B. D. Martino, Luigi Colucci Cante, Salvatore D'Angelo, A. Esposito, Mariangela Graziano, F. Marulli, Pietro Lupi, Alessandra Cataldi
In this paper a Big Data Pipeline is presented, taking in consideration both structured and unstructured data made available by the Italian Ministry of Justice, regarding their Telematic Civil Process. Indeed, the complexity and volume of the data provided by the Ministry requires the application of Big Data analysis techniques, in concert with Machine and Deep Learning frameworks, to be correctly analysed and to obtain meaningful information that could support the Ministry itself in better managing Civil Processes. The Pipeline has two main objectives: to provide a consistent workflow of activities to be applied to the incoming data, aiming at extracting useful information for the Ministry's decision making tasks; to homogenize the incoming data, so that they can be stored in a centralized and coherent Datalake to be used as a reference for further analysis and considerations.
{"title":"A Big Data Pipeline and Machine Learning for Uniform Semantic Representation of Data and Documents From IT Systems of the Italian Ministry of Justice","authors":"B. D. Martino, Luigi Colucci Cante, Salvatore D'Angelo, A. Esposito, Mariangela Graziano, F. Marulli, Pietro Lupi, Alessandra Cataldi","doi":"10.4018/ijghpc.301579","DOIUrl":"https://doi.org/10.4018/ijghpc.301579","url":null,"abstract":"In this paper a Big Data Pipeline is presented, taking in consideration both structured and unstructured data made available by the Italian Ministry of Justice, regarding their Telematic Civil Process. Indeed, the complexity and volume of the data provided by the Ministry requires the application of Big Data analysis techniques, in concert with Machine and Deep Learning frameworks, to be correctly analysed and to obtain meaningful information that could support the Ministry itself in better managing Civil Processes. The Pipeline has two main objectives: to provide a consistent workflow of activities to be applied to the incoming data, aiming at extracting useful information for the Ministry's decision making tasks; to homogenize the incoming data, so that they can be stored in a centralized and coherent Datalake to be used as a reference for further analysis and considerations.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"55 6 1","pages":"1-31"},"PeriodicalIF":1.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79117506","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}
Pub Date : 2021-10-01DOI: 10.4018/IJGHPC.2021100105
D. Rajput, Praveen Kumar Reddy Maddikunta, Ramasubbareddy Somula, S. BharathBhushan, Ravi Kumar Poluru
{"title":"A Novel Architectural Model for Dynamic Updating and Verification of Data Storage in Cloud Environment","authors":"D. Rajput, Praveen Kumar Reddy Maddikunta, Ramasubbareddy Somula, S. BharathBhushan, Ravi Kumar Poluru","doi":"10.4018/IJGHPC.2021100105","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021100105","url":null,"abstract":"","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"22 4 1","pages":"75-83"},"PeriodicalIF":1.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80048038","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}
Pub Date : 2021-10-01DOI: 10.4018/IJGHPC.2021100102
Srinivasan Palanisamy, S. Sankar, Ramasubbareddy Somula, G. Deverajan
{"title":"Communication Trust and Energy-Aware Routing Protocol for WSN Using D-S Theory","authors":"Srinivasan Palanisamy, S. Sankar, Ramasubbareddy Somula, G. Deverajan","doi":"10.4018/IJGHPC.2021100102","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021100102","url":null,"abstract":"","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"17 1","pages":"24-36"},"PeriodicalIF":1.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82671310","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}
Pub Date : 2021-10-01DOI: 10.4018/IJGHPC.2021100104
C. Ramesh, K. Santhiya, R. Sakthivel, Rizwan Patan
{"title":"Game the Oretic Approach for Cloud Service Negotiation","authors":"C. Ramesh, K. Santhiya, R. Sakthivel, Rizwan Patan","doi":"10.4018/IJGHPC.2021100104","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021100104","url":null,"abstract":"","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"83 1","pages":"65-74"},"PeriodicalIF":1.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76854135","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}
Pub Date : 2021-10-01DOI: 10.4018/IJGHPC.2021100103
D. Sumathi, S. Manivannan
{"title":"Analyzing Cognitive Radio Network Operation With the Mechanism of Deciding Handoff and Process of Handoff Employing Varied Distribution Models (5G)","authors":"D. Sumathi, S. Manivannan","doi":"10.4018/IJGHPC.2021100103","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021100103","url":null,"abstract":"","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"128 12 1","pages":"37-64"},"PeriodicalIF":1.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85534187","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}
Pub Date : 2021-10-01DOI: 10.4018/IJGHPC.2021100101
G. Siddesh, K. Srinivasa
{"title":"IoT Solution for Enhancing the Quality of Life of Visually Impaired People","authors":"G. Siddesh, K. Srinivasa","doi":"10.4018/IJGHPC.2021100101","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021100101","url":null,"abstract":"","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"27 1","pages":"1-23"},"PeriodicalIF":1.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88938354","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}
Pub Date : 2021-07-01DOI: 10.4018/IJGHPC.2021070104
Che-nan Yang, Li-Chi Ku, Jiunn-Jye Chen
The deployment of an automatic network performance measurement system is crucial to the early detection and analysis of network quality degradations and failures. Once the overall network health status can be summarized and visualized in an easily accessible graphic user interface, the difficulty of network maintenance and troubleshooting can be significantly reduced. This study provided a detailed introduction to how the perfSONAR is implemented in TWAREN backbone and how the individual data are integrated and eventually visualized as a handy weathermap for network operators to use.
{"title":"A perfSONAR-Based Network Performance Weathermap System","authors":"Che-nan Yang, Li-Chi Ku, Jiunn-Jye Chen","doi":"10.4018/IJGHPC.2021070104","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021070104","url":null,"abstract":"The deployment of an automatic network performance measurement system is crucial to the early detection and analysis of network quality degradations and failures. Once the overall network health status can be summarized and visualized in an easily accessible graphic user interface, the difficulty of network maintenance and troubleshooting can be significantly reduced. This study provided a detailed introduction to how the perfSONAR is implemented in TWAREN backbone and how the individual data are integrated and eventually visualized as a handy weathermap for network operators to use.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"57 1","pages":"43-55"},"PeriodicalIF":1.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84103426","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}
Pub Date : 2021-04-01DOI: 10.4018/IJGHPC.2021040101
T. Amarasimha, V. Rao
Wireless sensor networks are used in machine learning for data communication and classification. Sensor nodes in network suffer from low battery power, so it is necessary to reduce energy consumption. One way of decreasing energy utilization is reducing the information transmitted by an advanced machine learning process called support vector machine. Further, nodes in WSN malfunction upon the occurrence of malicious activities. To overcome these issues, energy conserving and faulty node detection WSN is proposed. SVM optimizes data to be transmitted via one-hop transmission. It sends only the extreme points of data instead of transmitting whole information. This will reduce transmitting energy and accumulate excess energy for future purpose. Moreover, malfunction nodes are identified to overcome difficulties on data processing. Since each node transmits data to nearby nodes, the misbehaving nodes are detected based on transmission speed. The experimental results show that proposed algorithm provides better results in terms of reduced energy consumption and faulty node detection.
{"title":"Efficient Energy Conservation and Faulty Node Detection on Machine Learning-Based Wireless Sensor Networks","authors":"T. Amarasimha, V. Rao","doi":"10.4018/IJGHPC.2021040101","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021040101","url":null,"abstract":"Wireless sensor networks are used in machine learning for data communication and classification. Sensor nodes in network suffer from low battery power, so it is necessary to reduce energy consumption. One way of decreasing energy utilization is reducing the information transmitted by an advanced machine learning process called support vector machine. Further, nodes in WSN malfunction upon the occurrence of malicious activities. To overcome these issues, energy conserving and faulty node detection WSN is proposed. SVM optimizes data to be transmitted via one-hop transmission. It sends only the extreme points of data instead of transmitting whole information. This will reduce transmitting energy and accumulate excess energy for future purpose. Moreover, malfunction nodes are identified to overcome difficulties on data processing. Since each node transmits data to nearby nodes, the misbehaving nodes are detected based on transmission speed. The experimental results show that proposed algorithm provides better results in terms of reduced energy consumption and faulty node detection.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"283 1","pages":"1-20"},"PeriodicalIF":1.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76837668","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}
Pub Date : 2021-04-01DOI: 10.4018/IJGHPC.2021040103
Nabil Kadache, Rachid Seghir
Volunteer computing (VC) has become a relatively mature technique of distributed computing. It is based on exploiting the idle time of ordinary online machines with the consent of their owners. Target applications are generally scientific projects requiring a huge amount of computational resources. Existing VC platforms raise several challenges. This work attempts to bring solutions for two defeats. The first one is the involvement of volunteers; the decreasing of participants affects the global performances. To cope with this, a new social volunteer computing environment is proposed in order to involve more volunteers. The second addressed problem is the task scheduling, which aims to optimize the use of resources. The proposed algorithm generates for each resource's class, a number of tasks whose cost of execution reflects the momentary capacity of the resources. The new solutions are validated through a theory of number's project, called “Collatz Conjecture.”
{"title":"A New Social Volunteer Computing Environment With Task-Adapted Scheduling Policy (TASP)","authors":"Nabil Kadache, Rachid Seghir","doi":"10.4018/IJGHPC.2021040103","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021040103","url":null,"abstract":"Volunteer computing (VC) has become a relatively mature technique of distributed computing. It is based on exploiting the idle time of ordinary online machines with the consent of their owners. Target applications are generally scientific projects requiring a huge amount of computational resources. Existing VC platforms raise several challenges. This work attempts to bring solutions for two defeats. The first one is the involvement of volunteers; the decreasing of participants affects the global performances. To cope with this, a new social volunteer computing environment is proposed in order to involve more volunteers. The second addressed problem is the task scheduling, which aims to optimize the use of resources. The proposed algorithm generates for each resource's class, a number of tasks whose cost of execution reflects the momentary capacity of the resources. The new solutions are validated through a theory of number's project, called “Collatz Conjecture.”","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"45 1","pages":"39-55"},"PeriodicalIF":1.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88909531","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}
Pub Date : 2021-04-01DOI: 10.4018/IJGHPC.2021040104
Zhifeng Zhang, Junxia Ma, Xiao Cui
In recent years, with the growing expansion of the recruitment scale and the further reform in teaching, how to use the limited teacher resources and the limited classroom resources to schedule a reasonable university course timetable has gotten great interest. In this paper, the authors firstly hashed over the university course timetabling problem, and then they presented the related mathematical model and constructed the relevant solution framework. Subsequently, in view of characteristics of the university course timetabling problem, they introduced genetic algorithm to solve the university course timetabling problem and proposed many improvement strategies which include the three-dimensional coding strategy, the fitness function design strategy, the initial population generation strategy, the population dominance strategy, the adaptive crossover probability strategy, and the adaptive mutation probability strategy to optimize genetic algorithm. Simulation results show that the proposed genetic algorithm can solve the university course timetabling problem effectively.
{"title":"Genetic Algorithm With Three-Dimensional Population Dominance Strategy for University Course Timetabling Problem","authors":"Zhifeng Zhang, Junxia Ma, Xiao Cui","doi":"10.4018/IJGHPC.2021040104","DOIUrl":"https://doi.org/10.4018/IJGHPC.2021040104","url":null,"abstract":"In recent years, with the growing expansion of the recruitment scale and the further reform in teaching, how to use the limited teacher resources and the limited classroom resources to schedule a reasonable university course timetable has gotten great interest. In this paper, the authors firstly hashed over the university course timetabling problem, and then they presented the related mathematical model and constructed the relevant solution framework. Subsequently, in view of characteristics of the university course timetabling problem, they introduced genetic algorithm to solve the university course timetabling problem and proposed many improvement strategies which include the three-dimensional coding strategy, the fitness function design strategy, the initial population generation strategy, the population dominance strategy, the adaptive crossover probability strategy, and the adaptive mutation probability strategy to optimize genetic algorithm. Simulation results show that the proposed genetic algorithm can solve the university course timetabling problem effectively.","PeriodicalId":43565,"journal":{"name":"International Journal of Grid and High Performance Computing","volume":"61 1","pages":"56-69"},"PeriodicalIF":1.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77764712","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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