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Author: search.filters.author.Benjangkaprasert, ChawalitSubject: search.filters.subject.Cloud Computing

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    Centralizing Data Warehouse Platform for Mining Management Using AWS Computing Instance
    (2024-01-01)
    Sathaporn, Posathip
    ;
    Chaowalittawin, Vasutorn
    ;
    Krungseanmuang, Woranidtha
    ;
    Benjangkaprasert, Chawalit
    ;
    Purahong, Boonchana
    Mining industry is one of significant industry in the world. In order to increase efficiency, safety, sustainability and environmental impacts in mining process. This article presents a centralized data platform for mining process by design based on microservices architecture which can be supported various of input data source such as manual form, excel file and internet of things (IoT) device and notification when the value is abnormal. Our platform implementation on Amazon Web Service (AWS) cloud. For development of productivity in process and controlling quality the mine environment. The results of the platform operations with various source of data acquisition with response time is less than 1.5 seconds per each request.
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    Implementation of Cloud Computing and Internet of Things (IoT) by Performance Evaluation
    (2024-01-01)
    Sithiyopasakul, Jiran
    ;
    Archevapanich, Tuanjai
    ;
    Sithiyopasakul, Saran
    ;
    Lasakul, Attasit
    ;
    Purahong, Boonchana
    The integration of cloud computing and the Internet of Things (IoT) holds transformative potential across diverse industries. Performance assessment is essential to gauge the quality and efficiency of cloud computing and IoT systems. This paper presents a comprehensive performance evaluation of cloud computing and IoT systems, focusing on three major platforms: Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Experimental results encompass various scenarios, including normal operation, heavy load conditions, IoT applications, and scalability testing. The outcomes reveal distinct performance metrics such as response time, throughput, latency, and reliability for each cloud platform.
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    Performance Evaluation of Infrastructure as a Service across Cloud Service Providers
    (2023-01-01)
    Sithiyopasakul, Saran
    ;
    Archevapanich, Tuanjai
    ;
    Purahong, Boonchana
    ;
    Sithiyopasakul, Paisan
    ;
    Lasakul, Attasit
    The purpose of this research aims to monitor, analyze, and compare the performance of infrastructure as a service (IaaS) between the selective cloud providers. To assure which cloud provider has more stability, reliability, and scalability. This paper focuses on performance testing based on a deployed web server in the cloud environment. The main feature of cloud computing is scalability thus most common IaaS cloud service providers (CSPs) have Auto Scaling features for instances or virtual machines. Not only does this paper gives the experimental results of the scaling scalability testing, but it also provides the results of recovery testing to inspect how long a web server is able to recover from failures and load testing which simulated traffic requests. Testing was conducted in the major public clouds of Google Cloud Platform (GCP), Microsoft Azure, and Amazon Web Services (AWS). Azure performs the most efficiently of almost all testing but hardest to configure.