Baoling Qin^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 255-267, 2023, DOI:10.32604/iasc.2023.037556

Abstract Although the Internet of Things has been widely applied, the problems of cloud computing in the application of digital smart medical Big Data collection, processing, analysis, and storage remain, especially the low efficiency of medical diagnosis. And with the wide application of the Internet of Things and Big Data in the medical field, medical Big Data is increasing in geometric magnitude resulting in cloud service overload, insufficient storage, communication delay, and network congestion. In order to solve these medical and network problems, a medical big-data-oriented fog computing architecture and BP algorithm application are proposed, and its structural advantages and characteristics… More >

Sanghyuck Nam¹, Jaehwan Lee², Kyoungchan Kim³, Mingyu Jo¹, Sangoh Park^1,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3457-3469, 2023, DOI:10.32604/csse.2023.035428

Abstract Recently, research on a distributed storage system that efficiently manages a large amount of data has been actively conducted following data production and demand increase. Physical expansion limits exist for traditional standalone storage systems, such as I/O and file system capacity. However, the existing distributed storage system does not consider where data is consumed and is more focused on data dissemination and optimizing the lookup cost of data location. And this leads to system performance degradation due to low locality occurring in a Wide Area Network (WAN) environment with high network latency. This problem hinders deploying distributed storage systems to… More >

Ashraf Ali^*, Omar A. Saraereh

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2203-2219, 2022, DOI:10.32604/cmc.2022.025994

Abstract The Internet has become an unavoidable trend of all things due to the rapid growth of networking technology, smart home technology encompasses a variety of sectors, including intelligent transportation, allowing users to communicate with anybody or any device at any time and from anywhere. However, most things are different now. Background: Structured data is a form of separated storage that slows down the rate at which everything is connected. Data pattern matching is commonly used in data connectivity and can help with the issues mentioned above. Aim: The present pattern matching system is ineffective due to the heterogeneity and rapid… More >

Moath Alsafasfeh^1,*, Zaid A. Arida², Omar A. Saraereh³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5355-5380, 2022, DOI:10.32604/cmc.2022.024093

Abstract Deep neural networks (DNN) are widely employed in a wide range of intelligent applications, including image and video recognition. However, due to the enormous amount of computations required by DNN. Therefore, performing DNN inference tasks locally is problematic for resource-constrained Internet of Things (IoT) devices. Existing cloud approaches are sensitive to problems like erratic communication delays and unreliable remote server performance. The utilization of IoT device collaboration to create distributed and scalable DNN task inference is a very promising strategy. The existing research, on the other hand, exclusively looks at the static split method in the scenario of homogeneous IoT… More >

Moazam Ali, Susmit Bagchi^*

Intelligent Automation & Soft Computing, Vol.24, No.4, 2018, DOI:10.31209/2018.100000043

Abstract Due to the rapid advancements and developments in wide area networks and powerful computational resources, the load balancing mechanisms in distributed systems have gained pervasive applications covering wired as well as mobile distributed systems. In large-scale distributed systems, sharing of distributed resources is required for enhancing overall resource utilization. This paper presents a comprehensive study and detailed comparative analysis of different load balancing algorithms employing fuzzy logic and mobile agents. We have proposed a hybrid architecture for integrated load balancing and monitoring in distributed computing systems employing fuzzy logic and autonomous mobile agents. Furthermore, we have proposed a smooth and… More >

Yu-Cheng Chou¹, Wei-Chieh Liao², Yan-Liang Chen², Ming Chang², Po Ting Lin³

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 79-90, 2019, DOI:10.31209/2018.100000011

Abstract This paper presents the Distributed Heterogeneous Inspection System (DHIS), which comprises two CUDA workstations and is equipped with CPU distributed computing, CPU concurrent computing, and GPU concurrent computing functions. Thirty-two grayscale images, each with 5,000× 12,288 pixels and simulated defect patterns, were created to evaluate the performances of three system configurations: (1) DHIS; (2) two CUDA workstations with CPU distributed computing and GPU concurrent computing; (3) one CUDA workstation with GPU concurrent computing. Experimental results indicated that: (1) only DHIS can satisfy the time limit, and the average turnaround time of DHIS is 37.65% of the time limit; (2) a… More >

Yinghang Jiang¹, Qi Liu^2,3,*, Williams Dannah¹, Dandan Jin², Xiaodong Liu³, Mingxu Sun^4,*

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 713-729, 2020, DOI:10.32604/cmc.2020.04604

Abstract Hadoop is a well-known parallel computing system for distributed computing and large-scale data processes. “Straggling” tasks, however, have a serious impact on task allocation and scheduling in a Hadoop system. Speculative Execution (SE) is an efficient method of processing “Straggling” Tasks by monitoring real-time running status of tasks and then selectively backing up “Stragglers” in another node to increase the chance to complete the entire mission early. Present speculative execution strategies meet challenges on misjudgement of “Straggling” tasks and improper selection of backup nodes, which leads to inefficient implementation of speculative executive processes. This paper has proposed an Optimized Resource… More >

Hangjun Zhou^1,2,*, Guang Sun¹, Sha Fu¹, Wangdong Jiang¹, Tingting Xie³, Danqing Duan¹

CMC-Computers, Materials & Continua, Vol.56, No.1, pp. 73-89, 2018, DOI: 10.3970/cmc.2018.02411

Abstract In the large-scale Distributed Virtual Environment (DVE) multimedia systems, one of key challenges is to distributedly preserve causal order delivery of messages in real time. Most of the existing causal order control approaches with real-time constraints use vector time as causal control information which is closely coupled with system scales. As the scale expands, each message is attached a large amount of control information that introduces too much network transmission overhead to maintain the real-time causal order delivery. In this article, a novel Lightweight Real-Time Causal Order (LRTCO) algorithm is proposed for large-scale DVE multimedia systems. LRTCO predicts and compares… More >

I. Kvasnica¹, P. Kvasnica²

CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.6, pp. 447-462, 2015, DOI:10.3970/cmes.2015.107.447

Abstract The issue of simulation of decentralized mathematical models is discussed in the paper. The authors’ knowledge is based on a theory of design of decentralized computer control systems. Their knowledge is gained in the process of designing mathematical models that are simulated. A decomposed control system is required to meet the conditions of observation and control. The methodology of a multi-model design is based on main principles of object orientation such as abstraction, hierarchy, and modularity. Modelling on a parallel architecture has an impact on a simulator system. The system is defined by the equations shown below. An important part… More >

J.E. Lee¹and S.J. Kim²

CMES-Computer Modeling in Engineering & Sciences, Vol.86, No.2, pp. 93-112, 2012, DOI:10.3970/cmes.2012.086.093

Abstract As the option trading nowadays has become popular, it is important to simulate efficiently large amounts of option pricings. The purpose of this paper is to show valuations of large amount of options, using network distribute computing resources. We valuated 108 options simultaneously on the self-made cluster computer system which is very inexpensive, compared to the supercomputer or the GPU adopting system. For the numerical valuations of options, we developed the option pricing software to solve the Black-Scholes partial differential equation by the finite element method. This yielded accurate values of options and the Greeks with reasonable computational times. This… More >