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Journal articles on the topic 'Embedded computing'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Sadiku, Matthew N. O., Yonghui Wang, Suxia Cui, and Sarhan M. Musa. "Embedded Computing Systems." International Journal of Scientific Engineering and Technology 6, no. 12 (2017): 361. http://dx.doi.org/10.5958/2277-1581.2017.00059.6.

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2

Teodorovici, Vasile G. "Modern embedded computing." ACM SIGSOFT Software Engineering Notes 38, no. 1 (2013): 59–60. http://dx.doi.org/10.1145/2413038.2413059.

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3

Dally, William J., James Balfour, David Black-Shaffer, et al. "Efficient Embedded Computing." Computer 41, no. 7 (2008): 27–32. http://dx.doi.org/10.1109/mc.2008.224.

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4

Johnson, S. D. "Embedded computing - Formal methods in embedded design." Computer 36, no. 11 (2003): 104–6. http://dx.doi.org/10.1109/mc.2003.1244539.

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5

Wolf, W. "What is embedded computing?" Computer 35, no. 1 (2002): 136–37. http://dx.doi.org/10.1109/2.976929.

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6

Li, Keqiu. "Advanced Topics on Embedded Computing." Journal of Embedded Computing 4, no. 1 (2011): 1–2. https://doi.org/10.3233/jec-2009-0101.

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7

Jensen, David, and Arun Rodrigues. "Embedded Systems and Exascale Computing." Computing in Science & Engineering 12, no. 6 (2010): 20–29. http://dx.doi.org/10.1109/mcse.2010.95.

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8

Yu, Huiqun, and Yongqiang Sun. "Hybridity in embedded computing systems." Journal of Computer Science and Technology 11, no. 1 (1996): 90–96. http://dx.doi.org/10.1007/bf02943525.

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9

Wolf, W. "Whither Warhol's law? [embedded computing]." Computer 35, no. 9 (2002): 96–97. http://dx.doi.org/10.1109/mc.2002.1033036.

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10

Dutt, N., and Kiyoung Choi. "Configurable processors for embedded computing." Computer 36, no. 1 (2003): 120–23. http://dx.doi.org/10.1109/mc.2003.1160063.

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11

Magoulès, Frédéric, Che-Lun Hung, Hai Jiang, and Jia Hu. "Embedded multicore computing and applications." Concurrency and Computation: Practice and Experience 28, no. 16 (2016): 4211–14. http://dx.doi.org/10.1002/cpe.3910.

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12

Swaleh, CA Mohd, and Dr N. Subbu Krishna Sastry. "Quantum Computing in Embedded Finance." International Journal of Managerial Studies and Research 13, no. 6 (2025): 1–12. https://doi.org/10.20431/2349-0349.1306001.

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13

Li, Jing, Huan Guo Zhang, Bo Zhao, Xi Guo, and Fan He. "Research on Hardware Security of Embedded System in Cloud Environment." Advanced Materials Research 488-489 (March 2012): 1480–87. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1480.

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Cloud computing is an important innovation of current computing models. At present, the research on the security of cloud computing is mainly concentrated on PCs and servers. The security of embedded system in cloud environment does not win enough attention. This paper analysis the security threats of it, and proposes a Secure Hardware Model to provide a tamper-resistant and more reliable hardware embedded platform in cloud environment. Our model adds some new components to traditional embedded system, controls the start sequence of platform’s components, verifies the integrity of crucial info

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14

Quilici-Gonzalez, J. A., G. Kobayashi, M. C. Broens, and M. E. Q. Gonzalez. "Ubiquitous Computing." International Journal of Technoethics 1, no. 3 (2010): 11–23. http://dx.doi.org/10.4018/jte.2010070102.

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In this article, the authors investigate, from an interdisciplinary perspective, possible ethical implications of the presence of ubiquitous computing systems in human perception/action. The term ubiquitous computing is used to characterize information-processing capacity from computers that are available everywhere and all the time, integrated into everyday objects and activities. The contrast in approach to aspects of ubiquitous computing between traditional considerations of ethical issues and the Ecological Philosophy view concerning its possible consequences in the context of perception/a

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15

Cheng, Tim. "Trustworthy ICs for secure embedded computing." IEEE Design & Test of Computers 24, no. 6 (2007): 516. http://dx.doi.org/10.1109/mdt.2007.207.

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16

Dai, Wenbin, Hiroaki Nishi, Valeriy Vyatkin, Victor Huang, Yang Shi, and Xinping Guan. "Industrial Edge Computing: Enabling Embedded Intelligence." IEEE Industrial Electronics Magazine 13, no. 4 (2019): 48–56. http://dx.doi.org/10.1109/mie.2019.2943283.

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17

Waldo, J. "Embedded computing and Formula One racing." IEEE Pervasive Computing 4, no. 3 (2005): 18–21. http://dx.doi.org/10.1109/mprv.2005.56.

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18

Hung, Che-Lun, Frédéric Magoulès, Meikang Qiu, Robert C. Hsu, and Chun-Yuan Lin. "Embedded multi-core computing and applications." Journal of Supercomputing 73, no. 8 (2017): 3327–32. http://dx.doi.org/10.1007/s11227-017-2107-6.

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19

Henkel, Jörg, Lars Bauer, Artjom Grudnitsky, and Hongyan Zhang. "Adaptive embedded computing with i -core." ACM SIGBED Review 11, no. 3 (2014): 20–21. http://dx.doi.org/10.1145/2692385.2692387.

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20

Vinh, Phan C., and Jonathan P. Bowen. "Continuity aspects of embedded reconfigurable computing." Innovations in Systems and Software Engineering 1, no. 1 (2005): 41–53. http://dx.doi.org/10.1007/s11334-005-0003-3.

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21

Martyshkin, A. I., I. A. Kiryutkin, and E. A. Merenyasheva. "Autotesting an Embedded Reconfigurable Computing System." Proceedings of the Southwest State University 27, no. 1 (2023): 140–52. http://dx.doi.org/10.21869/2223-1560-2023-27-1-140-152.

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Purpose of research. The main idea is to build a mathematical testing model that integrates different aspects of an embedded reconfigurable computing system and its interactions. This model provides an efficient representation of test scenarios and allows to analyse the dynamics of the reconfigurable computing system during testing. The paper also discusses methods for generating test sequences based on the properties of a finite state machine.Methods. The authors propose to represent the autotest as a finite state Mile machine, where states serve to store information about the current state o

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22

DP, Franco. "Hardware Forensics-an Introduction to Digital Forensics in the Embedded Computing Context." International Journal of Forensic Sciences 8, no. 4 (2023): 1–14. http://dx.doi.org/10.23880/ijfsc-16000345.

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The growing presence of embedded systems in the daily lives of people and companies, driven by the emergence of portable devices, makes these systems ubiquitous and a valuable source of information for criminal investigations. However, the lack of resources dedicated to forensics in this context, excluding IoT devices due to their technical particularities, led to the need to start writing this material. This article seeks to introduce experts to embedded systems forensics, highlighting the importance and existence of this field, and emphasizing that microcontrollers, flash memories, ROM memor

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23

Gao, Fang, Zhangqin Huang, Shulong Wang, and Xinrong Ji. "Optimized Parallel Implementation of Face Detection Based on Embedded Heterogeneous Many-Core Architecture." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 07 (2017): 1756011. http://dx.doi.org/10.1142/s0218001417560110.

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Computing performance is one of the key problems in embedded systems for high-resolution face detection applications. To improve the computing performance of embedded high-resolution face detection systems, a novel parallel implementation of embedded face detection system was established based on a low power CPU-Accelerator heterogeneous many-core architecture. First, a basic CPU version of face detection prototype was implemented based on the cascade classifier and Local Binary Patterns operator. Second, the prototype was extended to a specified embedded parallel computing platform that is ca

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24

Syschikov, Alexey, Yuriy Sheynin, Boris Sedov, and Vera Ivanova. "Domain-Specific Programming Environment for Heterogeneous Multicore Embedded Systems." International Journal of Embedded and Real-Time Communication Systems 5, no. 4 (2014): 1–23. http://dx.doi.org/10.4018/ijertcs.2014100101.

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Nowadays embedded systems are used in a broad range of domains such as avionics, space, automotive, mobile, domestic appliances etc. Sophisticated software determines the quality of embedded systems and requires high-qualified experts for software development. Software becomes the main assert of embedded systems that is valuable to retain in changing computing platforms in embedded systems evolution. Computing platforms for embedded systems became multicore processors and SoC, they can change in the embedded system lifetime that could be long (dozen of years for an automobile and airplane). It

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25

Rinaldi, Luciene Cristina Alves, Adriano dos Santos Viana, Celso Junji Sonehara, Gabriel Pereira da Costa Andrade, and Gustavo Souza Azevedo. "Embedded Computing for IoT Using Simple Projects." International Journal for Digital Society 10, no. 1 (2019): 1459–69. http://dx.doi.org/10.20533/ijds.2040.2570.2019.0181.

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26

Cabello, Sergio, Markus Chimani, and Petr Hliněný. "Computing the Stretch of an Embedded Graph." SIAM Journal on Discrete Mathematics 28, no. 3 (2014): 1391–401. http://dx.doi.org/10.1137/130945636.

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27

Zhang, Bin, Kuizhi Mei, and Jizhong Zhao. "Matrix computing coprocessor for an embedded system." Microprocessors and Microsystems 39, no. 7 (2015): 444–56. http://dx.doi.org/10.1016/j.micpro.2015.07.001.

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28

Sengers, P., J. Kaye, K. Boehner, et al. "Art, design & entertianment - Culturally embedded computing." IEEE Pervasive Computing 3, no. 1 (2004): 14–21. http://dx.doi.org/10.1109/mprv.2004.1269124.

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29

Munir, A., S. Ranka, and A. Gordon-Ross. "High-Performance Energy-Efficient Multicore Embedded Computing." IEEE Transactions on Parallel and Distributed Systems 23, no. 4 (2012): 684–700. http://dx.doi.org/10.1109/tpds.2011.214.

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30

Vahid, Frank, Roman Lysecky, Chuanjun Zhang, and Greg Stitt. "Highly configurable platforms for embedded computing systems." Microelectronics Journal 34, no. 11 (2003): 1025–29. http://dx.doi.org/10.1016/s0026-2692(03)00171-x.

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31

Zhang, YiMing, XiCheng Lu, and DongSheng Li. "Embedded DHT overlays in virtual computing environments." Science China Information Sciences 53, no. 3 (2010): 483–93. http://dx.doi.org/10.1007/s11432-010-0034-8.

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32

Heyrman, Barthélémy, Michel Paindavoine, Renaud Schmit, Laurent Letellier, and Thierry Collette. "Smart camera design for intensive embedded computing." Real-Time Imaging 11, no. 4 (2005): 282–89. http://dx.doi.org/10.1016/j.rti.2005.04.006.

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33

Rezk, Nesma M., Madhura Purnaprajna, Tomas Nordstrom, and Zain Ul-Abdin. "Recurrent Neural Networks: An Embedded Computing Perspective." IEEE Access 8 (2020): 57967–96. http://dx.doi.org/10.1109/access.2020.2982416.

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34

Krishna, Shankara Narayanan. "Membrane computing with transport and embedded proteins." Theoretical Computer Science 410, no. 4-5 (2009): 355–75. http://dx.doi.org/10.1016/j.tcs.2008.09.046.

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35

Cheong, Lee Sing, Feng Lin, Hock Soon Seah, et al. "Embedded Computing for Fluorescence Confocal Endomicroscopy Imaging." Journal of Signal Processing Systems 55, no. 1-3 (2008): 217–28. http://dx.doi.org/10.1007/s11265-008-0204-8.

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36

Henkel, J. "Embedded computing - Closing the soc design gap." Computer 36, no. 9 (2003): 119–21. http://dx.doi.org/10.1109/mc.2003.1231200.

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37

Serpanos, D., and J. Henkel. "Dependability and Security Will Change Embedded Computing." Computer 41, no. 1 (2008): 103–5. http://dx.doi.org/10.1109/mc.2008.14.

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38

Herman, Yurii, Halyna Lastivka, and Andrii Samila. "Embedded Operating Systems in IoT Edge Computing." Security of Infocommunication Systems and Internet of Things 2, no. 2 (2024): 02001. https://doi.org/10.31861/sisiot2024.2.02001.

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Embedded systems and Edge Computing in Internet of Things (IoT) represent a special approach to creating systems for collecting, processing and analyzing data in an unstable environment. This article examines the benefits of Linux in this context, highlighting its flexibility, robust software ecosystems, and scalability, which are critical for a variety of IoT applications. The question of the operation of devices in an environment with a weak and/or unstable network is also raised, the general development of IoT/Internet-of-Everything (IoE) as a technology in the conditions of various distrib

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39

Kumar, Ajitesh, and Sanjai Kumar Gupta. "Reliable Energy-Aware Scheduling Algorithm With Multi-Level Budget for Real-Time Embedded System." International Journal of Embedded and Real-Time Communication Systems 12, no. 4 (2021): 55–76. http://dx.doi.org/10.4018/ijertcs.2021100104.

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Energy consumption of embedded applications has rapidly increased with the advancement of technology and computing. There is a little improvement in energy consumption as compared to computing and storage capacity. Although computing performance has been continuously increasing, power/energy consumption is more critical in the design of real-time embedded systems. Real-time embedded applications need a power management technique to judicially balance the energy consumption and computing performance. It should be done in such a way that the system performance improves along with an increase in

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40

Li, Xinwei. "Embedded Smart Sensor Network Architecture Based on Edge Computing." Applied and Computational Engineering 127, no. 1 (2025): 134–40. https://doi.org/10.54254/2755-2721/2025.20262.

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This paper focuses on the integration of edge computing in smart sensor networks. In Internet of Things (IoT) applications, traditional cloud computing models cause data processing delays due to long-distance data transmission. This transmission delay significantly impairs real-time data processing and feedback capabilities, particularly in time-sensitive applications. Edge computing can transfer data to local devices for processing so that data that is affected by network congestion does not have to be transmitted long distances to the cloud for processing. It can greatly reduce the delay cau

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41

Tang, Jian Gang. "The Research on Embedded Database System of Wireless Network." Applied Mechanics and Materials 511-512 (February 2014): 727–31. http://dx.doi.org/10.4028/www.scientific.net/amm.511-512.727.

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Wireless embedded database system is more complex and flexible than conventional computing environment. Embedded database computing platform requires more technologies such as asymmetric mobility, instability connected topology diversity, network communications, highly scalable systems, low reliability. This paper described the design and development process of embedded database, analyzed the database indexes, data storage and lexical analyzer. It supports CAPI interfaces and standard SQL subset, also supports ODBC or JDBC and bi-directional data exchange, and has a two-way flow of data betwee

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42

Uma, Perumal, and Renganathan Vasantharajan. "Embedded AI Application in Defense UAV." Journal of Advances in Computational Intelligence Theory 4, no. 3 (2022): 1–9. https://doi.org/10.5281/zenodo.7446973.

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Embedded systems in combination with AI in defense systems is a boon for nations security. Various embedded hardware along with algorithms of AI, is a blend of computing techniques is a leading-edge tool for an army. Army drones, single or a swarm, can either inform the allies with necessary facts or can even misinform enemies with fake data is a game changer in a battle or military operation. The capabilities of embedded systems in addition edge and fog computing techniques to bring down latency, bandwidth and reduction in load to cloud servers. AI algorithms that can teach Intuition with adv

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43

Chaudhari, Pallavi, Snehal Dhadge, and Aishwarya Rajale. "STEGANOGRAPHY BASED ON EMBEDDED SYSTEM." JournalNX - A Multidisciplinary Peer Reviewed Journal QIPCEI2K18 (April 30, 2018): 155–57. https://doi.org/10.5281/zenodo.1411821.

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Steganography is method dealing with writing hidden messages in a specific path that only the sender and the receiver are able to decrypt. Important domains, besides classic computing, where steganography can be applied are domains using mobile and embedded devices. This project work mainly focuses on the implementation of a steganographic algorithm on embedded devices like ARM, PIC or any equivalent embedded device https://journalnx.com/journal-article/20150594

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44

Han, Zhiyuan, Jian Shen, Dandan Luo, Bo Gao, HuaQi Chen, and Jin Xie. "The Optimization Of The Distributed AI Embedded Cluster System." Journal of Physics: Conference Series 2195, no. 1 (2022): 012010. http://dx.doi.org/10.1088/1742-6596/2195/1/012010.

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Abstract This paper improves the core functions of the real-time video analysis system for edge computing which we proposed before. The improvement of this paper including distributed cluster status management and two-level horizontal expansion. The three-level task scheduling mechanism is realized, and the complete data link processing is realized. At the same time, RK3399pro is proposed to replace RK3399 as the hardware computing unit of the AI business. On the premise of satisfying real-time processing, the computing unit resources are saved. Compared with our previous system, the processin

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45

S., M. Sivakama Sundari, and A. Rijuvana Begum Dr. "Soft Computing Healthcare Intelligence through Multisensory Activity Recognition." International Journal of Trend in Scientific Research and Development 2, no. 1 (2017): 294–300. https://doi.org/10.31142/ijtsrd5879.

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Remote patient monitoring through telemedicine has become very usual nowadays. Sensor are attached to the patient's body and they monitor the vital signs during various activity, the data acquires from sensor is given as input to genetic algorithm based activity recognition system. If any deviations are found in vital signs during any activity, it is informed to the physician. Simulation was performed by taking 10 sample patients and some activities. Results prove the efficiency of the algorithm. S. M. Sivakama Sundari | Dr. A. Rijuvana Begum "Soft Computing Healthcare Intelligence th

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46

Pajuelo-Holguera, Francisco, Juan A. Gómez-Pulido, and Fernando Ortega. "Performance of Two Approaches of Embedded Recommender Systems." Electronics 9, no. 4 (2020): 546. http://dx.doi.org/10.3390/electronics9040546.

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Nowadays, highly portable and low-energy computing environments require programming applications able to satisfy computing time and energy constraints. Furthermore, collaborative filtering based recommender systems are intelligent systems that use large databases and perform extensive matrix arithmetic calculations. In this research, we present an optimized algorithm and a parallel hardware implementation as good approach for running embedded collaborative filtering applications. To this end, we have considered high-level synthesis programming for reconfigurable hardware technology. The design

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47

Osta, Mario, Ali Ibrahim, and Maurizio Valle. "Approximate Computing Circuits for Embedded Tactile Data Processing." Electronics 11, no. 2 (2022): 190. http://dx.doi.org/10.3390/electronics11020190.

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In this paper, we demonstrate the feasibility and efficiency of approximate computing techniques (ACTs) in the embedded Support Vector Machine (SVM) tensorial kernel circuit implementation in tactile sensing systems. Improving the performance of the embedded SVM in terms of power, area, and delay can be achieved by implementing approximate multipliers in the SVD. Singular Value Decomposition (SVD) is the main computational bottleneck of the tensorial kernel approach; since digital multipliers are extensively used in SVD implementation, we aim to optimize the implementation of the multiplier ci

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48

Gill, C. D., R. K. Cytron, and D. C. Schmidt. "Multiparadigm scheduling for distributed real-time embedded computing." Proceedings of the IEEE 91, no. 1 (2003): 183–97. http://dx.doi.org/10.1109/jproc.2002.805822.

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49

Vince McLoughlin, Ian, Timo Rolf Bretschneider, and Chen Zheming. "Virtualized Development and Testing for Embedded Cluster Computing." International Journal of Networking and Computing 2, no. 2 (2012): 160–87. http://dx.doi.org/10.15803/ijnc.2.2_160.

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50

Årzén, Karl-Erik, and Anton Cervin. "CONTROL AND EMBEDDED COMPUTING: SURVEY OF RESEARCH DIRECTIONS." IFAC Proceedings Volumes 38, no. 1 (2005): 191–202. http://dx.doi.org/10.3182/20050703-6-cz-1902.01073.

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