S. Mangalampalli, Vamsi Krishna Mangalampalli, S. K. Swain
Rapid growth has been occurred in the IT industry with the emergence of Cloud computing in terms of the resources provisioned to the users in a seamless and flexible way. Task Scheduling is a prodigious challenge in the Cloud Computing. It is difficult to schedule the continuously varying requests to schedule on continuously varying resources. The existing approaches haven’t considered all the metrics while considering only the metrics like makespan and waiting time. In this paper, our focus is to formulate a Multi objective approach which is used to optimally map and load balance the tasks in the cloud by calculating the task priority and VM priority based on the electricity price per unit cost while minimizing the makespan, migration time and the power cost in the datacenters. The proposed algorithm is modeled using the hybridized approach by combining PSO and Cuckoo search algorithms. It is simulated on cloudsim simulator and it is compared against the basic ACO, GA, PSO and CS algorithms and our algorithm is outperformed against these basic algorithms with concerned parameters such as makespan, Migration time and the Total Power cost in the datacenters.
{"title":"Multi Objective Task Scheduling Algorithm in Cloud Computing Using the Hybridization of Particle Swarm Optimization and Cuckoo Search","authors":"S. Mangalampalli, Vamsi Krishna Mangalampalli, S. K. Swain","doi":"10.1166/JCTN.2020.9427","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9427","url":null,"abstract":"Rapid growth has been occurred in the IT industry with the emergence of Cloud computing in terms of the resources provisioned to the users in a seamless and flexible way. Task Scheduling is a prodigious challenge in the Cloud Computing. It is difficult to schedule the continuously varying\u0000 requests to schedule on continuously varying resources. The existing approaches haven’t considered all the metrics while considering only the metrics like makespan and waiting time. In this paper, our focus is to formulate a Multi objective approach which is used to optimally map and\u0000 load balance the tasks in the cloud by calculating the task priority and VM priority based on the electricity price per unit cost while minimizing the makespan, migration time and the power cost in the datacenters. The proposed algorithm is modeled using the hybridized approach by combining\u0000 PSO and Cuckoo search algorithms. It is simulated on cloudsim simulator and it is compared against the basic ACO, GA, PSO and CS algorithms and our algorithm is outperformed against these basic algorithms with concerned parameters such as makespan, Migration time and the Total Power cost in\u0000 the datacenters.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5346-5357"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48534318","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}
V. Kalpana, S. Shanthi, A. S. F. Britto, N. Prakash
Nowadays traffic congestion is major problem in all over the cities. The cities are renovated to “smart cities” by using Information and Communication Technologies (ICT). The IoT are playing a vital role in smart cities. This work proposes Internet of Thing (IoT) based smart traffic control signal using solar energy for smart cities. This signal is always coordinated with the emergency vehicle like ambulance to discover the signal and select the route where road traffic is dynamically controlled and the traffic violation vehicles are identified by traffic monitoring officers through internet. The traffic control signal lights are automatically controlled by Raspberry Pi controller with the help of IR sensor and RF signal. If any emergency vehicle will come nearby traffic control signal then the green signal shows for emergency vehicle and the remaining paths are shows as red signal.
{"title":"Internet of Thing Based Smart Traffic Control Signal Using Solar Energy","authors":"V. Kalpana, S. Shanthi, A. S. F. Britto, N. Prakash","doi":"10.1166/JCTN.2020.9425","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9425","url":null,"abstract":"Nowadays traffic congestion is major problem in all over the cities. The cities are renovated to “smart cities” by using Information and Communication Technologies (ICT). The IoT are playing a vital role in smart cities. This work proposes Internet of Thing (IoT) based smart\u0000 traffic control signal using solar energy for smart cities. This signal is always coordinated with the emergency vehicle like ambulance to discover the signal and select the route where road traffic is dynamically controlled and the traffic violation vehicles are identified by traffic monitoring\u0000 officers through internet. The traffic control signal lights are automatically controlled by Raspberry Pi controller with the help of IR sensor and RF signal. If any emergency vehicle will come nearby traffic control signal then the green signal shows for emergency vehicle and the remaining\u0000 paths are shows as red signal.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5334-5338"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46233585","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}
Purohit Om Hemantkumar, R. Lodha, Meghna Bajoria, R. Sujatha
Pneumonia is an infection caused by bacteria and viruses. It can shift from mellow to serious cases. This disease causes severe damages to the lungs since they fill with fluids. This situation causes difficulty in breathing. It further prevents oxygen to reach the blood. Pneumonia is diagnosed with the help of a chest X-rays, which can also use in the diagnosis of diseases like emphysema, lung cancer, and tuberculosis. According to WHO (World Health Organization (WHO). 2001. Standardization of Interpretation of Chest Radiographs for the Diagnosis of Pneumonia in Children. p.4.), Chest X-rays, at present, is the best available method for detecting pneumonia. Feature extraction methods like DiscreteWavelet Transform (DWT),Wavelet Frame Transform (WFT), andWavelet Packet Transform (WPT) can be used followed by any classification algorithm. In this paper, models like Squeezenet, DenseNet, and Resnet34 have been used for image recognition. In our system, the medical images were taken from Kaggle database and were recorded using a suitable imaging system. The images retrieved were then considered for input for the system where the images go through the various phases of image processing like pre-processing, edge detection and feature extraction. Later, a variety of training models are applied to know which model offers the highest accuracy.
{"title":"Pneumonia Detection Using Deep Learning Architectures","authors":"Purohit Om Hemantkumar, R. Lodha, Meghna Bajoria, R. Sujatha","doi":"10.1166/JCTN.2020.9450","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9450","url":null,"abstract":"Pneumonia is an infection caused by bacteria and viruses. It can shift from mellow to serious cases. This disease causes severe damages to the lungs since they fill with fluids. This situation causes difficulty in breathing. It further prevents oxygen to reach the blood. Pneumonia is\u0000 diagnosed with the help of a chest X-rays, which can also use in the diagnosis of diseases like emphysema, lung cancer, and tuberculosis. According to WHO (World Health Organization (WHO). 2001. Standardization of Interpretation of Chest Radiographs for the Diagnosis of Pneumonia in Children.\u0000 p.4.), Chest X-rays, at present, is the best available method for detecting pneumonia. Feature extraction methods like DiscreteWavelet Transform (DWT),Wavelet Frame Transform (WFT), andWavelet Packet Transform (WPT) can be used followed by any classification algorithm. In this paper, models\u0000 like Squeezenet, DenseNet, and Resnet34 have been used for image recognition. In our system, the medical images were taken from Kaggle database and were recorded using a suitable imaging system. The images retrieved were then considered for input for the system where the images go through\u0000 the various phases of image processing like pre-processing, edge detection and feature extraction. Later, a variety of training models are applied to know which model offers the highest accuracy.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5535-5542"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49055706","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 real time applications demands high speed and reliable data access from the remote database. An effective logical data management strategy that handles simultaneous connections with better performance negotiation is inevitable. This work considers an e-health care application that proposes MongoDB based modified indexing and performance tuning methods. To cope with certain high frequency use case and its performance mandates, a flexible and efficient logical data management may be preferred. By analysing the data dependency, data decomposition concerns and the performance requirements of the specific use case of the medical application, a logical schema may be customized on an ala-carte basis. This work focused on the flexible logical data modeling schemes and its performance factors of the NoSql DB. The efficiency of unstructured data base management in storing and retrieving the e-health care data was analysed with a web based tool. To enable faster data retrieval and query processing over the distributed nodes, a Spark based storage engine was built on top of the MongoDB based data storage management. With Spark tool, the database has been made distributed as master–slave structures with suitable data replication mechanisms. In such distributed database the fail-over also implemented with the suitable replication mechanism. This work considered MongoDB based flexible schema modeling and Spark based distributed computation with multiple chunks of data. The flexible data modeling scheme with MongoDB with the on-demand Spark based computation framework was proposed. To facilitate the eventual consistency, scalability aspects of the e-health care applications, use case based indexing was proposed. With the effective data management, faster query processing the horizontal scalability has been increased. The overall efficiency and scalability of the proposed logical data management approach was analysed. Through the simulation studies, the proposed approach has been claimed to boost the performance of the bigdata based application to a considerable extent.
{"title":"Modified Data Storage and Replication Mechanism with Frequent Use-Case Based Indexing","authors":"P. Selvaraj, V. Kannan, Bruno Voisin","doi":"10.1166/JCTN.2020.9413","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9413","url":null,"abstract":"The real time applications demands high speed and reliable data access from the remote database. An effective logical data management strategy that handles simultaneous connections with better performance negotiation is inevitable. This work considers an e-health care application that\u0000 proposes MongoDB based modified indexing and performance tuning methods. To cope with certain high frequency use case and its performance mandates, a flexible and efficient logical data management may be preferred. By analysing the data dependency, data decomposition concerns and the performance\u0000 requirements of the specific use case of the medical application, a logical schema may be customized on an ala-carte basis. This work focused on the flexible logical data modeling schemes and its performance factors of the NoSql DB. The efficiency of unstructured data base management in storing\u0000 and retrieving the e-health care data was analysed with a web based tool. To enable faster data retrieval and query processing over the distributed nodes, a Spark based storage engine was built on top of the MongoDB based data storage management. With Spark tool, the database has been made\u0000 distributed as master–slave structures with suitable data replication mechanisms. In such distributed database the fail-over also implemented with the suitable replication mechanism. This work considered MongoDB based flexible schema modeling and Spark based distributed computation with\u0000 multiple chunks of data. The flexible data modeling scheme with MongoDB with the on-demand Spark based computation framework was proposed. To facilitate the eventual consistency, scalability aspects of the e-health care applications, use case based indexing was proposed. With the effective\u0000 data management, faster query processing the horizontal scalability has been increased. The overall efficiency and scalability of the proposed logical data management approach was analysed. Through the simulation studies, the proposed approach has been claimed to boost the performance of the\u0000 bigdata based application to a considerable extent.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5229-5237"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49361864","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 Trusted Key Management Protocol (TKMP) provides one of the most secure communication technologies in MANET cluster-based data protection. For security reasons, TKMP is a trusted key that can be sent to all nodes in the communication cluster. This document introduces the Trusted Key Management Protocol (TKMP) feature to improve the quality of secure communications over a cluster-based wireless network. The proposed TKMP execution process includes CBPPRS (Cluster Based Privacy Preserving Routing Selection), LBCPR (Load Balancing Cluster Based Privacy Routing) and DLBPS (Dynamic Load Balancing Privacy Path Selection) procedure. To lock the data from the malicious node, the Paillier Cryptosystem (PC) encrypts packets with homomorphic encryption. The trust score makes it easier to update routing information and improves network throughput. The experimental results show that the proposed TKMP method works better than the other Trust-ECC method.
{"title":"An Implementation of Trusted Key Management Protocol (TKMP) in Wireless Network","authors":"R. Jayaprakash, B. Radha","doi":"10.1166/JCTN.2020.9415","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9415","url":null,"abstract":"The Trusted Key Management Protocol (TKMP) provides one of the most secure communication technologies in MANET cluster-based data protection. For security reasons, TKMP is a trusted key that can be sent to all nodes in the communication cluster. This document introduces the Trusted\u0000 Key Management Protocol (TKMP) feature to improve the quality of secure communications over a cluster-based wireless network. The proposed TKMP execution process includes CBPPRS (Cluster Based Privacy Preserving Routing Selection), LBCPR (Load Balancing Cluster Based Privacy Routing) and DLBPS\u0000 (Dynamic Load Balancing Privacy Path Selection) procedure. To lock the data from the malicious node, the Paillier Cryptosystem (PC) encrypts packets with homomorphic encryption. The trust score makes it easier to update routing information and improves network throughput. The experimental\u0000 results show that the proposed TKMP method works better than the other Trust-ECC method.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5243-5249"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47609736","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}
Tanzania is the regional gateway for a number of landlocked neighboring countries. Zambia, Burundi, Malawi, Congo, Rwanda and Uganda all rely to certain extent on the countries transport network, linking them to the global network. Railways are found to be the most effective transport system in Tanzania after-road transport system and it is Critical to long-haul freight along the main transport corridors of Tanzania. Most of the operations at Tanzania Railway Sector are manual system. For instance closing and opening of the gates are not automatic resulting in calamities and delays in the train’s advent. An innovative method to enhance railway safety measures is proposed in this Paper. This research paper proposes mechanisms which operate automatically without any 600073 intervention. Internet of Things (IoT) can be used to increase different features of the rail system. Automation of railways can transform the current legacy approaches and help decrease the railway related accidents considerably. Many challenges are underscored and dealt with in the proposed research. To summate, this paper aims at enhancing rail safety, minimizing accidents at unmanned level crossings, introducing smart railway gates, preventing calamity, and incorporating digital transformation through the use of IoT.
{"title":"Internet of Things (IoT) Based Automated Calamity Avoidance System for Railway Sectors","authors":"A. Ranjith, S. Vijayaragavan","doi":"10.1166/JCTN.2020.9433","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9433","url":null,"abstract":"Tanzania is the regional gateway for a number of landlocked neighboring countries. Zambia, Burundi, Malawi, Congo, Rwanda and Uganda all rely to certain extent on the countries transport network, linking them to the global network. Railways are found to be the most effective transport\u0000 system in Tanzania after-road transport system and it is Critical to long-haul freight along the main transport corridors of Tanzania. Most of the operations at Tanzania Railway Sector are manual system. For instance closing and opening of the gates are not automatic resulting in calamities\u0000 and delays in the train’s advent. An innovative method to enhance railway safety measures is proposed in this Paper. This research paper proposes mechanisms which operate automatically without any 600073 intervention. Internet of Things (IoT) can be used to increase different features\u0000 of the rail system. Automation of railways can transform the current legacy approaches and help decrease the railway related accidents considerably. Many challenges are underscored and dealt with in the proposed research. To summate, this paper aims at enhancing rail safety, minimizing accidents\u0000 at unmanned level crossings, introducing smart railway gates, preventing calamity, and incorporating digital transformation through the use of IoT.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5399-5408"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43322076","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}
Data in the Cloud, which applies to data as a cloud service provider (CSP), transmits stores, or manages it. The company will enforce the same definition of data usage while the data is resident within the enterprise and thus extend the required cryptographic security criteria to data collected, exchanged, or handled by CSP. The CSP Service Level Agreements cannot override the cryptographic access measures. When the data is transferred securely to CSP, it can be securely collected, distributed, and interpreted. Data at the rest position applies to data as it is processed internally in organized and in the unstructured ways like databases and file cabinets. The Data at the Rest example includes the use of cryptography for preserving the integrity of valuable data when processed. For cloud services, computing takes multiple forms from recording units, repositories, and many unstructured items. This paper presents a secure model for Data at rest. The TF-Sec model suggested is planned for use with Slicing, Tokenization, and Encryption. The model encrypts the given cloud data using AES 256 encryption, and then the encrypted block is sliced into the chunks of data fragments using HD-Slicer. Then it applies tokenization algorithm TKNZ to each chunk of data, applies erasure coding technique to tokens, applies the data dispersion technique to scramble encrypted data fragments, and allocates to storage nodes of the multiple CSP. In taking the above steps, this study aims to resolve the cloud security problems found and to guarantee the confidentiality of their data to cloud users due to encryption of data fragments would be of little benefit to a CSP.
{"title":"Slicing, Tokenization, and Encryption Based Combinational Approach to Protect Data-at-Rest in Cloud Using TF-Sec Model","authors":"N. Keerthana, Viji Vinod, Sudhakar Sengan","doi":"10.1166/JCTN.2020.9421","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9421","url":null,"abstract":"Data in the Cloud, which applies to data as a cloud service provider (CSP), transmits stores, or manages it. The company will enforce the same definition of data usage while the data is resident within the enterprise and thus extend the required cryptographic security criteria to data\u0000 collected, exchanged, or handled by CSP. The CSP Service Level Agreements cannot override the cryptographic access measures. When the data is transferred securely to CSP, it can be securely collected, distributed, and interpreted. Data at the rest position applies to data as it is processed\u0000 internally in organized and in the unstructured ways like databases and file cabinets. The Data at the Rest example includes the use of cryptography for preserving the integrity of valuable data when processed. For cloud services, computing takes multiple forms from recording units, repositories,\u0000 and many unstructured items. This paper presents a secure model for Data at rest. The TF-Sec model suggested is planned for use with Slicing, Tokenization, and Encryption. The model encrypts the given cloud data using AES 256 encryption, and then the encrypted block is sliced into the chunks\u0000 of data fragments using HD-Slicer. Then it applies tokenization algorithm TKNZ to each chunk of data, applies erasure coding technique to tokens, applies the data dispersion technique to scramble encrypted data fragments, and allocates to storage nodes of the multiple CSP. In taking the above\u0000 steps, this study aims to resolve the cloud security problems found and to guarantee the confidentiality of their data to cloud users due to encryption of data fragments would be of little benefit to a CSP.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5296-5306"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43531499","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 IoT (Internet of Thing) envisage is the unified interlinking to the fake space and the physical planet. This offers an encouraging chance to build influential facilities and services provided by the applications for industrial production. This article offers an overview of major research problems that need to be adopted and the latest developments in that field of IoT-aided industrial production. Initially, the core technologies of IoT like Big information, Cloud computer, Wireless antenna Network, and Radio Incidence Identification has been described. Then certain key research problems of IoT-aided industrial production has been described in accordance with architecture, implementation and enterprise model, data collection and handling, reduction of latency with state-of-theart reviews, user-centric pervasive environment, dynamic service composition, and model-based decision-making. At last, some possible application fields of IoT in the industrial sector have been described.
物联网(Internet of Thing)设想的是虚拟空间和物理星球的统一互联。这为建立工业生产应用程序提供的有影响力的设施和服务提供了一个令人鼓舞的机会。本文概述了物联网辅助工业生产领域需要采用的主要研究问题以及该领域的最新进展。初步阐述了物联网的大信息、云计算机、无线天线网络、无线射频识别等核心技术。然后，从物联网辅助工业生产的体系结构、实现与企业模型、数据采集与处理、基于状态评审的延迟降低、以用户为中心的普及环境、动态服务组合、基于模型的决策等方面阐述了物联网辅助工业生产的若干关键研究问题。最后，对物联网在工业领域的应用前景进行了展望。
{"title":"Analysis of Internet of Thing in Smart Manufacturing Industry","authors":"M. Dharmalingam, B. Umarani, R. Shankar, K. Kumar","doi":"10.1166/JCTN.2020.9444","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9444","url":null,"abstract":"The IoT (Internet of Thing) envisage is the unified interlinking to the fake space and the physical planet. This offers an encouraging chance to build influential facilities and services provided by the applications for industrial production. This article offers an overview of major\u0000 research problems that need to be adopted and the latest developments in that field of IoT-aided industrial production. Initially, the core technologies of IoT like Big information, Cloud computer, Wireless antenna Network, and Radio Incidence Identification has been described. Then certain\u0000 key research problems of IoT-aided industrial production has been described in accordance with architecture, implementation and enterprise model, data collection and handling, reduction of latency with state-of-theart reviews, user-centric pervasive environment, dynamic service composition,\u0000 and model-based decision-making. At last, some possible application fields of IoT in the industrial sector have been described.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5495-5502"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46134113","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}
Network Lifetime of sensor node plays a fundamental role in Wireless Sensor Networks, since they drain out energy during the communication. The hierarchical networks assist in hindering energy loss by exchanging the information at various levels. The Hierarchical levels formed avoid overburdening of single level cluster zones and helps the network to retain energy of cluster level heads. Malicious attack disturbs the regular functionality of a routing algorithm and deviates QoS performance in the network. The existing LEACH-Mobile protocol adopts low energy clustering techniques but, falls short in providing security of the network when there is malicious attack. The proposed Trust Computation for Hierarchical Clustering Network protocol proves itself to be trustworthy by having various trust measuring metrics. It enhances the lifetime by adopting low energy hierarchical protocol and shows improvement of 12% in terms of energy consumption.
{"title":"TCHCN: Trust Computation for Hierarchical Clustering Network to Improve Network Lifetime in Wireless Sensor Network","authors":"P. Manasa, K. Shaila, K. Venugopal","doi":"10.1166/JCTN.2020.9446","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9446","url":null,"abstract":"Network Lifetime of sensor node plays a fundamental role in Wireless Sensor Networks, since they drain out energy during the communication. The hierarchical networks assist in hindering energy loss by exchanging the information at various levels. The Hierarchical levels formed avoid\u0000 overburdening of single level cluster zones and helps the network to retain energy of cluster level heads. Malicious attack disturbs the regular functionality of a routing algorithm and deviates QoS performance in the network. The existing LEACH-Mobile protocol adopts low energy clustering\u0000 techniques but, falls short in providing security of the network when there is malicious attack. The proposed Trust Computation for Hierarchical Clustering Network protocol proves itself to be trustworthy by having various trust measuring metrics. It enhances the lifetime by adopting low energy\u0000 hierarchical protocol and shows improvement of 12% in terms of energy consumption.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5509-5515"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44616309","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 problem of child health management and development has been well studied. There are number of methods available for the problem of child health development but suffers to achieve higher performance. To improve the performance, an efficient real time child infant mortality analysis for improved health development using multi feature covariance measure (MFCM). The method maintains number of data records of various child and infants from the age of 1 month to 15 years. For each child or infant, the method maintains continuous records of their health diagnosis. Using the data maintained, the method identifies and groups them according to the cause of death. Using the cluster generated, the method estimates health factor influence (HFI) for different features. Based on the value of HFI, a set of features which has higher HFI are selected and used to generate analysis. Further the method generates a prediction result on the future mortality and the reasons. The method improves the performance of mortality prediction and increases the accuracy also.
{"title":"Real Time Child Infant Mortality Analysis for Efficient Public Health Development","authors":"K. Sudha, G. Venkatesan","doi":"10.1166/JCTN.2020.9419","DOIUrl":"https://doi.org/10.1166/JCTN.2020.9419","url":null,"abstract":"The problem of child health management and development has been well studied. There are number of methods available for the problem of child health development but suffers to achieve higher performance. To improve the performance, an efficient real time child infant mortality analysis\u0000 for improved health development using multi feature covariance measure (MFCM). The method maintains number of data records of various child and infants from the age of 1 month to 15 years. For each child or infant, the method maintains continuous records of their health diagnosis. Using the\u0000 data maintained, the method identifies and groups them according to the cause of death. Using the cluster generated, the method estimates health factor influence (HFI) for different features. Based on the value of HFI, a set of features which has higher HFI are selected and used to generate\u0000 analysis. Further the method generates a prediction result on the future mortality and the reasons. The method improves the performance of mortality prediction and increases the accuracy also.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5270-5278"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43293232","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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