G. R. Sreekanth^1,*, S. Ahmed Najat Ahmed², Marko Sarac³, Ivana Strumberger³, Nebojsa Bacanin³, Miodrag Zivkovic³

Computer Systems Science and Engineering, Vol.41, No.2, pp. 751-765, 2022, DOI:10.32604/csse.2022.020534

Abstract Fog computing provides quality of service for cloud infrastructure. As the data computation intensifies, edge computing becomes difficult. Therefore, mobile fog computing is used for reducing traffic and the time for data computation in the network. In previous studies, software-defined networking (SDN) and network functions virtualization (NFV) were used separately in edge computing. Current industrial and academic research is tackling to integrate SDN and NFV in different environments to address the challenges in performance, reliability, and scalability. SDN/NFV is still in development. The traditional Internet of things (IoT) data analysis system is only based on a linear and time-variant system… More >

S. Prakash^1,*, M. Vinoth Kumar², R. Saravana Ram³, Miodrag Zivkovic⁴, Nebojsa Bacanin⁴, Milos Antonijevic⁴

Computer Systems Science and Engineering, Vol.41, No.2, pp. 735-749, 2022, DOI:10.32604/csse.2022.020533

Abstract Breast cancer has become the second leading cause of death among women worldwide. In India, a woman is diagnosed with breast cancer every four minutes. There has been no known basis behind it, and detection is extremely challenging among medical scientists and researchers due to unknown reasons. In India, the ratio of women being identified with breast cancer in urban areas is 22:1. Symptoms for this disease are micro calcification, lumps, and masses in mammogram images. These sources are mostly used for early detection. Digital mammography is used for breast cancer detection. In this study, we introduce a new hybrid… More >

P. Rajeswari^*, K. Jayashree

Computer Systems Science and Engineering, Vol.41, No.2, pp. 511-524, 2022, DOI:10.32604/csse.2022.020352

Abstract Recent advancements in cloud computing (CC) technologies signified that several distinct web services are presently developed and exist at the cloud data centre. Currently, web service composition gains maximum attention among researchers due to its significance in real-time applications. Quality of Service (QoS) aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS. But these models have failed to handle the uncertainties of QoS. The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users. On the other hand, trip planning is an… More >

R. Amirthavalli^1,*, S. Thanga Ramya², N. R. Shanker³

Computer Systems Science and Engineering, Vol.41, No.2, pp. 829-847, 2022, DOI:10.32604/csse.2022.020307

Abstract In Underwater Acoustic Sensor Network (UASN), routing and propagation delay is affected in each node by various water column environmental factors such as temperature, salinity, depth, gases, divergent and rotational wind. High sound velocity increases the transmission rate of the packets and the high dissolved gases in the water increases the sound velocity. High dissolved gases and sound velocity environment in the water column provides high transmission rates among UASN nodes. In this paper, the Modified Mackenzie Sound equation calculates the sound velocity in each node for energy-efficient routing. Golden Ratio Optimization Method (GROM) and Gaussian Process Regression (GPR) predicts… More >

K. Ezhilarasi^1,*, G. Maria Kalavathy²

Computer Systems Science and Engineering, Vol.41, No.2, pp. 569-582, 2022, DOI:10.32604/csse.2022.020280

Abstract Ontology is the progression of interpreting the conceptions of the information domain for an assembly of handlers. Familiarizing ontology as information retrieval (IR) aids in augmenting the searching effects of user-required relevant information. The crux of conventional keyword matching-related IR utilizes advanced algorithms for recovering facts from the Internet, mapping the connection between keywords and information, and categorizing the retrieval outcomes. The prevailing procedures for IR consume considerable time, and they could not recover information proficiently. In this study, through applying a modified neuro-fuzzy algorithm (MNFA), the IR time is mitigated, and the retrieval accuracy is enhanced for trouncing the… More >

Baili Zhang¹, Keke Ling^1,*, Pei Zhang^2,3, Zhao Zhang^2,3, Mingjun Zhong⁴

Computer Systems Science and Engineering, Vol.41, No.2, pp. 699-715, 2022, DOI:10.32604/csse.2022.020193

Abstract Calculating the most reliable maximum flow (MRMF) from the edge cache node to the requesting node can provide an important reference for selecting the best edge cache node in a content delivery network (CDN). However, SDBA, as the current state-of-the-art MRMF algorithm, is too complex to meet real-time computing needs. This paper proposes a set of MRMF algorithms: NWCD (Negative Weight Community Deletion), SCPDAT (Single-Cycle Preference Deletion Approximation algorithm with Time constraint) and SCPDAP (Single-Cycle Preference Deletion Approximation algorithm with Probability constraint). NWCD draws on the “flow-shifting” algorithm of minimum cost and maximum flow, and further defines the concept of… More >

Wei Fang^1,2,*, Enming Gu¹, Weinan Yi¹, Weiqing Wang¹, Victor S. Sheng³

Computer Systems Science and Engineering, Vol.41, No.2, pp. 689-698, 2022, DOI:10.32604/csse.2022.020176

Abstract With the development of image restoration technology based on deep learning, more complex problems are being solved, especially in image semantic inpainting based on context. Nowadays, image semantic inpainting techniques are becoming more mature. However, due to the limitations of memory, the instability of training, and the lack of sample diversity, the results of image restoration are still encountering difficult problems, such as repairing the content of glitches which cannot be well integrated with the original image. Therefore, we propose an image inpainting network based on Wasserstein generative adversarial network (WGAN) distance. With the corresponding technology having been adjusted and… More >

Masood Ahmad¹, Jehad F. Al-Amri², Ahmad F. Subahi³, Sabita Khatri², Adil Hussain Seh¹, Mohd Nadeem¹, Alka Agrawal^1,*

Computer Systems Science and Engineering, Vol.41, No.2, pp. 811-828, 2022, DOI:10.32604/csse.2022.020097

Abstract The current study discusses the different methods used to secure healthcare devices and proposes a quantitative framework to list them in order of significances. The study uses the Hesitant Fuzzy (HF), Analytic Hierarchy Process (AHP) integrated with Fuzzy Technical for Order Preference by Similarities to Ideal Solution (TOPSIS) to classify the best alternatives to security techniques for healthcare devices to securing the devices. The technique is enlisted to rate the alternatives based on the degree of satisfaction of their weights. The ranks of the alternatives consequently decide the order of priority for the techniques. A1 was the most probable alternative… More >

Adriano G. Passos, Tiago Cousseau, Marco A. Luersen^*

Computer Systems Science and Engineering, Vol.41, No.2, pp. 583-593, 2022, DOI:10.32604/csse.2022.020020

Abstract A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small… More >

Qunhui Zhang¹, Mengzhe Lu^3,4, Liang Dai^2,*

Computer Systems Science and Engineering, Vol.41, No.2, pp. 795-809, 2022, DOI:10.32604/csse.2022.019987

Abstract Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. But the fact is that forecasting stock prices by using various models has been suffering from low accuracy, slow convergence, and complex parameters. This study aims to employ a mixed model to improve the accuracy of stock price prediction. We present how to use a random walk based on jump-diffusion, to obtain stock predictions with a good-fitting degree by adjusting different parameters. Aimed at getting better parameters and then using the time series model to predict the data, we employed the time… More >