Journal articles: 'Computing'

1

Henkel, Jorg. "Approximate Computing: Solving Computing's Inefficiency Problem?" IEEE Design & Test 33, no. 1 (February 2016): 4–5. http://dx.doi.org/10.1109/mdat.2015.2509608.

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Румянцев, К. Е., and Л. К. Хаджиева. "CONFIDENTIAL COMPUTINGIN A PROTECTED COMPUTING ENVIRONMENT." Вестник ГГНТУ. Технические науки, no. 4(30) (December 22, 2022): 31–37. http://dx.doi.org/10.34708/gstou.2022.13.45.004.

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Обеспечение информационной безопасности является немаловажным фактором в настоящее время, особенно это касается вычислительных систем, инфокоммуникационных систем и систем передачи данных. В статье рассмотрена надежность вычислений, изложена концепция вычислений, проведена параллель между физической и логической составляющей защиты информации. Применению больших данных и технологий искусственного интеллекта в наше время уделяется все больше внимания с точки зрения защиты конфиденциальности и адекватного соответствия данных. Методы, которые могут обеспечить безопасность данных и использовать данные для доверенных вычислений в соответствии с требованиями, так называемые конфиденциальные вычисления, привлекают все больше и больше внимания людей. Решение данной проблемы в статье предлагается реализовать с применением технологии TEMPEST, которая применяет экранирование, которое ограничивает утечку электромагнитной информации от внутреннего излучения, предотвращает попадание внешних радиочастотных помех в вычислительные среды. Ensuring information security is no small important factor at present, especially for computing systems, infocommunication systems and data transmission systems. Since electromagnetic leakage not only harms the health of people who are near the computer, but also causes electromagnetic interference in the surrounding electronic equipment and leads to information leakage, this article discusses methods for protecting information and preventing leakage of electromagnetic radiation, analyzes methods for protecting information and their applications. The TEMPEST shielding technology, which includes the mechanism of electromagnetic leakage of information processing equipment, is considered. In addition to electromagnetic information leakage, the article considers the reliability of calculations, outlines the concept of calculations, draws a parallel between the physical and logical components of information protection.

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Sakariya, Harsh Bipinbhai, and Ganesh D. "Taxonomy of Load Balancing Strategies in Distributed Systems." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 03 (March 25, 2024): 1796–802. http://dx.doi.org/10.15680/ijircce.2024.1203070.

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Large-scale parallel and distributed computing systems are becoming more popular as a result of falling hardware prices and improvements in computer networking technologies. Improved performance and resource sharing are potential benefits of distributed computing systems. We have provided a summary of distributed computing in this essay. The differences between parallel and distributed computing, terms related to distributed computing, task distribution in distributed computing, performance metrics in distributed computing systems, parallel distributed algorithm models, benefits of distributed computing, and distributed computing's application domain were all covered in this paper.

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Zhang, Guo Zhi, and Ning Zhou. "The Development of Computing System with Equivalent Beam Element Based on Matlab Software." Advanced Materials Research 479-481 (February 2012): 1161–64. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.1161.

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The computing method of series traction mechanism of heavy machinery was studied. The scheme of its computing system with equivalent beam element was proposed. Based on this scheme, combining with secondary development of language of Matlab, the computing system was developed. Through comparing with the reslut of enity element with ANSYS, the computing system was verified. Beacause of the computing system developed, the computating efficiency is improved and the accuracy is ensured.

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Sahare, Shubhangi, and Dr D. V. Rojatkar. "Cloud Computing." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (October 31, 2017): 786–89. http://dx.doi.org/10.31142/ijtsrd4685.

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Eeckhout, Lieven. "Approximate Computing, Intelligent Computing." IEEE Micro 38, no. 4 (July 2018): 6–7. http://dx.doi.org/10.1109/mm.2018.043191119.

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Vachhani, Prof Milan Kantilal, and Dr Kishor H. Atkotiya. "Similarities and Contrast between Grid Computing and Cloud Computing." Indian Journal of Applied Research 3, no. 3 (October 1, 2011): 54–56. http://dx.doi.org/10.15373/2249555x/mar2013/19.

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Zhang, Yi, and Yi Min Su. "Research on Resource Scheduling Algorithm in Cloud Computing Data Center." Advanced Materials Research 926-930 (May 2014): 2050–53. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2050.

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In recent years, with the rapid development of Internet and virtualization technology, cloud computing, which providing users with on-demand services, has become a research hotspot. Under the environment of cloud computing, the datacenter, consisted by hardware and software, is a loosely coupled resource sharing architecture. The existing cloud computing's inadequacies are as following three aspects: 1. For lacking of real adequate and effective transaction of global bidirectional-way selection, the revenue of most of cloud resource provider is too low. 2. Since not fully considering the scheduling of multi-dimensional cloud resources, existing cloud computing's utilization for multi-dimensional cloud resource is too low. 3. Because existing cloud datacenter does not fully consider the energy consumption of communication between the cloud tasks, its energy consumption is too high. Resource scheduling is a major research direction of cloud computing. First, we make a in-depth investigation and analysis of the research status of cloud computing resource scheduling, and then focus on resource scheduling method to reduce the energy consumption of cloud computing data center. Finally we set an important future research direction of cloud computing resource management research in order to provide a useful reference for cloud computing research.

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Zhang, Yan. "Web Data Mining Technology on Cloud Computing." Applied Mechanics and Materials 543-547 (March 2014): 3490–93. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.3490.

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With the rapid development of cloud computing technology, the traditional centralized data mining technology becomes inappropriate for the growing huge amounts of data. Cloud computings Web data mining technology comes into use because it is a reliable and efficient method. This article introduces the meaning, characteristics, and the present situation of cloud computing, analyzes the advantage of Web data mining technology on the basis of the use of cloud computing technology, makes investigations and summaries of the present situation, challenges and problems of the current cloud computing Web data mining technology research, and puts forward the corresponding methods to solve these problems.

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Zhao, Wei, and Hong Tao Zhang. "E-Commerce Recommendation System Based on Cloud Computing." Advanced Materials Research 926-930 (May 2014): 2570–73. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2570.

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According to the Present Situations were that there is an urgent demand for large data analysis in Electronic Commerce, by using cloud computings advantage in storing and analyzing mass data, the solution of new project which can analysis data was proposed, based on the cloud computing. Firstly, aiming to the advantages of the cloud computing platform, the novel data-analysis architecture was designed, then the business flow chart by using cloud computing analysis on the architecture. Finally the project is validated by practical application and possesses certain reference meaning in data exchange based on cloud computing.

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Bashir, Noman, David Irwin, Prashant Shenoy, and Abel Souza. "Sustainable Computing - Without the Hot Air." ACM SIGEnergy Energy Informatics Review 3, no. 3 (October 2023): 47–52. http://dx.doi.org/10.1145/3630614.3630623.

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The demand for computing is continuing to grow exponentially. This growth will translate to exponential growth in computing's energy consumption unless improvements in its energy-efficiency can outpace increases in its demand. Yet, after decades of research, further improving energy-efficiency is becoming increasingly challenging, as it is already highly optimized. As a result, at some point, increases in computing demand are likely to outpace increases in its energy-efficiency, potentially by a wide margin. Such exponential growth, if left unchecked, will position computing as a substantial contributor to global carbon emissions. While prominent technology companies have recognized the problem and sought to reduce their carbon emissions, they understandably focus on their successes, which has the potential to inadvertently convey the false impression that this is now, or will soon be, a solved problem. Such false impressions can be counterproductive if they serve to discourage further research in this area, since, as we discuss, eliminating computing's, and more generally society's, carbon emissions is far from a solved problem. To better understand the problem's scope, this paper distills the fundamental trends that determine computing's carbon footprint and their implications for achieving sustainable computing.

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Parveen Shaik, Dr Sajeeda. "Strategic Placement of Servers in Mobile Cloud Computing: A Comprehensive Exploration of Edge Computing, Fog Computing, and Cloudlet Technologies." INTERNATIONAL RESEARCH JOURNAL OF ENGINEERING & APPLIED SCIENCES 8, no. 4 (2020): 24–28. http://dx.doi.org/10.55083/irjeas.2020.v08i04009.

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Mobile Cloud Computing (MCC) has become integral to the advancement of mobile applications, necessitating strategic server placement for optimized performance. This review article explores three pivotal technologies—Edge Computing, Fog Computing, and Cloudlet Technologies—aimed at addressing the challenges posed by traditional cloud-centric models in MCC environments. The paper provides a thorough analysis of each approach, elucidating their architectural principles, benefits, and applications. Edge Computing’s proximity to end-users, Fog Computing’s intermediary role, and the localized Cloudlet Technologies are scrutinized. A comparative analysis offers insights into their strengths and limitations, aiding in determining their suitability based on diverse use cases. Real-world applications showcase the transformative impact of these technologies in enhancing mobile experiences across sectors such as healthcare, gaming, and more. The review concludes with a discussion on the challenges inherent in each strategy and proposes future research directions. This comprehensive exploration serves as a valuable resource for researchers, practitioners, and decision-makers navigating the dynamic landscape of strategic server placement in MCC, contributing to the optimization of performance and user experience in mobile applications and services.

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YAMAMURA, MASAYUKI. "DNA Computing. 3. Aqueous Computing." Journal of the Institute of Electrical Engineers of Japan 122, no. 3 (2002): 156–59. http://dx.doi.org/10.1541/ieejjournal.122.156.

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Keyes, Robert W. "Quantum Computing and Digital Computing." IEEE Transactions on Electron Devices 57, no. 8 (August 2010): 2041. http://dx.doi.org/10.1109/ted.2010.2049225.

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Yamamoto, Yoshihisa, Kenta Takata, and Shoko Utsunomiya. "Quantum Computing vs. Coherent Computing." New Generation Computing 30, no. 4 (October 2012): 327–56. http://dx.doi.org/10.1007/s00354-012-0403-5.

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16

Graña, Manuel. "Lattice computing and natural computing." Neurocomputing 72, no. 10-12 (June 2009): 2065–66. http://dx.doi.org/10.1016/j.neucom.2008.11.021.

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Suzuki, Yasuhiro. "Natural Computing and Formal Computing." Proceedings of International Conference on Artificial Life and Robotics 24 (January 10, 2019): 229–32. http://dx.doi.org/10.5954/icarob.2019.os9-3.

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18

Colwell, B. "That's not computing- thisis computing." Computer 36, no. 6 (June 2003): 6–8. http://dx.doi.org/10.1109/mc.2003.1204312.

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Popa, Raluca Ada. "Confidential Computing or Cryptographic Computing?" Queue 22, no. 2 (April 30, 2024): 108–32. http://dx.doi.org/10.1145/3664295.

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Secure computation via MPC/homomorphic encryption versus hardware enclaves presents tradeoffs involving deployment, security, and performance. Regarding performance, it matters a lot which workload you have in mind. For simple workloads such as simple summations, low-degree polynomials, or simple machine-learning tasks, both approaches can be ready to use in practice, but for rich computations such as complex SQL analytics or training large machine-learning models, only the hardware enclave approach is at this moment practical enough for many real-world deployment scenarios.

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Hajibaba, Majid, and Saeid Gorgin. "A Review on Modern Distributed Computing Paradigms: Cloud Computing, Jungle Computing and Fog Computing." Journal of Computing and Information Technology 22, no. 2 (2014): 69. http://dx.doi.org/10.2498/cit.1002381.

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Nwobodo, Ikechukwu. "Cloud Computing: A Detailed Relationship to Grid and Cluster Computing." International Journal of Future Computer and Communication 4, no. 2 (April 2015): 82–87. http://dx.doi.org/10.7763/ijfcc.2015.v4.361.

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Anjaneyulu, P., and Mr S. Srinivasa Reddy. "Cloud Computing Adoption Approach towards Securing Data in Cloud Computing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (June 30, 2018): 390–93. http://dx.doi.org/10.31142/ijtsrd12995.

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Tedre, Matti, and Nella Moisseinen. "Experiments in Computing: A Survey." Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/549398.

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Experiments play a central role in science. The role of experiments in computing is, however, unclear. Questions about the relevance of experiments in computing attracted little attention until the 1980s. As the discipline then saw a push towards experimental computer science, a variety of technically, theoretically, and empirically oriented views on experiments emerged. As a consequence of those debates, today's computing fields use experiments and experiment terminology in a variety of ways. This paper analyzes experimentation debates in computing. It presents five ways in which debaters have conceptualized experiments in computing: feasibility experiment, trial experiment, field experiment, comparison experiment, and controlled experiment. This paper has three aims: to clarify experiment terminology in computing; to contribute to disciplinary self-understanding of computing; and, due to computing’s centrality in other fields, to promote understanding of experiments in modern science in general.

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Kesswani, Nishtha, and Shelendra Kumar Jain. "Schematic Classification Model of Green Computing Approaches." Journal of Cases on Information Technology 17, no. 3 (July 2015): 14–21. http://dx.doi.org/10.4018/jcit.2015070102.

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Every electronic device has an impact on the environment, and computing devices are not an exception. Green computing is a highly motivated smart computing which tries to save energy and environment by minimizing harmful impacts of computing resource's production and their uses. As the 21st Century is known for Information Technology Revolution, major negative impact of computing resources on environment are day by days increasing contribution to carbon dioxide emission, hazardous substances, e-Waste and high consumption of energy. Nowadays Global Warming is a big issue which is responsible for climate changes. And according to many available facts computing resources are highly affecting it directly and indirectly. So the world's moral duties motivate it to save earth and environment from these harmful impacts, whose outcome is Green Computing. This paper focus on classification of various existing approaches which are used for Green Computing. This classification enhances researcher's concentration on particular classified category for their future contribution so that Green Computing's main aims can be fulfilled.

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Manca, Vincenzo, Carlos Martı́n-Vide, and Gheorghe Păun. "New computing paradigms suggested by DNA computing: computing by carving." Biosystems 52, no. 1-3 (October 1999): 47–54. http://dx.doi.org/10.1016/s0303-2647(99)00031-3.

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Rakib, Abdur. "Grid Computing Introduction." Journal of Advances and Scholarly Researches in Allied Education 15, no. 5 (July 1, 2018): 140–44. http://dx.doi.org/10.29070/15/57603.

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Wagobera Edgar Kedi, Chibundom Ejimuda, and Mojeed Dayo Ajegbile. "Cloud computing in healthcare: A comprehensive review of data storage and analysis solutions." World Journal of Advanced Engineering Technology and Sciences 12, no. 2 (July 30, 2024): 290–98. http://dx.doi.org/10.30574/wjaets.2024.12.2.0291.

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Cloud computing is revolutionizing the healthcare industry by offering scalable, flexible, and cost-effective solutions for data storage, analysis, and access to healthcare services. This comprehensive review explores the role, benefits, challenges, and future directions of cloud computing in healthcare. It highlights how cloud computing enhances data management and interoperability, facilitates telemedicine, ensures cost-effectiveness, and supports research and development. Despite the benefits, challenges such as data security, regulatory compliance, and system reliability must be addressed to fully leverage cloud computing's potential. Integrating emerging technologies like AI, blockchain, and IoT with cloud computing holds promise for further advancements in healthcare. Cloud computing will significantly impact healthcare delivery, enabling more personalized, efficient, and global healthcare solutions.

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Das, Sayantan, Madhurima Mondal, and Soumen Swarnakar. "A REVIEW ON CLOUD LOAD BALANCING TECHNIQUES." International Journal of Advanced Research 10, no. 07 (July 31, 2022): 1102–9. http://dx.doi.org/10.21474/ijar01/15135.

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Cloud computing simply means storing & accessing data and programs over the internet instead of your computers hard drive. The cloud is just a metaphor for the internet. An example of Cloud Computings process could also be Googles Gmail. Cloud computing is highly efficient, productive, safe & secure. Cloud computing consists of two terms One is Cloud which is a useful feature of computer technology to perform appropriate tasks. Computing may include computer hardware and software but must involve some form of a computer system. It is a type of operation of a computer that is fully dependent on exchanging computing resources rather than having local servers or personal devices to handle the appeal. Cloud refers to a public or semi-public space on transmission lines that exists between the endpoints of a transmission. Data that is transmitted across a WAN enters the network from one endpoint using a standard protocol.

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Connolly, Randy. "Can Citizenship Education Benefit Computing?" Informatics 9, no. 4 (November 18, 2022): 93. http://dx.doi.org/10.3390/informatics9040093.

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A recurring motif in recent scholarship in the computing ethics and society studies (CESS) subfield within computing have been the calls for a wider recognition of the social and political nature of computing work. These calls have highlighted the limitations of an ethics-only approach to covering social and political topics such as bias, fairness, equality, and justice within computing curricula. However, given the technically focused background of most computing educators, it is not necessarily clear how political topics should best be addressed in computing courses. This paper proposes that one helpful way to do so is via the well-established pedagogy of citizenship education, and as such it endeavors to introduce the discourse of citizenship education to an audience of computing educators. In particular, the change within citizenship education away from its early focus on personal responsibility and duty to its current twin focus on engendering civic participation in one’s community along with catalyzing critical attitudes to the realities of today’s social, political, and technical worlds, is especially relevant to computing educators in light of computing’s new-found interest in the political education of its students. Related work in digital literacy education is also discussed.

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Seidman, Stephen. "Computing." ACM Inroads 5, no. 4 (December 3, 2014): 6–11. http://dx.doi.org/10.1145/2644826.

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Frailey, Dennis J. "Computing." ACM Inroads 2, no. 4 (December 2011): 4–8. http://dx.doi.org/10.1145/2038876.2038877.

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Ahuja, Sanjay P., and Niharika Deval. "From Cloud Computing to Fog Computing." International Journal of Fog Computing 1, no. 1 (January 2018): 1–14. http://dx.doi.org/10.4018/ijfc.2018010101.

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This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.

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Singh, Hardeep. "Cloud Computing: An Internet Based Computing." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 3 (June 30, 2012): 116–21. http://dx.doi.org/10.24297/ijct.v2i3b.2701.

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Present paper focuses on the overview of Cloud Computing. Cloud Computing is an Internet-based computing; where resources, software and information are provided to computers on-demand, like a public utility; is emerging as a platform for sharing resources like infrastructure, software and various applications. This paper does a literature survey on some of the prominent applications of Cloud Computing, and how they meet the requirements of reliability, availability of data, scalability of software and hardware systems and overall customer satisfaction.

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Chen, Yifan, Shaolong Shi, Xin Yao, and Tadashi Nakano. "Touchable Computing: Computing-Inspired Bio-Detection." IEEE Transactions on NanoBioscience 16, no. 8 (December 2017): 810–21. http://dx.doi.org/10.1109/tnb.2017.2769162.

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Norman, Donald A. "Collaborative computing: collaboration first, computing second." Communications of the ACM 34, no. 12 (December 1991): 88–90. http://dx.doi.org/10.1145/125319.125398.

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Hassan, Mohammad Mehedi, Md Rafiul Hassan, Victor Hugo C. de Albuquerque, and Witold Pedrycz. "Soft Computing for Intelligent Edge Computing." Applied Soft Computing 128 (October 2022): 109628. http://dx.doi.org/10.1016/j.asoc.2022.109628.

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Keyes, Robert W. "Information, computing technology, and quantum computing." Journal of Physics: Condensed Matter 18, no. 21 (May 12, 2006): S703—S719. http://dx.doi.org/10.1088/0953-8984/18/21/s01.

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Keidar, Idit. "Distributed computing column 36 distributed computing." ACM SIGACT News 40, no. 4 (January 25, 2010): 64–67. http://dx.doi.org/10.1145/1711475.1711489.

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Bao, Lina, and Shifei Ding. "Cloud computing: a new computing paradigm." International Journal of Collaborative Intelligence 1, no. 3 (2016): 167. http://dx.doi.org/10.1504/ijci.2016.077096.

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Rafael de la Llave. "Computing Some Integrals by Computing Derivatives." American Mathematical Monthly 122, no. 9 (2015): 888. http://dx.doi.org/10.4169/amer.math.monthly.122.9.888.

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Eeckhout, Lieven. "Automotive Computing, Neuromorphic Computing, and Beyond." IEEE Micro 38, no. 1 (January 2018): 4–5. http://dx.doi.org/10.1109/mm.2018.011441559.

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Sookhak, Mehdi, F. Richard Yu, Ying He, Hamid Talebian, Nader Sohrabi Safa, Nan Zhao, Muhammad Khurram Khan, and Neeraj Kumar. "Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing." IEEE Vehicular Technology Magazine 12, no. 3 (September 2017): 55–64. http://dx.doi.org/10.1109/mvt.2017.2667499.

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Chandan, P. H., and S. K. Manju Bargavi. "Green Cloud Computing: Innovating for Sustainable, Low-Impact Data Management." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 05 (May 17, 2024): 6235–40. http://dx.doi.org/10.15680/ijircce.2024.1205182.

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Cloud computing is the internet-based provision of computer services. The usage of some cloud services by individuals and businesses is expanding quickly. The rising demand for cloud infrastructure has led to a notable rise in the energy consumption of data centers. Reducing energy usage is essential to lowering carbon dioxide emissions, hence it must be addressed. Given that green cloud computing's main objective is to maximize energy efficiency, it is acknowledged as a potential solution to this issue. This paper presents green cloud computing alternatives for energy savings in addition to defining cloud computing with the key cloud service models, deployment strategies, and computing platforms. After that, these solutions were categorized based on how well they reduced energy.

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Liu, Zhi, Cheng Zhan, Ying Cui, Celimuge Wu, and Han Hu. "Robust Edge Computing in UAV Systems via Scalable Computing and Cooperative Computing." IEEE Wireless Communications 28, no. 5 (October 2021): 36–42. http://dx.doi.org/10.1109/mwc.121.2100041.

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Oesterle, F., S. Ostermann, R. Prodan, and G. J. Mayr. "Experiences with distributed computing for meteorological applications: grid computing and cloud computing." Geoscientific Model Development 8, no. 7 (July 13, 2015): 2067–78. http://dx.doi.org/10.5194/gmd-8-2067-2015.

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Abstract. Experiences with three practical meteorological applications with different characteristics are used to highlight the core computer science aspects and applicability of distributed computing to meteorology. Through presenting cloud and grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. The paper concludes that distributed computing complements and extends existing high performance computing concepts and allows for simple, powerful and cost-effective access to computing capacity.

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Schüller, F., S. Ostermann, R. Prodan, and G. J. Mayr. "Experiences with distributed computing for meteorological applications: Grid computing and Cloud computing." Geoscientific Model Development Discussions 8, no. 2 (February 10, 2015): 1171–99. http://dx.doi.org/10.5194/gmdd-8-1171-2015.

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Abstract. Experiences with three practical meteorological applications with different characteristics are used to highlight the core computer science aspects and applicability of distributed computing to meteorology. Presenting Cloud and Grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. The paper concludes that distributed computing complements and extends existing high performance computing concepts and allows for simple, powerful and cost effective access to computing capacity.

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Li, Bo. "Application of Cloud Computing in Walling Management." Advanced Materials Research 756-759 (September 2013): 1840–44. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1840.

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Facing the current inadequacy of informatization in walling management, this paper focuses on the design to use cloud computings reliability, secure data storage, convenient web services and strong capability of calculation. In addition, this paper sets up a model based on cloud-computing for walling management in governments. Firstly, the paper briefly introduces cloud computing, and then analyzes the advantage of walling management platform. Moreover, this paper points out the key issues should be solved. It will bring the positive effect of walling management informatization to government of China.

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Zhang, Xiaoling. "Optimization design of railway logistics center layout based on mobile cloud edge computing." PeerJ Computer Science 9 (April 20, 2023): e1298. http://dx.doi.org/10.7717/peerj-cs.1298.

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With the development of the economy, the importance of railway freight transportation has become essential. The efficiency of a railway logistics center depends on the types, quantities, information exchange, and layout optimization. Edge collaboration technology can consider the advantages of cloud computing’s rich computing storage resources and low latency. It can also provide additional computing power and real-time requirements for intelligent railway logistics construction. However, the cloud-side collaboration technology will introduce the wireless communication delay between the mobile terminal and the edge computing server. We designed a two-tier unloading strategy algorithm and solved the optimization problem by determining the unloading decision of each task. The cost of every task is calculated in the onboard device calculation, vehicular edge computing (VEC), and cloud computing server calculation. Simulation results show that the proposed method can save about 40% time delay compared to other unloading strategies.

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Sakhi, Abdlehak, Salah-Eddine Mansour, and Abderrahim Sekkaki. "Enhancing security mechanisms for robot-fog computing networks." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 3 (March 1, 2024): 1660. http://dx.doi.org/10.11591/ijeecs.v33.i3.pp1660-1666.

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<p>The evolution from conventional Internet usage to the internet of things (IoT) is reshaping communication norms significantly. Cloud computing, while prevalent, faces challenges like limited capacity, high latency, and network failures, especially when handling connected objects, leading to the emergence of fog computing as a more suitable approach for IoT. However, establishing secure connections among heterogeneous IoT entities is complex due to resource disparities and the unsuitability of existing security protocols for resource-constrained devices. This article explores fog computing's architecture, drawing comparisons with cloud computing while emphasizing its significance within the realm of IoT. Moreover, it delves into the practical application of fog computing within the context of the robot teacher project. Subsequently, our exploration introduces an advanced mutual authentication protocol, centered around hashed message authentication code (HMAC), aimed at enhancing the security infrastructure between the robot and the fog computing server.</p>

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Mangla, Cherry, Shalli Rani, and Henry Kwame Atiglah. "Secure Data Transmission Using Quantum Cryptography in Fog Computing." Wireless Communications and Mobile Computing 2022 (January 22, 2022): 1–8. http://dx.doi.org/10.1155/2022/3426811.

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Fog computing’s idea is to bring virtual existence into objects used on a daily basis. The “objects” layer of fog architecture is also known as the smart object layer (SOL). SOL has provided the fog network with a strong platform to outperform. Although the fog architecture decentralizes data, uses more data centers, and collects and transmits it to adjacent servers for faster processing in fog networks, it faces several security challenges. The security problems of fog computing need to be alleviated for the exploitation of all benefits of fog computing in classical networks. This article has addressed the security challenges in fog computing, potential solutions via quantum cryptography, a use case portraying the importance of quantum cryptography in fog computing along future scope, and research directions.

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Journal articles on the topic 'Computing'

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