Research Article An Integrated Node Selection Model Using FAHP and FTOPSIS for Data Retrieval in Ubiquitous Computing Belal Z. Hassan, 1 Ahmed. A. A. Gad-Elrab , 1,2 Mohamed S. Farag, 1 and Shaban E. Abo Youssef 1 1 Department of Mathematics and Computer Science, Faculty of Science, Al-Azhar University, Cairo, Egypt 2 Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia Correspondence should be addressed to Ahmed. A. A. Gad-Elrab; asaadgad@azhar.edu.eg Received 16 June 2022; Revised 18 August 2022; Accepted 20 August 2022; Published 22 September 2022 Academic Editor: Musavarah Sarwar Copyright © 2022 Belal Z. Hassan et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Ubiquitous computing (UC) is an advanced computing concept that makes services and computing available everywhere and anytime. In UC, data lies at the heart of all UC applications, and the key technologies that are required to make UC a reality are data and task management. In this context, retrieving data is influenced by the dynamic nature of these systems in addition to human and sensor failures. So the main problem is how to select the most appropriate service provider for retrieving data. Retrieving data is a complex issue that requires an extensive evaluation process and is one of the biggest challenges in UC. In addition, not every eventuality in these systems can be predicted due to their dynamic nature. As a result, there is a strong need to address the uncertainty in context data. In this paper, to assist users to efficiently select their most preferred service provider for retrieving data, a new fuzzy integrated multicriteria decision-making model, which meets quality of context (QoC) and quality of service (QoS) and satisfies user quality requirements and needs, is proposed. e proposed model is based on four stages. In the initial stage, the identification of evaluation criteria is performed due to the varying importance of the selected criteria. In the second stage, a fuzzy Analytical Hierarchy Process (FAHP) procedure is utilized to assign importance weights to each criterion. In the third stage, the fuzzy Technique for Order Preference by Similarity of an Ideal Solution (FTOPSIS) is used to evaluate and measure the performance of each alternative. Finally, sensitivity analysis is performed to check the robustness and the applicability of the proposed model. 1. Introduction Currently, the human life is a world full of computing devices as shown in Figure 1. By 2025, the number of smart device subscribers will have reached 5.9 billion. Due to this increase, computers are playing an ever-increasing role in the daily lives of people. As a results, ubiquitous computing (UC) [1] can be considered as a complete view for the future that is move near to implementing at an hasten space [2]. In UC, the computing devices are embedded into the physical environment [3, 4], so the users can interact with the devices at the same time they interact with the physical environment in a highly distributed fashion. e diverse devices are linked to each other and have diverse sizes and input and output capabilities depending on their objectives, which differ in terms of hardware components, operating systems, and capability. ese features of UC inspire a need for interaction methods that are radically diverse from the desktop computer interactions. e ubiquitous computing concept has been used by several systems. ey are characterized by their ability to adapt their operation to the surrounding context to improve usability and efficacy. Because of the wide spread and het- erogeneity of devices in the ubiquitous computing environ- ment, the dynamic nature of the environment, the frequent changes in user needs, and the possibility of unforeseen events during execution, these systems pose considerable challenges [2]. Indeed, these systems use a variety of devices, sensors, and networks to form a heterogeneous distributed environment, integrated into the daily activities of users. Hindawi Applied Computational Intelligence and So Computing Volume 2022, Article ID 8092432, 16 pages https://doi.org/10.1155/2022/8092432