Fog computing, a novel paradigm for distributed computing, has found extensive applications in critical sectors like healthcare. This study is dedicated to setting up and evaluating network properties crucial for real-time decision-making systems. Specifically, it comprehensively and analytically assesses two leading fog computing simulators, YAFS and LEAF. By focusing on key performance metrics—memory usage, CPU consumption, and execution latency—the research aims to clearly delineate the capabilities and limitations of each simulator. Through meticulous comparative analysis, the study identifies which simulator offers superior efficiency and scalability in modelling complex fog computing environments within healthcare. Moreover, the paper aims to highlight both the strengths and weaknesses of YAFS and LEAF, providing foundational insights to inform the deployment of fog computing solutions in healthcare settings. This research not only examines the technical properties and performance of these simulators but also explores broader implications of adopting fog computing over traditional cloud architectures. Ultimately, the findings aim to serve as a valuable guide for researchers and practitioners in selecting the most suitable simulation tools, thereby facilitating the enhanced design and optimization of fog-based applications.
{"title":"Fog Computing Simulators: A Comprehensive Research and Analytical Study","authors":"Rushikesh Rajendra Nikam, Dr. Dilip Motwani","doi":"10.52783/cana.v31.1057","DOIUrl":"https://doi.org/10.52783/cana.v31.1057","url":null,"abstract":"Fog computing, a novel paradigm for distributed computing, has found extensive applications in critical sectors like healthcare. This study is dedicated to setting up and evaluating network properties crucial for real-time decision-making systems. Specifically, it comprehensively and analytically assesses two leading fog computing simulators, YAFS and LEAF. By focusing on key performance metrics—memory usage, CPU consumption, and execution latency—the research aims to clearly delineate the capabilities and limitations of each simulator. Through meticulous comparative analysis, the study identifies which simulator offers superior efficiency and scalability in modelling complex fog computing environments within healthcare. Moreover, the paper aims to highlight both the strengths and weaknesses of YAFS and LEAF, providing foundational insights to inform the deployment of fog computing solutions in healthcare settings. This research not only examines the technical properties and performance of these simulators but also explores broader implications of adopting fog computing over traditional cloud architectures. Ultimately, the findings aim to serve as a valuable guide for researchers and practitioners in selecting the most suitable simulation tools, thereby facilitating the enhanced design and optimization of fog-based applications.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we discuss about the Hill Cipher cryptosystem, the RSA public-key cryptosystem, developed by Rivest, Shamir, Adleman for text encoding and decoding. To encrypt and decrypt the message, we use the Euler Phi-function, congruences, and matrix multiplication. Further, we employ two keys for coding and decoding. Introduction: In present, computer networks, internet and mobile communications are important and inevitable part of our society and security of information from hackers is a big task. One of the most widely used applications for information security is Cryptography. Usually in Hill cipher there are two keys, of which one acts as encryption key and the other one acts as decryption key. In this paper we discuss about Hill Cipher using only one key for data encryption and data decryption. Further, we extend our result with dual encryption and decryption process which is explained by using the RSA public key cryptosystem and Hill Cipher and they together execute a powerful cryptosystem to secure the data. Objectives: The purpose of this paper is to obtain and compare the result of data encryption and data decryption using: A matrix which is invertible. A matrix which is Involutory. An RSA cryptosystem which is applied for Hill Cipher where the matrix is Involutory. Methods: Using Hill Cipher and thereafter Hill Cipher - RSA together we have encrypted and decrypted the data under modulo 255. Results: The text message is converted to coded message and then original message is retrieved by using the three different techniques. Conclusions: As the paper involves two stages of encryption and decryption where public key and private key which are unthinkable by the third parities, the security of information is highly appreciable.
{"title":"Some Results of Data Encryption and Decryption using Euler’s Totient Function","authors":"Gobburi Rekha, V. Srinivas","doi":"10.52783/cana.v31.1063","DOIUrl":"https://doi.org/10.52783/cana.v31.1063","url":null,"abstract":"In this paper, we discuss about the Hill Cipher cryptosystem, the RSA public-key cryptosystem, developed by Rivest, Shamir, Adleman for text encoding and decoding. To encrypt and decrypt the message, we use the Euler Phi-function, congruences, and matrix multiplication. Further, we employ two keys for coding and decoding. \u0000Introduction: In present, computer networks, internet and mobile communications are important and inevitable part of our society and security of information from hackers is a big task. One of the most widely used applications for information security is Cryptography. Usually in Hill cipher there are two keys, of which one acts as encryption key and the other one acts as decryption key. In this paper we discuss about Hill Cipher using only one key for data encryption and data decryption. Further, we extend our result with dual encryption and decryption process which is explained by using the RSA public key cryptosystem and Hill Cipher and they together execute a powerful cryptosystem to secure the data. \u0000Objectives: The purpose of this paper is to obtain and compare the result of data encryption and data decryption using: \u0000 \u0000A matrix which is invertible. \u0000A matrix which is Involutory. \u0000An RSA cryptosystem which is applied for Hill Cipher where the matrix is Involutory. \u0000 \u0000Methods: Using Hill Cipher and thereafter Hill Cipher - RSA together we have encrypted and decrypted the data under modulo 255. \u0000Results: The text message is converted to coded message and then original message is retrieved by using the three different techniques. \u0000Conclusions: As the paper involves two stages of encryption and decryption where public key and private key which are unthinkable by the third parities, the security of information is highly appreciable.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141824656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
By using compatibility condition type (P) in probabilistic metric space, establish common fixed point results for four self-mappings with control function in [0,1]. The result of Chaudhary et. al [5] is a particular case of this new result and it extends and generalizes other similar results in the literature.
{"title":"A Common Fixed Point Result in Menger Space","authors":"Ajay Kumar Chaudhary","doi":"10.52783/cana.v31.1065","DOIUrl":"https://doi.org/10.52783/cana.v31.1065","url":null,"abstract":"By using compatibility condition type (P) in probabilistic metric space, establish common fixed point results for four self-mappings with control function in [0,1]. The result of Chaudhary et. al [5] is a particular case of this new result and it extends and generalizes other similar results in the literature.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141824358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates an inventory model addressing non-instantaneous deteriorating items with expiration concerns, incorporating a hybrid payment approach. The demand factors of this study are price-sensitive demand, product freshness considerations, and advertising frequency impact, which are critical elements in contemporary supply chain challenges. The proposed model investigates multiple prepayments and delayed payments to bolster business operations during financial emergencies. This study aims to enhance business flexibility, and the model reflects real-world complexities by introducing a time-dependent holding cost and accounting for partial backlogged shortages. The establishment of convexity ensures efficient optimization and numerical examples clearly illustrate how the proposed strategies influence overall enterprise profitability. Furthermore, the utilization of MATLAB for graphical representation enhances result availability and understanding. Sensitivity analysis enriches decision-making by providing important managerial insights during the recovery phase. This research contributes a strong foundation for inventory optimization that can adapt to changing post-pandemic economic conditions.
{"title":"Optimizing Advertising and Pricing for Perishable Inventory with Freshness-Related Demand in a Hybrid Partial Prepayment and Trade Credit Supply Chain","authors":"T.Vanjikkodi","doi":"10.52783/cana.v31.1060","DOIUrl":"https://doi.org/10.52783/cana.v31.1060","url":null,"abstract":"This paper investigates an inventory model addressing non-instantaneous deteriorating items with expiration concerns, incorporating a hybrid payment approach. The demand factors of this study are price-sensitive demand, product freshness considerations, and advertising frequency impact, which are critical elements in contemporary supply chain challenges. The proposed model investigates multiple prepayments and delayed payments to bolster business operations during financial emergencies. This study aims to enhance business flexibility, and the model reflects real-world complexities by introducing a time-dependent holding cost and accounting for partial backlogged shortages. The establishment of convexity ensures efficient optimization and numerical examples clearly illustrate how the proposed strategies influence overall enterprise profitability. \u0000Furthermore, the utilization of MATLAB for graphical representation enhances result availability and understanding. Sensitivity analysis enriches decision-making by providing important managerial insights during the recovery phase. This research contributes a strong foundation for inventory optimization that can adapt to changing post-pandemic economic conditions.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 46","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Swathi, Sivakumar Depuru, M. Sakthivel, S. Sivanantham, K. Amala, Pavan Kumar
User credentials are vulnerable to exposure in demilitarized zones due to software vulnerabilities and hardware threats. This research aims to mitigate these risks by proposing a sophisticated trust-based malware detection (T-MALWARE DETECTION) method that can accurately classify data. The proposed system utilizes an enhanced Glow-Worm Swarm Optimization (IGWSO) technique to efficiently cluster datasets. To classify potential intrusions and assign trust levels to cloud data after clustering, a Recurrent Neural Network (RNN) approach is employed. The effectiveness of the Trust-oriented Malware Detection System (T-MALWARE DETECTIONS) is evaluated using metrics such as detection rate, precision, recall, and F-measure. This system is developed using Java and the CloudSimulator (CloudSim) tool, allowing for a thorough evaluation of its performance in comparison to contemporary state-of-the-art systems.
{"title":"A Hybrid Malware Detection System for Enhanced Cloud Security Utilizing Trust-Based Glow-Worm Swarm Optimization and Recurrent Deep Neural Networks","authors":"R. Swathi, Sivakumar Depuru, M. Sakthivel, S. Sivanantham, K. Amala, Pavan Kumar","doi":"10.52783/cana.v31.994","DOIUrl":"https://doi.org/10.52783/cana.v31.994","url":null,"abstract":"User credentials are vulnerable to exposure in demilitarized zones due to software vulnerabilities and hardware threats. This research aims to mitigate these risks by proposing a sophisticated trust-based malware detection (T-MALWARE DETECTION) method that can accurately classify data. The proposed system utilizes an enhanced Glow-Worm Swarm Optimization (IGWSO) technique to efficiently cluster datasets. To classify potential intrusions and assign trust levels to cloud data after clustering, a Recurrent Neural Network (RNN) approach is employed. The effectiveness of the Trust-oriented Malware Detection System (T-MALWARE DETECTIONS) is evaluated using metrics such as detection rate, precision, recall, and F-measure. This system is developed using Java and the CloudSimulator (CloudSim) tool, allowing for a thorough evaluation of its performance in comparison to contemporary state-of-the-art systems.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":"135 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Companies constantly strive to increase their profits, but the competition is tough in the market. Businesses try to either keep their existing customers through increased satisfaction, or to win new customers and new market shares in order to reach their objective. The term Customer Relationship Management was developed in the late 1990s, in order to facilitate relationships at the “business to consumer market”. CRM is used as a tool in order to build long term relationships between sellers and buyers. Through this relationship both the company and its customers should receive mutual benefits, such as retention and good service. Hence this paper helps to study the effectiveness of CRM practices and its impact on customer satisfaction at Hyundai motors.
{"title":"Effectiveness of Customer Relationship Management Practices at Hyundai Motors","authors":"G. M. Siddeeq, Dr. G. Silpa","doi":"10.52783/cana.v31.1004","DOIUrl":"https://doi.org/10.52783/cana.v31.1004","url":null,"abstract":"Companies constantly strive to increase their profits, but the competition is tough in the market. Businesses try to either keep their existing customers through increased satisfaction, or to win new customers and new market shares in order to reach their objective. The term Customer Relationship Management was developed in the late 1990s, in order to facilitate relationships at the “business to consumer market”. CRM is used as a tool in order to build long term relationships between sellers and buyers. Through this relationship both the company and its customers should receive mutual benefits, such as retention and good service. Hence this paper helps to study the effectiveness of CRM practices and its impact on customer satisfaction at Hyundai motors.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we proposed two new algorithms to address the task of multicriteria decision-making problems in which the criteria weights which have been unidentified, and alternatives are provided by triangular fuzzy numbers' linguistic values. A decision-making problem with assessments has been proposed on the basis of expected values. The expected values for two algorithms are calculated with two different 'Ranking Functions'. The weights are obtained by calculating the variance and mean of expected values with the aid of the triangular hesitant fuzzy decision matrix. The all alternatives ranking order is determined, and the maximum one is the best that can be identified easily. Lastly, a representative example is provided regarding the health issues of a community.
{"title":"Decision–Making Problem for Triangular Hesitant Fuzzy Set","authors":"E. Fany Helena","doi":"10.52783/cana.v31.1036","DOIUrl":"https://doi.org/10.52783/cana.v31.1036","url":null,"abstract":"In this paper, we proposed two new algorithms to address the task of multicriteria decision-making problems in which the criteria weights which have been unidentified, and alternatives are provided by triangular fuzzy numbers' linguistic values. A decision-making problem with assessments has been proposed on the basis of expected values. The expected values for two algorithms are calculated with two different 'Ranking Functions'. The weights are obtained by calculating the variance and mean of expected values with the aid of the triangular hesitant fuzzy decision matrix. The all alternatives ranking order is determined, and the maximum one is the best that can be identified easily. Lastly, a representative example is provided regarding the health issues of a community.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the impact of hybrid work models on employee well-being and engagement in modern organizational settings. Using a mixed-methods approach, the study examines the effects of hybrid work arrangements on various dimensions of employee well-being, including stress levels, work-life balance, and job satisfaction. Additionally, the study explores the relationship between hybrid work models and employee engagement, considering factors such as communication patterns, collaboration dynamics, and managerial support. The findings shed light on the implications of hybrid work for organizational practices and offer recommendations for optimizing employee well-being and engagement in hybrid work environments.
{"title":"The Impact of Hybrid Work Models on Employee Well-being and Engagement","authors":"T. Saritha, Dr. P. Akthar","doi":"10.52783/cana.v31.1003","DOIUrl":"https://doi.org/10.52783/cana.v31.1003","url":null,"abstract":"This study investigates the impact of hybrid work models on employee well-being and engagement in modern organizational settings. Using a mixed-methods approach, the study examines the effects of hybrid work arrangements on various dimensions of employee well-being, including stress levels, work-life balance, and job satisfaction. Additionally, the study explores the relationship between hybrid work models and employee engagement, considering factors such as communication patterns, collaboration dynamics, and managerial support. The findings shed light on the implications of hybrid work for organizational practices and offer recommendations for optimizing employee well-being and engagement in hybrid work environments.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The relationships among the objects in actual scenario are more complex than pairwise. Information loss will unavoidably result from naively condensing complicated relationships into pairwise ones. As a result, hypergraphs are necessary to depict the intricate interactions between the items of our interest, which leads to the issue of learning with hypergraphs. Intuitionistic Fuzzy Hypergraph defined in a time domain, termed as Temporal Intuitionistic Fuzzy Hypergraph (TIFHG) is introduced. Dual Temporal Intuitionistic Fuzzy Hypergraph has also been offered as a concept. An application of TIFHG in mobile communication is discussed.
{"title":"A Novel Application of Temporal Intuitionistic Fuzzy Hypergraphs in Mobile Networks","authors":"S.Jagadeesan","doi":"10.52783/cana.v31.1010","DOIUrl":"https://doi.org/10.52783/cana.v31.1010","url":null,"abstract":"The relationships among the objects in actual scenario are more complex than pairwise. Information loss will unavoidably result from naively condensing complicated relationships into pairwise ones. As a result, hypergraphs are necessary to depict the intricate interactions between the items of our interest, which leads to the issue of learning with hypergraphs. Intuitionistic Fuzzy Hypergraph defined in a time domain, termed as Temporal Intuitionistic Fuzzy Hypergraph (TIFHG) is introduced. Dual Temporal Intuitionistic Fuzzy Hypergraph has also been offered as a concept. An application of TIFHG in mobile communication is discussed.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A significant difficulty in WSN settings is recognizing the abnormalities as security threats become divergent in various fields. The major drawbacks of WSN including insufficient memory, limited energy, and low compute power, and a small communication range. Thus, enhancing the detection accuracy of intrusion detection in such contexts is critical. However, this work intends to propose intrusion detection in WSN with improved class imbalance processing. The input data is pre-processed to balance the data with modified class imbalance process. Here, the SMOTE-ENN and Tomek link algorithm is employed to pre-process the raw data. Then the entropy and improved correlation based features are retrieved from the balanced data. Later, these features are trained by subjecting those features into the hybrid model that includes Deep Maxout and Bi-GRU model and then the final detection is predicted with the classifier outcomes. Further, at the training rate 90%, the proposed yielded the least FPR rate (0.1038) than the other 60, 70 and 80 training percentages.
{"title":"Hybrid Model for Intrusion Detection in Wireless Sensor Network: An Improved Class Imbalance Processing","authors":"Sravanthi Godala, Dr. M. Sunil Kumar","doi":"10.52783/cana.v31.1006","DOIUrl":"https://doi.org/10.52783/cana.v31.1006","url":null,"abstract":"A significant difficulty in WSN settings is recognizing the abnormalities as security threats become divergent in various fields. The major drawbacks of WSN including insufficient memory, limited energy, and low compute power, and a small communication range. Thus, enhancing the detection accuracy of intrusion detection in such contexts is critical. However, this work intends to propose intrusion detection in WSN with improved class imbalance processing. The input data is pre-processed to balance the data with modified class imbalance process. Here, the SMOTE-ENN and Tomek link algorithm is employed to pre-process the raw data. Then the entropy and improved correlation based features are retrieved from the balanced data. Later, these features are trained by subjecting those features into the hybrid model that includes Deep Maxout and Bi-GRU model and then the final detection is predicted with the classifier outcomes. Further, at the training rate 90%, the proposed yielded the least FPR rate (0.1038) than the other 60, 70 and 80 training percentages.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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