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Journal articles on the topic 'Monitoraggio,Raspberry Pi,cluster'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

Papakyriakou, Dimitrios, Dimitra Kottou, and Ioannis Kostouros. "Benchmarking Raspberry Pi 2 Beowulf Cluster." International Journal of Computer Applications 179, no. 32 (2018): 21–27. http://dx.doi.org/10.5120/ijca2018916728.

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2

Papakyriakou, Dimitrios. "Benchmarking Raspberry Pi 2 Hadoop Cluster." International Journal of Computer Applications 178, no. 42 (2019): 37–47. http://dx.doi.org/10.5120/ijca2019919328.

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3

Abdulhamid, Mohanad, and Mwalimu Muthami. "Design of Raspberry PI Parallel Processor." Scientific Bulletin 25, no. 2 (2020): 63–74. http://dx.doi.org/10.2478/bsaft-2020-0009.

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AbstractAs data centers have increased in size, there has been a need to create clusters out of cheaper, more affordable commodity parts that can easily be replaced upon failure, and that create more affordable data centers overall. However, such large clusters are still outside of feasibility for individuals and small businesses. It is a worthwhile exercise to see if much smaller clusters could be created for such applications, and to compare their performance / price measure to that of the previous traditional data centers. For this paper, such a cluster is created using Raspberry Pis which

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Singh, Mr Raghvendra Omprakash. "Cluster Computing using Raspberry PI -3 with Python Programming." International Journal for Research in Applied Science and Engineering Technology 7, no. 5 (2019): 269–71. http://dx.doi.org/10.22214/ijraset.2019.5043.

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Babchuk, S. M., Т. V. Humeniuk, and I. T. Romaniv. "MATHEMATICAL MODELS PRODUCTIVITY OF CLUSTER SYSTEM BASED ON RASPBERRY PI 3B+." Radio Electronics, Computer Science, Control 1, no. 1 (2021): 46–56. http://dx.doi.org/10.15588/1607-3274-2021-1-5.

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Context. High-performance computing systems are needed to solve many scientific problems and to work with complex applied problems. Previously, real parallel data processing was supported only by supercomputers, which are very limited and difficult to access. Currently, one way to solve this problem is to build small, cheap clusters based on single-board computers Raspberry Pi. Objective. The goal of the work is the creation of a complex criterion for the efficiency of the cluster system, which could properly characterize the operation of such a system and find the dependences of the per

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Myint, Khin Nyein, Myo Hein Zaw, and Win Thanda Aung. "Parallel and Distributed Computing Using MPI on Raspberry Pi Cluster." International Journal of Future Computer and Communication 9, no. 1 (2020): 18–22. http://dx.doi.org/10.18178/ijfcc.2020.9.1.559.

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Cloutier, Michael, Chad Paradis, and Vincent Weaver. "A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement." Electronics 5, no. 4 (2016): 61. http://dx.doi.org/10.3390/electronics5040061.

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Sujana, Aprianti Putri. "Implementasi Cluster Server Pada Raspberry Pi Dengan Menggunakan Metode Load Balancing." Komputika : Jurnal Sistem Komputer 8, no. 1 (2019): 37–43. http://dx.doi.org/10.34010/komputika.v8i1.1623.

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Ketika server mengalami overload, hal ini akan membuat server melambat, efeknya adalah waktu akses layanan bertambah yang akan membuat client tidak nyaman dalam menggunakan layanan yang ada pada server. Cluster server menawarkan solusi agar beban terbagi secara merata, sistem ini memanfaatkan beberapa komputer yang di konfigurasi sedemikian rupa agar dapat berkerja bersama-sama. Hasil dari pengujian cluster server menunjukan peningkatan waktu respon http request sebesar 59% lebih cepat dibandingkan tanpa menggunakan sistem cluster server. Keuntungan lain menggunakan cluster server adalah adany

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Rohadi, E., A. Amalia, A. Prasetyo, M. F. Rahmat, A. Setiawan, and I. Siradjuddin. "Cluster implementation on mini Raspberry Pi computers using Round Robin Algorithm." Journal of Physics: Conference Series 1450 (February 2020): 012068. http://dx.doi.org/10.1088/1742-6596/1450/1/012068.

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10

Kim, Woojae, and Inbum Jung. "Simulator for Interactive and Effective Organization of Things in Edge Cluster Computing." Sensors 21, no. 8 (2021): 2616. http://dx.doi.org/10.3390/s21082616.

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Edge computing is intended to process events that occur at the endpoint of the Internet of Things (IoT) network quickly and intelligently. Edge regions must be organized effectively to facilitate cooperation so that the intention of edge computing can be realized. However, inevitably, many human and material resources are required in the process of arranging things in the edge area to confirm the appropriateness of the thing operation. To address this problem, we proposed a simulator that created a virtual space for edge computing and provided an interactive role and effective organization for

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Ağbahca, Erdem, and Adem Alpaslan Altun. "Parallel Performance of Mandelbrot Set Generation Using MPI On Raspberry Pi 2 Beowulf Cluster." Journal of Engineering and Fundamentals 3, no. 1 (2016): 31–36. http://dx.doi.org/10.17530/jef.16.05.3.1.

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Bernabé, Gregorio, Raúl Hernández, and Manuel E. Acacio. "Parallel implementations of the 3D fast wavelet transform on a Raspberry Pi 2 cluster." Journal of Supercomputing 74, no. 4 (2016): 1765–78. http://dx.doi.org/10.1007/s11227-016-1933-2.

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13

Arief Prasetyo, Sofyan Noor Arief, and Rokhimatul wakhidah. "OPTIMASI PEMROSESAN ENKRIPSI DAN DEKRIPSI RSA PADA SINGLE BOARD COMPUTER (SBC) DENGAN PEMBAGIAN BEBAN KOMPUTASI DALAM SISTEM TERDISTRIBUSI." Jurnal Informatika Polinema 7, no. 4 (2021): 7–12. http://dx.doi.org/10.33795/jip.v7i4.523.

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Algoritma kriptografi RSA menjadi metode yang paling sulit diretas karena kerumitan persamaan matematis yang digunakan. Semakin rumit persamaan matematis yang digunakan, semakin besar pula daya komputasi yang digunakan untuk memproses algoritma tersebut. Penggunaan Single-Board Computer (SBC) mulai digunakan untuk menggantikan alat pemrosesan komputasi seperti komputer personal baik berupa laptop maupun workstation. Penetlitian ini bertujuan untuk mengetahui hasil optimasi pemroresan enkirpsi dan dekripsi RSA menggunakan SBC yang tersusun sebagai bentuk cluster. Metode yang digunakan adalah me

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Liu, Peng, Jongwon Yoon, Ha Ryung Kim, and Suman Banerjee. "VideoCoreCluster: Energy-Efficient, Low-Cost, and Hardware-Assisted Video Transcoding System." Wireless Communications and Mobile Computing 2018 (June 5, 2018): 1–13. http://dx.doi.org/10.1155/2018/7470234.

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Video streaming is one of the killer applications in recent years. Video transcoding plays an important role in the video streaming service to cope with the various purposes. Specifically, content owners and publishers heavily utilize video transcoders to reconfigure source video in a variety of formats, video qualities, and bitrate to provide end users with the best possible quality of service. In this paper, we present VideoCoreCluster, a low-cost and energy-efficient transcoder cluster that is suitable for live streaming services. We designed and implemented real-time video transcoder clust

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Penas-Noce, Javier, Óscar Fontenla-Romero, and Bertha Guijarro-Berdiñas. "A Machine Learning Solution for Distributed Environments and Edge Computing." Proceedings 21, no. 1 (2019): 47. http://dx.doi.org/10.3390/proceedings2019021047.

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In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive and of reduced size. Moreover, they should operate in a distributed manner making use of edge computing capabilities while preserving local data privacy. The aim of this work is to provide a solution offering all these features by implementing the algorithm LANN-DSVD over a cluster of Raspberry Pi devices. In this system, every node first learns locally a one-layer neural network. Later

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Großmann, Marcel, Steffen Illig, and Cornelius L. Matějka. "SensIoT: An Extensible and General Internet of Things Monitoring Framework." Wireless Communications and Mobile Computing 2019 (March 7, 2019): 1–15. http://dx.doi.org/10.1155/2019/4260359.

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SensIoT is an open-source sensor monitoring framework for the Internet of Things, which utilizes proven technologies to enable easy deployment and maintenance while staying flexible and scalable. It closes the gap between highly specialized and, therefore, inflexible sensor monitoring solutions, which are only adjusted to a specific context, and the development of every other solution from scratch. Our framework fits a variety of use cases by providing an easy to set up, extensible, and affordable solution. The development is based on our former published framework MonTreAL, whose goal is to o

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Huang, Xu, Hasnain Cheena, Abin Thomas, and Joseph K. P. Tsoi. "Indoor Detection and Tracking of People Using mmWave Sensor." Journal of Sensors 2021 (February 2, 2021): 1–14. http://dx.doi.org/10.1155/2021/6657709.

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This paper proposes a new indoor people detection and tracking system using a millimeter-wave (mmWave) radar sensor. Firstly, a systematic approach for people detection and tracking is presented—a static clutter removal algorithm used for removing mmWave radar data’s static points. Two efficient clustering algorithms are used to cluster and identify people in a scene. The recursive Kalman filter tracking algorithm with data association is used to track multiple people simultaneously. Secondly, a fast indoor people detection and tracking system is designed based on our proposed algorithms. The

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18

Fayos-Jordan, Rafael, Santiago Felici-Castell, Jaume Segura-Garcia, Adolfo Pastor-Aparicio, and Jesus Lopez-Ballester. "Elastic Computing in the Fog on Internet of Things to Improve the Performance of Low Cost Nodes." Electronics 8, no. 12 (2019): 1489. http://dx.doi.org/10.3390/electronics8121489.

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The Internet of Things (IoT) is a network widely used with the purpose of connecting almost everything, everywhere to the Internet. To cope with this goal, low cost nodes are being used; otherwise, it would be very expensive to expand so fast. These networks are set up with small distributed devices (nodes) that have a power supply, processing unit, memory, sensors, and wireless communications. In the market, we can find different alternatives for these devices, such as small board computers (SBCs), e.g., Raspberry Pi (RPi)), with different features. Usually these devices run a coarse version

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19

Horton, Pascal. "AtmoSwing: Analog Technique Model for Statistical Weather forecastING and downscalING (v2.1.0)." Geoscientific Model Development 12, no. 7 (2019): 2915–40. http://dx.doi.org/10.5194/gmd-12-2915-2019.

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Abstract. Analog methods (AMs) use synoptic-scale predictors to search in the past for similar days to a target day in order to infer the predictand of interest, such as daily precipitation. They can rely on outputs of numerical weather prediction (NWP) models in the context of operational forecasting or outputs of climate models in the context of climate impact studies. AMs require low computing capacity and have demonstrated useful potential for application in several contexts. AtmoSwing is open-source software written in C++ that implements AMs in a flexible way so that different variants c

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Marković, Dušan, Dejan Vujičić, Dragana Mitrović, and Siniša Ranđić. "Image Processing on Raspberry Pi Cluster." IJEEC - INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTING 2, no. 2 (2019). http://dx.doi.org/10.7251/ijeec1802083m.

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The development direction of the high-performance computing has been primarily oriented toward improvements in thenumber of computing units, and their better organization and interconnection. The central processing units in modern mainframes arein some cases inadequate for data parallelization, because a large amount of data requires a large number of processing units. Thisproblem can be partially overcome by introducing embedded devices with enough processing power and with smaller power dissipation,but the new problems emerge, specifically the problem of their interconnection in a distribute

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21

Putra, Ridho Habi, and Winarno Sugeng. "Implementasi Cluster Server pada Raspberry Pi dengan Menggunakan Metode Load Balancing." Jurnal Edukasi dan Penelitian Informatika (JEPIN) 2, no. 1 (2016). http://dx.doi.org/10.26418/jp.v2i1.14988.

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Server merupakan bagian penting dalam sebuah layanan didalam jaringan komputer. Peran server dapat menentukan kualitas baik buruknya dari layanan tersebut. Kegagalan dari sebuah server bisa disebabkan oleh beberapa faktor diantaranya kerusakan perangkat keras, sistem jaringan serta aliran listrik. Salah satu solusi untuk mengatasi kegagalan server dalam suatu jaringan komputer adalah dengan melakukan clustering server. Tujuan dari penelitian ini adalah untuk mengukur kemampuan Raspberry Pi (Raspi) digunakan sebagai web server. Raspberry Pi yang digunakan menggunakan Raspberry Pi 2 Model B deng

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22

Zikri, Arizal Akbar. "Pengembangan Sistem Streaming Sensor Data Temperatur dan Kelembapan di Ruang Laboratorium BBTA3 Melalui Teknologi Open Source." Journal of Aero Technology 2, no. 1 (2019). http://dx.doi.org/10.29122/joat.v2i1.3820.

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AbstractDevelopment of temperature and humidity data streaming Application from sensors in the server room is necessary to enable the operator to monitor the real-time air condition in the server room, without having to enter the room. This application development utilizes open source technology to make developers more independent and able to interact easily within the community without license hassle.Sensor data reading is done by Raspberry Pi, assigned as a producer in sending data to Kafka Cluster. Kafka is an open source technology used as tools for streaming data distributedly. One node i

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23

Sidharta, Hanugra Aulia, Felix Filipi, Rafli Attala Jaskandi, and Febrian Nugroho. "Design and Implementation LETS (Low Power Cluster Server) for Sustaining UMKM during Pandemic." Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, February 28, 2021, 77–82. http://dx.doi.org/10.22219/kinetik.v6i1.1162.

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Covid pandemic is spreading since end 2019 arround globe, this resulting several countries suffer economic crisis. Due people movement restriction and international border is closed, impact halting on export and import. Indonesia with 267,7 million people manage to overcome global crisis during 1998 and 2008 with encourage small and local industry. According data from BPS, SME support 60% GDP with Rp 7,7 Billion and provide 85 million employment. To sustain SME during customer shifting behavior, we propose small cluster server called as LETS. LETS is modular, and composed with several Raspberr

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24

Thanrak, Chotitham, and Sasalak Tongkaw. "Mathematical Model for Approximation the Efficiency of Parallel Computing on Single Board Cluster with Least-squares Approximation." International Journal of Integrated Engineering 12, no. 7 (2020). http://dx.doi.org/10.30880/ijie.2020.12.07.020.

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This research aims to study the relationship between parallel processing efficiency and several nodes on a single board cluster using a mathematical model, approximating least squares. This research tested on the Raspberry Pi single-board in the form of a high-performance computing system. It divided the tasks that need to be processed in each particular part and sent it to each unit to process simultaneously via the MPI (Messaging Passing Interface). This process is the standard division of work with communication between processors in the form of messages on the cluster system. It consists o

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Frantskevich, Kiril, Maxim Demenkovets, Roman Tavtyn, and Andrey Stepaniuk. "STUDY OF A CLUSTER SYSTEM BASED ON SINGLE BOARD COMPUTERS RASPBERRY Pi 3B +." Engineering Solutions 10, no. 9 (2019). http://dx.doi.org/10.32743/2658-6479.2019.9.10.199.

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26

Augustynowicz, Paweł, and Aneta Buraczyńska. "Comparison Between Experimental, Analytical and Simulation Model of Distributed Computation on ARM processors in High-Performance Computing." Computer Science and Mathematical Modelling, October 18, 2017, 5–10. http://dx.doi.org/10.5604/01.3001.0010.5517.

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The paper presents a comparison between experimental, analytical and simulation model of distributed cryptographic computation regarding password recovery with SHA 1 password hashing. The aim of this paper is compare popular mobile ARM processors with their Intel Atom analogue and determine their usefulness in cryptographic computations from High Performance Computing (HPC) point of view. During the construction process of HPC cluster, three different versions of Raspberry Pi computers were used. Then the constructed model was applied to develop an analytical and simulation models that allow c

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