networking, Software Defined Networking and Network Function Virtualization, Adaptive Networking Applications, IoT & IoE & Edge Computing, Distributed Mobile Applications Utilizing IoT, Security, Privacy and Trust in IoT & IoE, Standards for IoT Applications, Ubiquitous Computing, Blockchain-Enabled IoT Device and Data Security and Privacy, Application of WSN in IoT, Cloud Resources Utilization in IoT, Wireless Access Technologies for IoT, Mobile Applications and Services for IoT, Machine/ Deep Learning with IoT & IoE, Smart Sensors and Internet of Things for Smart City, Logic, Functional programming and Microcontrollers for IoT, Sensor Networks, Actuators for Internet of Things, Data Visualization using IoT, IoT Application and Communication Protocol, Big Data Analytics for Social Networking using IoT, IoT Applications for Smart Cities, Emulation and Simulation Methodologies for IoT, IoT Applied for Digital Contents, Microstrip Antenna, Microwave, Radar and Satellite, Smart Antenna, MIMO Antenna, Wireless Communication, RFID Network and Applications, 5G Communication, 6G Communication. #Network Architectures #Network Based Applications #Network Protocols #Network Operations & Management #Network Security Trust & Privacy #Cross Layer Design and Optimization #Internet and Web Applications #Network Measurement & Performance Analysis #Next Generation Internet & Web Architectures #Peer to Peer and Overlay Networks #QOS And Resource Management #Recent Trends & Developments in Computer Networks #Self-Organizing Networks and Networked Systems #Ubiquitous Networks #Virtual & Overlay Networks #Wireless Mesh Networks and Protocols #Wireless Multimedia Systems #Personal and Wearable Networks #Information-Centric Networking #Embedded Networks #Opportunistic Networking #Delay-Tolerant Networks #Cognitive Radio Networks #Vehicular Networks #Smart Grid Communications #Underwater Sensor Networks #Cyber-Physical Systems #Social Networks #Green Networking #Overlay and Peer-to-Peer Networks #Local-area and Metropolitan-Area Networks #Storage-Area Networks #Routing and Transport Protocols #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Internet of Things #Link Technologies #Adaptive Networking Applications #Authentication, Authorization, Accounting #Security and Privacy #Cross-Layer Optimization #Multimedia and Real-Time Communication #Machine-to-Machine Communications for Smart Environments #Smart Cities #Network Traffic Characterization and Measurements #Network Management, Reliability and QoS #Performance Evaluation of Networks #Testbeds for Network Experiments #Network Coding #Optical and High-Speed Access Networks #High Performance Computing #Digital System and Logic Design #Networked-Driven Multicourse Chips #Information-Centric Networking #Opportunistic Networking #Mobile and Ubiquitous Networking #Big Data Networking #Cloud Computing and Networking #Software Defined Networking and Network Function Virtualization #Adaptive Networking Applications #Internet of Things (IoT) #IoT & IoE & Edge Computing #Distributed Mobile Applications Utilizing IoT #Security, Privacy and Trust in IoT & IoE #Standards for IoT Applications #Ubiquitous Computing #Blockchain-enabled IoT Device and Data Security and Privacy #Application of WSN in IoT #Cloud Resources Utilization in IoT #Wireless Access Technologies for IoT #Mobile Applications and Services for IoT #Machine/ Deep Learning with IoT & IoE #Smart Sensors and Internet of Things for Smart City #Logic, Functional programming and Microcontrollers for IoT #Sensor Networks, Actuators for Internet of Things #Data Visualization using IoT #IoT Application and Communication Protocol #Big Data Analytics for Social Networking using IoT #IoT Applications for Smart Cities #Emulation and Simulation Methodologies for IoT #IoT Applied for Digital Contents #Antenna and Communications Devices #Microstrip Antenna #Microwave #Radar and Satellite #Smart Antenna #MIMO Antenna #Wireless Communication #RFID Network and Applications #5G Communication #6G Communication #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLons

Medical Insurance Cost Prediction
Sabarinath U S¹, Ashly Mathew²

¹Sabarinath U S, Department of Computer Science, St. Albert’s College, Kochi (Kerala), India.

²Ashly Mathew, Department of Computer Science, St. Albert’s College, Kochi (Kerala), India.

Abstract: This is a medical insurance cost prediction model that uses a linear regression algorithm to predict the medical insurance charges of a person based on the given data. To predict things that have never been so easy. In this project used to predict values that wonder how Insurance amount is normally charged. This is a medical insurance cost prediction model that uses a linear regression algorithm to predict the medical insurance charges of a person based on the given data. This project on predicting medical insurance costs can serve various purposes and address several needs that are Accurate Pricing Insurance companies need accurate predictions of medical insurance costs to set appropriate premiums for policyholders. Predictive models can analyse historical data and various factors such as age, gender, pre-existing conditions, lifestyle habits, and geographic location to estimate future healthcare expenses accurately. This Prediction model achieves three regression methods accuracy that the linear regression gets an accuracy of 74.45 %, whereas Ridge regression and Support Vector Regression gets 82.59% word-level state-of-the-art accuracy. The Medical Insurance Cost Prediction project, proposes a comprehensive approach to predict the medical cost, aiming to develop a robust and accurate system capable of predicting the accurate cost for a particular individual. Leveraging linear regression, our proposed system builds upon the successes of existing models like different types of regressions like linear regression, Ridge regression and Support Vector regression. We will put the Regression algorithm into practice and evaluate how it performs in comparison to the other three algorithms. By comparing the performance of these three methodologies, this project aims to identify the most effective approach for medical insurance cost prediction. Through rigorous evaluation and validation processes, the selected model will provide valuable insights for insurance companies, policymakers, and individuals seeking to optimize healthcare resource allocation and financial planning strategies.

Keywords: Regression, Linear regression, Ridge Regression, Support vector Regression.
Scope of the Article: Machine/ Deep Learning with IoT & IoE

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D503504040624

IJDCN Journal — Wed, 26 Jun 2024 05:25:04 +0000

A Comprehensive Survey of Load Balancing Techniques in Multipath Energy-Consuming Routing Protocols for Wireless Ad hoc Networks in MANET
Neetu Sahu¹, S. Veenadhari²

¹Neetu Sahu, Research Scholar, Rabindranath Tagore University, Bhopal (M.P), India.

²Dr. S. Veenadhari, Professor, Department of Computer Science and IT, Rabindranath Tagore University, Bhopal (M.P), India.

Abstract: As technology progresses, networking undergoes continuous evolution to align with contemporary trends. Mobile Ad hoc Networks (MANETs) have emerged as a pivotal technology facilitating communication among mobile nodes sans a central administering node. MANETs find diverse applications spanning communication networks to battlefield scenarios. Nonetheless, MANETs encounter various challenges, including load balancing, energy efficiency, packet loss, and connection failures. Routing, among these challenges, assumes a pivotal role in defining network performance and connectivity capacity within MANETs. Moreover, the energy consumption of mobile nodes, often reliant on batteries with limited rechargeability, presents a significant concern in MANETs. This paper delves into diverse techniques devised to tackle the issues of energy efficiency and load balancing in MANETs. Additionally, it offers a comparative analysis to consolidate the survey findings. The outcomes of this study enrich our comprehension of energy-efficient and load-balanced routing protocols in MANETs, thereby facilitating the design and deployment of efficient networking solutions.

Keywords: Energy Efficiency, Load Balancing, Battery Constraint, Mobile Nodes, MANET
Scope of the Article: Communication

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