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intelligent computing and networking - proceedings of ic-icn 2023

ISBN: (纸本)9789819931767

The proceedings contain 42 papers. The special focus in this conference is on intelligent computing and networking. The topics include: Investigating the Impact of Distance on the Reception in Molecular Communication;skin Cancer Multiclass Classification Using Weighted Ensemble Model;indian Sign Language Recognition: A Comparative Study;Comparative Investigation of Machine Learning and Deep Learning Methods for Univariate AQI Forecasting;scheduling the Tasks and Balancing the Loads in Cloud computing Using African Vultures-Aquila Optimization Model;cyber Intrusion Detection Using a Boosting Ensemble of Neural Networks;hyperparameter Study: An Analysis of Hyperparameters and Their Search Methodology;Virtual Machine Load Balancing Using Improved ABC for Task Scheduling in Cloud computing;aspect-Based Sentiment Classification: Survey;Dollar Price Prediction Using ARIMA;Irrigation Using IOT Sensors;music Overflow: A Music Genre Classification Web Application;a Comparative Analysis of Recent Face Detection Methods Implemented for Age and Gender Detection;a Machine Learning Approach for Entrepreneurial Competencies and Economic Growth of Women Entrepreneurs from Kandhamal District;product Review and Recommendation;Performance Evaluation of Lightweight ASCON-HASH Algorithm for IoT Devices;design of Virtual-Real Software-Defined Network for Cloud;deep Learning-Based Intrusion Detection Model for Network Security;controlling Project Execution in the Era of Soft computing and Machine Learning;PUF-Based Lightweight Authentication Protocol for IoT Devices;an Exploratory Study on the Impact of Digital Marketing and Innovations on E-commerce Mechanism;support Vector Machine for Multiclass Classification of Redundant Instances;energy Efficient Lightweight Scheme to Identify Selective Forwarding Attack on Wireless Sensor Networks;predicting Position of User Equipment Using Machine Learning.

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15th International Conference on intelligent computing and networking, ic-icn 2024

15th International Conference on Intelligent Computing and N...

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15th International Conference on intelligent computing and networking, ic-icn 2024

ISBN: (纸本)9789819786305

The proceedings contain 16 papers. The special focus in this conference is on intelligent computing and networking. The topics include: Performance Analysis of Medical Image Fusion Using Wavelet Technique;correlation Analysis and Stock Market Prediction of Nifty and Nasdaq Indices Using Machine Learning Techniques;Integrated RFID-Verified Smart Manufacturing System for Bottle Production Using Industry 4.0;Comparing Advanced Programming Languages Based on Machine Learning (ML);optimal Cluster and Node Balancing Technique Using K-Mean Based on Q-Learning for Wireless Sensor Network;optimizing IoT Task Offloading with Federated Deep Reinforcement Learning in Vehicle and Industrial Environments;enhancing Video Action Recognition with Spatial–Temporal Convolutional Attention Networks;spatial Federated Learning Based Blockchain Mechanism for Smart Contract Vulnerability Detection;enhancing Healthcare Recommendations for Special-Need Patients Using Deep Learning and Blockchain Security;machine-Learning-Enhanced Blockchain for Dynamic Pricing Models in E-Commerce;mining Intelligence Hierarchical Feature for Malware Detection;scraping Data from Google Maps: Comparisons and Experimentations;source Code Pre-processing and Analysis to Extricate Features Using Abstract Syntax Tree;AI-Based Wireless Communication: Ultra-Reliable MAC Protocols.

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International Conference on intelligent computing and networking, ic-icn 2022

International Conference on Intelligent Computing and Networ...

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International Conference on intelligent computing and networking, ic-icn 2022

ISBN: (纸本)9789819900701

The proceedings contain 18 papers. The special focus in this conference is on intelligent computing and networking. The topics include: Stock Market Trend Prediction Along with Twitter Sentiment Analysis;A Study on MQTT Protocol Architecture and Security Aspects Within IoT Paradigm;compartive Analysis of Different Block Chain Technology to Improve the Security in Social Network;euphonia: Music Recommendation System Based on Facial Recognition and Emotion Detection;Improvement of Makespan and TCTime in Dynamic Job Ordering and Slot Utilization for MapReduce Workloads;preface;Implementation of a PID Controller for Autonomous Vehicles with Traffic Light Detection in CARLA;identification and Detection of Plant Disease Using Transfer Learning;blockchain Based E-Voting System;an intelligent Voice Assistant Engineered to Assist the Visually Impaired;analysis of Python Libraries for Artificial Intelligence;annual Rainfall Prediction of Maharashtra State Using Multiple Regression;Automated Healthcare System Using AI Based Chatbot;winner Prediction of Football Match Using Machine Learning;raktaSeva—An App for Civilians and Blood Banks;prediction of Anemia Disease Using Machine Learning Algorithms.

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On the icn-IoT with federated learning integration of communication: Concepts, security-privacy issues, applications, and future perspectives

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2023年 138卷 61-88页

作者： Rahman, Anichur Hasan, Kamrul Kundu, Dipanjali Islam, Md. Jahidul Debnath, Tanoy Band, Shahab S. Kumar, Neeraj Mawlana Bhashani Sci & Technol Univ Dept CSE Tangail Bangladesh Constituent Inst Univ Dhaka Natl Inst Text Engn & Res NITER Dept CSE Savar Dhaka 1350 Bangladesh Hankuk Univ Foreign Studies Dept ICE Seoul South Korea Green Univ Bangladesh Dept CSE 220-D Begum Rokeya Sarani Dhaka 1207 Bangladesh Natl Yunlin Univ Sci & Technol Coll Future Future Technol Res Ctr 123 Univ Rd Sect 3 Touliu 64002 Yunlin Taiwan Deemed Univ Thapar Inst Engn & Technol Dept CSE Patiala Punjab India Univ Petr & Energy Studies Sch Comp Sci Dehra Dun Uttarakhand India Asia Univ Dept Comp Sci & Informat Engn Taichung Taiwan King Abdulaziz Univ Jeddah Saudi Arabia

The individual and integration use of the Internet of Things (IoT), Information-Centric networking (icn), and Federated Learning (FL) have recently been used in several network-related scenarios and have consequently experienced a growing interest in the research community. Federated learning addresses the privacy and security issues of the IoT data in a decentralized manner. Also, it can be capable of training the multiple learning algorithms through local content except for exchanging data through intelligent Artificial Intelligence (AI)-based algorithms. Moreover, in icn, the content is retrieved and stored based on the content name rather than the content location address. On the other hand, it is challenging to support the massive IoT devices by the fifth generation (5G) mobile-cellular networks. Therefore, the cellular 6G networks are expected to increase the connection capabilities by 10-100 times over 5G, which necessitates a convergence of Communication, computing, and Caching (3C). At the same time, the in-network caching capabilities of icn can be attractive features for IoT networks. IoT aspires to link anybody and/or everything at any time and location. However, integrating IoT with different areas is a new academic topic and is still in its infancy. As a result, this research highlights the potential of icn for IoTs by conducting an exhaustive literature review. This work provides a comprehensive survey regarding these three recent research trends (i.e., FL, IoT, and icn) and reviews the related state-of-the-art literature. We first describe the main features of each technology and discuss their most common and used variants. Furthermore, we envision the integration of such technologies to take advantage efficiently. Indeed, we consider their group-wise (FL-icn-IoT) utilization based on the need for more robust security and privacy. Additionally, we cover the application fields of these technologies both individually and combinedly. Finally, we discuss

关键词： Internet of Things Information-Centric networking Federated Learning Communication Security computing Machine Learning Privacy Artificial Intelligence Confidentiality

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Design of Virtual-Real Software-Defined Network for Cloud

Design of Virtual-Real Software-Defined Network for Cloud

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Lakshmi, J. Divya Mallikarjun, P.Y. Department of Electronics and Communication Engineering Sri Krishna Institute of Technology Bengaluru India Department of Electronics and Communication Engineering Dayananda Sagar Academy of Technology and Management Bengaluru India

ISBN: (纸本)9789819931767

In the construction of network simulation experiment scenarios, complex physical terminals are challenging to realize virtual simulation, and physical terminals need to be accessed. However, the existing access methods are difficult to deploy, have bottlenecks in network performance, and cannot be applied to large-scale network scenarios. To effectively solve the above problems, a virtual-real fusion network simulation construction method based on SDN (software defined-network) is proposed, using the SDN controller combined with the flow table construction algorithm to realize the link management and data connection of the virtual and real network and design A prototype system for virtual-real fusion network simulation has been developed. Through the SDN controller, the virtual instance in the cloud platform and the physical terminal outside the cloud can be jointly networked to build a virtual-real fusion network simulation experiment scene. Using this prototype system, experiments have proved that the SDN-based network simulation method can realize efficient large-scale networking of virtual instances and physical terminals in the cloud platform and has good network performance. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Software defined networking

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Controlling Project Execution in the Era of Soft computing and Machine Learning

Controlling Project Execution in the Era of Soft Computing a...

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Bajpai, Bhavna Khare, Amit Mudhafar, Mustafa Singh, Shweta Jawarneh, Malik Mustafa Mohammad Sandhu, Mukta Dr. C V Raman University Madhya Pradesh Khandwa India Department of Technology JIET Institute of Design and Technology Rajasthan Jodhpur India Department of Anesthesia and Health Care Faculty of Altuff College University Karbala Iraq Electronics and Communication Department IES College of Technology Bhopal India Faculty of Computing Sciences Gulf College Seeb India SVSU Haryana India

ISBN: (纸本)9789819931767

During the execution control of their initiatives, organisations use a variety of devices to aid independent direction. Regardless, they are still insufficient in the face of skewed statistics and shifting management approaches. The absence of frameworks for controlling the execution of enterprises has an impact on the nature of their categorization in terms of supporting independent direction. The presentation of soft registering methods, which provide heartiness, effectiveness and flexibility at apparatuses, is an optional arrangement. This research provides a technique for project execution control based on Soft computing and ML, which contributes to the executives’ ability to further improve the project. The proposed method allows for AI and the replacement of fuzzy inference frameworks in project evaluation. The results are derived from seven calculations involving space apportioning, neural architecture, gradient descent and genetic algorithms. Adoption of the proposed framework, which has been included in this paper for project personnel, signifies a change in the nature of venture evaluation. The obtained result ensures that the apparatuses are in perfect working order to assist the independent direction in projecting the executive associations. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Soft computing

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Compartive Analysis of Different Block Chain Technology to Improve the Security in Social Network 1

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International Conference on intelligent computing and networking, ic-icn 2022

作者： Modi, Niki Princeton University PrincetonNJ08544 United States Springer Heidelberg Tiergartenstr. 17 Heidelberg69121 Germany

ISBN: (数字)9789819900718

ISBN: (纸本)9789819900701

Social networking sites have given users unprecedented opportunities for the generation and dissemination of content. Block chain Technology as defined the decentralized system for distributed registers which are used to record data transactions on multiple computers. So a variety of social networking sites exist for different purposes, to afford users a range of anonymous and non-anonymous options for self-expression, and the ability to be a part of a virtual community. Sometimes a misinformation, propagated by users and group can create chaos or in some cases, might leads to cases of riots. Therefore, a robust and new system is required to check the information authenticity within the network, to stop the propagation of misinformation. In this paper, propose of block chain based framework is for sharing the information securely at the peer level. In the block chain model, a chain is created by combining blocks of information. I analyze real data by exploiting one of the most well-known DApps sites (decentralized applications), and also compare current technologies in order to get better algorithm or tool to secure our information. such as Facebook. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Social networking (online)

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Virtual Machine Load Balancing Using Improved ABC for Task Scheduling in Cloud computing 1

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Hanuman, Reddy N. Lathigara, Amit Aluvalu, Rajanikanth Viswanadhula, Uma Maheswari R K University Rajkot India Chaitanya Bharathi Institute of Technology Hyderabad India

ISBN: (数字)9789819931774

ISBN: (纸本)9789819931767

computing resources are now more accessible, powerful, and inexpensive than ever before thanks to the widespread adoption of the Internet and rapid advancements in processing and storage technology. Thanks to this development in expertise, a new kind of computing architecture known as "cloud computing" is now a practical reality. Load balancing task scheduling is an essential issue that has a direct impact on resource utilisation in cloud settings. One of the most important goals of scheduling is to distribute work among virtual machines in such a way that no individual machine is overburdened or underutilised. Considering load balancing scheduling is crucial because of the importance it has on the backend and frontend of the cloud research sector. Any time a cloud environment is able to effectively balance its load, resource utilisation improves. The challenge with load balancing in the cloud is that it is an NP-hard optimization delinquent. To solve this issue, this research suggests a method that combines a heuristic scheduling algorithm with an artificial bee colony;this method is referred to as enhanced Artificial Bee Colony for Task Scheduling (IABC-TS). For better cloud computing scheduling of virtual machines in both homogeneous and heterogeneous contexts, this approach is used. The goal of its implementation was to shorten makespan and distribute weight more evenly. The IABC-TS cloud computing system's scheduling performance was measured against that of competing swarm intelligence techniques. In our lab tests, we used CloudSim to simulate systems with various augmentation techniques to examine their makespan and load balancing ability. Based on the results of the experiments, it is clear that the suggested IABC-TS outperformed the baseline models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Virtual machine

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Scheduling the Tasks and Balancing the Loads in Cloud computing Using African Vultures-Aquila Optimization Model 1

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Raghavender Reddy, K.L. Lathigara, Amit Aluvalu, Rajanikanth Viswanadhula, Uma Maheswari R K University Rajkot India Chaitanya Bharathi Institute of Technology Hyderabad India

ISBN: (数字)9789819931774

ISBN: (纸本)9789819931767

Load balancing among VMs is crucial for optimizing the delivery of cloud services, both in terms of the money spent and the time spent. Transferring a running virtual machine from one physical host to another is known as "live VM migration," and it is used in the cloud to balance the system load. While this method has been offered to lessen downtime while moving overburdened VMs, it is still expensive and requires a sizable amount of memory to implement. To address these limitations, we provide a Task-based-System Load Balancing approach based on the African Vultures-Aquila Optimization Model (AVAO), which attains system load balancing by moving only the surplus of tasks from an overcrowded VM. In addition, we develop an optimization model for applying AVAO to the transfer of these supplementary activities to the new host VMs. We employ an augmented version of the cloud simulator (Cloudsim) package with AVAO as its task scheduling typically to test the suggested strategy. Based on the simulation findings, it is clear that the proposed method considerably shortens the time required for the load balancing practice when compared to the conventional methods. In terms of both makespan time and throughput, the system's performance is significantly enhanced if the proposed method is proven to be valid. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Virtual machine

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Probabilistic Scheme for intelligent Jammer Localization for Wireless Sensor Networks

Probabilistic Scheme for Intelligent Jammer Localization for...

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intelligent computing and networking - proceedings of ic-icn 2023

作者： Yadav, Amar Pal Davuluri, Sandeep Kumar Charan, Piyush Keshta, Ismail Gavilán, Juan Carlos Orosco Dhiman, Gaurav CSE-AI College: Noida Institute of Engineering and Technology Greater Noida Greater Noida India Department of Information Technology University of the Cumberlands WilliamsburgKY40769 United States Electronics and Communication Engineering Manav Rachna University Faridabad India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Universidad Privada del Norte campus virtual Lima Peru Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9789819931767

With the development of artificial intelligence technology, intelligent interference sources can improve the interference effect by changing their transmission power, which leads to the failure of traditional positioning technology based on received signal strength. Therefore, a sensor wake-up mechanism is introduced to study multi-interference sources based on block-compressed sensing positioning method. First, wake up the sensor nodes periodically, while improving the utilization effectiveness of the sensor nodes and the accuracy of positioning information collection;secondly, considering that the distance between the distance and the received signal strength cannot be determined when the transmission power of the interference source is unknown and changes. Then, based on the compressive sensing theory, the positioning problem is modeled as a block sparse vector reconstruction problem;finally, a variation-based algorithm is designed by exploring the law of power variation. The Wake-VBEM reconstruction algorithm based on Bayesian mean expectation accurately reconstructs the target position vector. The simulation proves that the proposed method can simultaneously realize the position estimation of multiple interference sources and effectively improve the service life of the network when the interference source power is unknown and changes. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Artificial intelligence

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