Manar Mohamed Hafez^1,*, Essam Eldin F. Elfakharany¹, Amr A. Abohany², Mostafa Thabet³

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 943-958, 2023, DOI:10.32604/cmc.2023.034078

Abstract Big data is usually unstructured, and many applications require the analysis in real-time. Decision tree (DT) algorithm is widely used to analyze big data. Selecting the optimal depth of DT is time-consuming process as it requires many iterations. In this paper, we have designed a modified version of a (DT). The tree aims to achieve optimal depth by self-tuning running parameters and improving the accuracy. The efficiency of the modified (DT) was verified using two datasets (airport and fire datasets). The airport dataset has 500000 instances and the fire dataset has 600000 instances. A comparison has been made between the… More >

Muhammad Hasnain¹, Imran Ghani², Seung Ryul Jeong^3,*, Aitizaz Ali¹

Computer Systems Science and Engineering, Vol.40, No.1, pp. 327-339, 2022, DOI:10.32604/csse.2022.018300

Abstract This paper presents a review of the ensemble learning models proposed for web services classification, selection, and composition. Web service is an evolutionary research area, and ensemble learning has become a hot spot to assess web services’ earlier mentioned aspects. The proposed research aims to review the state of art approaches performed on the interesting web services area. The literature on the research topic is examined using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) as a research method. The study reveals an increasing trend of using ensemble learning in the chosen papers within the last ten years.… More >

Mohamed Eb-Saad¹, Yunyoung Nam^2,*, Hazem M. El-bakry¹, Samir Abdelrazek¹

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1483-1501, 2021, DOI:10.32604/cmc.2021.017783

Abstract Web service (WS) presents a good solution to the interoperability of different types of systems that aims to reduce the overhead of high processing in a resource-limited environment. With the increasing demand for mobile WS (MWS), the WS discovery process has become a significant challenging point in the WS lifecycle that aims to identify the relevant MWSs that best match the service requests. This discovery process is a resource-consuming task that cannot be performed efficiently in a mobile computing environment due to the limitations of mobile devices. Meanwhile, a cloud computing can provide rich computing resources for mobile environments given… More >

Sulaiman Khan¹, Shah Nazir¹, Habib Ullah Khan^2,*

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 895-915, 2021, DOI:10.32604/cmc.2021.013878

Abstract During the last decade the emergence of Internet of Things (IoT) based applications inspired the world by providing state of the art solutions to many common problems. From traffic management systems to urban cities planning and development, IoT based home monitoring systems, and many other smart applications. Regardless of these facilities, most of these IoT based solutions are data driven and results in small accuracy values for smaller datasets. In order to address this problem, this paper presents deep learning based hybrid approach for the development of an IoT-based intelligent home security and appliance control system in the smart cities.… More >

Mohemmed Sha^*, Abdalla Alameen

Computer Systems Science and Engineering, Vol.36, No.1, pp. 201-211, 2021, DOI:10.32604/csse.2021.014513

Abstract The composition of the web service is a common technique to attain the best results of complex web tasks. The selection of appropriate web services, linking those services in the action flow and attaining the actual functionality of the task are the important factors to be considered. Even though different frameworks and methods have been proposed to dynamically compose web services, each method has its advantage and disadvantage over the other. Most of the methods give much importance to the Quality of Service (QoS) but fail to achieve the actual functionality after composition. This paper proposes a functionality-oriented composition technique… More >

Muhammad Hasnain¹, Seung Ryul Jeong^{2, *}, Muhammad Fermi Pasha³, Imran Ghani⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 729-752, 2020, DOI:10.32604/cmc.2020.010394

Abstract Performance anomaly detection is the process of identifying occurrences that do not conform to expected behavior or correlate with other incidents or events in time series data. Anomaly detection has been applied to areas such as fraud detection, intrusion detection systems, and network systems. In this paper, we propose an anomaly detection framework that uses dynamic features of quality of service that are collected in a simulated setup. Three variants of recurrent neural networks-SimpleRNN, long short term memory, and gated recurrent unit are evaluated. The results reveal that the proposed method effectively detects anomalies in web services with high accuracy.… More >

Zhichun Jia^{1, 2}, Qiuyang Han¹, Yanyan Li¹, Yuqiang Yang¹, Xing Xing^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1221-1235, 2020, DOI:10.32604/cmc.2020.09722

Abstract With the development of the service-oriented computing (SOC), web service has an important and popular solution for the design of the application system to various enterprises. Nowadays, the numerous web services are provided by the service providers on the network, it becomes difficult for users to select the best reliable one from a large number of services with the same function. So it is necessary to design feasible selection strategies to provide users with the reliable services. Most existing methods attempt to select services according to accurate predictions for the quality of service (QoS) values. However, because the network and… More >