Commodity single board computer clusters and their applications

© 2018 Current commodity Single Board Computers (SBCs) are sufficiently powerful to run mainstream operating systems and workloads. Many of these boards may be linked together, to create small, low-cost clusters that replicate some features of large data center clusters. The Raspberry Pi Foundation produces a series of SBCs with a price/performance ratio that makes SBC clusters viable, perhaps even expendable. These clusters are an enabler for Edge/Fog Compute, where processing is pushed out towards data sources, reducing bandwidth requirements and decentralizing the architecture. In this paper we investigate use cases driving the growth of SBC clusters, we examine the trends in future hardware developments, and discuss the potential of SBC clusters as a disruptive technology. Compared to traditional clusters, SBC clusters have a reduced footprint, are low-cost, and have low power requirements. This enables different models of deployment—particularly outside traditional data center environments. We discuss the applicability of existing software and management infrastructure to support exotic deployment scenarios and anticipate the next generation of SBC. We conclude that the SBC cluster is a new and distinct computational deployment paradigm, which is applicable to a wider range of scenarios than current clusters. It facilitates Internet of Things and Smart City systems and is potentially a game changer in pushing application logic out towards the network edge

Implementasi Deteksi dan Pengenalan Wajah pada Sistem Ujian Online Menggunakan Metode Deep Learning Berbasis Raspberry Pi

Penelitian ini bertujuan untuk mengembangkan sistem yang secara otomatis dapat mengenali peserta dalam tes berbasis online untuk efisiensi waktu dan biaya. Sistem ini terdiri dari Raspberry Pi untuk menjalankan algoritma pengenalan wajah, Kamera Pi untuk menangkap gambar peserta dan server lokal untuk menyimpan data peserta. Pada tahap awal penelitian, dibangun sebuah dataset yang berisi foto terbaru peserta dan id peserta. Dataset ini kemudian digunakan dalam proses pembelajaran menggunakan algoritma haarcascade yang merupakan bagian dari metode deep learning untuk menghasilkan sebuah model. Pada tahap pengenalan, gambar peserta dibandingkan dengan model. Peserta yang berhasil dikenali akan secara otomatis dialokasikan ke komputer yang tersedia. Pengujian menunjukkan bahwa sistem berhasil mengenali peserta tes dan yang bukan peserta tes

Ten Quick Tips for Using a Raspberry Pi

Much of biology (and, indeed, all of science) is becoming increasingly computational. We tend to think of this in regards to algorithmic approaches and software tools, as well as increased computing power. There has also been a shift towards slicker, packaged solutions--which mirrors everyday life, from smart phones to smart homes. As a result, it's all too easy to be detached from the fundamental elements that power these changes, and to see solutions as "black boxes". The major goal of this piece is to use the example of the Raspberry Pi--a small, general-purpose computer--as the central component in a highly developed ecosystem that brings together elements like external hardware, sensors and controllers, state-of-the-art programming practices, and basic electronics and physics, all in an approachable and useful way. External devices and inputs are easily connected to the Pi, and it can, in turn, control attached devices very simply. So whether you want to use it to manage laboratory equipment, sample the environment, teach bioinformatics, control your home security or make a model lunar lander, it's all built from the same basic principles. To quote Richard Feynman, "What I cannot create, I do not understand".Comment: 12 pages, 2 figure

Mathematical Model for Approximation the Efficiency of Parallel Computing on Single Board Cluster with Least-squares Approximation

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 of eight nodes of Raspberry Pi. It measures the instruction set's ability to perform decimal operations per second or Floating-point Operation Per Second (FLOPS) with High-Performance Linpack Benchmarks (HPL). As a result, the efficiency of the ability to process instruction set in decimal per second increases the performance continuously when increasing the number of the node on the cluster. Which corresponds to the mathematical model obtained f(x) = 1.0684x^(0.8256).It shows a relationship between parallel processing performance values and the number of nodes on the cluster and can be estimated with the mathematical model above

Energy Usage Profiling for Virtualized Single Board Computer Clusters

With Network Function Virtualization (NFV) platforms gaining ground, we question the combination of NFV and Single Board Computers (SBCs) in terms of compatibility, reliability, and energy consumption. A mini cluster of SBCs is used to develop a scalable and resilient energy monitoring application. The application is employed to discover the energy demands of a NFV platform in modern SBCs, and build the energy profile of the devices and the deployed services. We use the results and the added knowledge from building the application to strengthen the argument that SBC clusters can support virtualized service deployment. This evidence, alongside the rich gamut of characteristics that SBCs hold, proves that they are a viable option for edge components of a fog network. Our results show that running different virtualised processes offers added functionality, resilience and scalability without heavily sacrificing energy consumption

Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad RTI2018-098062-A-I00European Union’s Horizon 2020 No. 754489Science Foundation Ireland grant 13/RC/209

Life cycle assessment of ICT in higher education: a comparison between desktop and single-board computers

International audiencePurposeInformation and communications technology (ICT) plays a key role in higher education in improving the teaching process. Consequently, the environmental impacts associated with ICT are increasing, and innovative solutions must be deployed to reduce these impacts and increase students’ awareness. Single-board computers (SBCs) are promising because they rely on less materials and energy than desktop computers (PCs). But additional servers are required to perform large-scale computations. Hence, this paper aims at conducting comparative LCA between SBCs and PCs.Materials and methodsThe study is conducted in the context of a French engineering school with the following functional unit: “use 600 computers for 5 years in an engineering school.” Two scenarios are defined to fulfil this functional unit. Scenario 1 is the use of 600 PCs (current infrastructure), and scenario 2 is the use of 600 SBCs combined with 6 servers (alternative infrastructure). The analysis includes the materials manufacturing, assembly, packaging, transport, use and end-of-life of each device. Life cycle inventory (LCI) of the foreground systems was generated using a variety of sources: disassembly of computers, counting of electronic components, datasheets, estimations, etc. LCI of the background systems is taken from ecoinvent 3.5. The selected life cycle impact assessment methodology is ReCiPe 2016 midpoint, and computation of impacts is done with openLCA 1.10.3.Results and discussionScenario 2 (SBCs + servers) generates 84 to 92% less impact than scenario 1 (PCs) in all categories. In terms of global warming, scenarios 1 and 2 generate 225 and 18 tCO2 eq per functional unit, respectively. This is explained by the large reduction in material and energy requirements for SBCs which is not counterbalanced by the servers. Equipment manufacturing accounts for the largest share of impacts in most categories for both scenarios (e.g., ~70% for global warming), followed by the use phase. This differs from the results found in the literature, as this study was conducted in the context of France, which has a low-carbon electricity mix.ConclusionsOur analysis has shown that SBCs combined with servers reduce the carbon footprint and other environmental impacts of ICT infrastructure for higher education. This study provides an example of low tech-oriented solution for students. Other prospective solutions (e.g., use of laptops) should be extensively studied in the future. From an LCA point of view, updating the inventory data related to background processes for electronic components is a necessary step forward to improve the certainty of the results

Data acquirement and evaluation of road quality with regard to seating comfort in moving car

Bakalářská práce se zabývá záznamem a vyhodnocením měření kvality vozovky za použití snímačů zrychlení umístěných na podlaze automobilu a měřením rozložení tlaku v kontaktní zóně sedící osoby a sedáku. Program pro záznam je řízen pomocí vývojové platformy Arduino, která čte data z akcelerometru a následně je záznam zpracován programem MATLAB. Teoretická část se zabývá principem funkce snímačů zrychlení a jejich rozdělením, vývojovou platformou arduino a metodami analýzy a vyhodnocení signálů. Experimentální část bakalářské práce je věnována volbě vhodného snímače zrychlení, zpracováním signálu, volbou kritéria hodnocení kvality vozovky a měřením rozložení tlaku v kontaktní zóně sedící osoby a sedáku.The bachelor's thesis deals with the recording and evaluation of road quality measurements using acceleration sensors located on the floor of a car and measuring the pressure distribution in the contact zone of the seated person and seat. The recording program is controlled by the Arduino development platform, which reads data from the accelerometer and then the recording is processed by the MATLAB program. The theoretical part deals with the principle of acceleration sensors and their distribution, the arduino development platform and methods of signal analysis and evaluation. The experimental part of the bachelor's thesis is devoted to the selection of a suitable acceleration sensor, signal processing, selection of road quality evaluation criteria and measuring the pressure distribution in the contact zone of the seated person and seat.