9th International Engineering Conference on Sustainable Technology and Development ( 9 th IEC-2023) , Tishk and Erbil Polytechnic University, Erbil-Iraq 979-8-3503-3506-4/23/$31.00 ©2023 IEEE 45 Design and Analysis of Proposed Smartphone-based Distributed Parallel Processing System Nashma Taha Muhammed IT Department Sulaimani Polytechnic University Sulaymani, Iraq nashma.taha.m@spu.edu.iq Zryan Najat Rashid Computer Network Department Sulaimani Polytechnic University Sulaymani, Iraq zryan.rashid@spu.edu.iq Subhi R. M. Zeebaree Energy Eng. Department Duhok Polytechnic University Duhok, Iraq subhi.rafeeq@dpu.edu.krd Yousif Sufyan Jghef Computer Eng. Department Knowledge University Erbil, Iraq yousif.jghef@knu.edu.iq Rowaida Khalil Ibrahim Computer Science Department University of Zakho Duhok, Iraq rowaida.ibrahim@uoz.edu.krd Teba Mohammed Ghazi Sami Computer Science Department University of Zakho Duhok, Iraq teba.sami@uoz.edu.krd Abstract— Online storage and use of digital assets and applications are both aspects of cloud computing. Through a computer network, distributed information systems store and transmit data. Data and effort have both grown for studying and keeping track of outcomes. Cloud-based parallel processing techniques must be improved. Our research hastens the resolution of interactive composite jobs. In this innovative architecture, cell phones act as servers for distributed parallel processing and cloud computing. Users with restricted availability could find the update useful for completing challenging jobs. The recommended strategy is supported by cloud computing, which may expand to infinity servers (webserver). Servers between clients and servers are automatically registered by web servers. Cloud storage and client- side matrices (web server). To ensure timely completion, the server distributes matrix algebra assignments to all subscribed workstations. Before transmitting results to the user, the server uploads them to the cloud. A large number of sets of two- dimensional matrices were requested from the user, and the responses were compared to the total number of servers that were available. Keywords— Parallel Processing, Cloud Comuting, Distributed Parallel Processing, Web server. I. INTRODUCTION In an idealistic situation, a single, dependable, and trustworthy computer would immediately handle all computing needs. In practice, however, no single computer could be efficient, dependable, or even available enough to meet such a requirement. Because of the goals of efficiency, dependability, security, and the enormous benefits of interactivity, distributed computing is the sole option [1]. A distributed system is a collection of autonomously computing parts that appear to consumers as a single system, with each computing element capable of behaving separately from the others [2]. Tasks, as well as resources, are physically spread between multiple computers in a distributed system. A distributed system's scalability may be defined in three distinct ways. a. scalability in terms of size, b. scalability in terms of geography, and c. administrative scalability [3]. Distributed systems are extraordinarily strong and useful for computer systems that are recognized for solving jobs and issues in a feasible and timely manner [4]. Hardware costs have decreased, and computer networking capabilities have improved. This has led to the utilization of large-scale parallel and distributed computing systems, which have grown in popularity. Distributed computing systems can boost performance while also allowing for resource sharing [5]. By permitting programs to be handled in parallel, distributed systems improve a system's performance [3]. For complicated applications to execute jobs effectively, parallel processing is required [6]. Mobile nodes are a viable distributed computing concept that has been used in a variety of contexts. Parallel processing is also one of the fields that might benefit from the deployment of mobile agent technology [7]. In the past, mobile devices have been used for distributed computing in a variety of different ways. Some examples of these uses include offloading data and processing to remote cloud servers or establishing distributed computing clusters by employing local mobile devices [8]. The idea of computing via mobile devices has grown more realistic than the traditional technique [9]. Mobile computing is not only the face of computing change, but so are our choices as we gain knowledge, generate ideas, and collaborate to solve problems [10]. Along with the rapid expansion in computing capability of mobile devices, particularly smartphones, the quantity of data that must be processed is expanding as the amount of data generated by each user. Furthermore, the number of mobile apps that strongly depend on resource utilization has been steadily expanding. In recent years, it has been accomplished by transferring data and 2023 9th International Engineering Conference on Sustainable Technology and Development (IEC) | 979-8-3503-3506-4/23/$31.00 ©2023 IEEE | DOI: 10.1109/IEC57380.2023.10438822 Authorized licensed use limited to: UNIVERSITY TEKNOLOGI MALAYSIA. Downloaded on February 26,2024 at 12:21:20 UTC from IEEE Xplore. Restrictions apply.