Enhanced techniques to measure the execution time of distributed and cloud computing systems

^1,2,3,4,5 College of Engineering, Department of Computer Engineering, Knowledge University, Erbil, Iraq
⁶ College of Engineering, Department of System and Networks Computer, Damascus University

^* Corresponding author: yousif.jghef@knu.edu.iq

Abstract

ICT giants include cloud computing and distributed systems. Researchers have ignored the idea of merging distributed systems and cloud computing to examine millisecond execution times and megabyte capacity. The system used Google’s API to download files to the cloud. The system sent files to the principal server. Now there are two ways to calculate execution time accurately. The first scenario uses threads to construct clients and servers. Second, pool threads are used. This article examines file capacity and execution time. The system demonstrated how cloud computing influences distributed systems’ execution time and capacity in these two circumstances. According to the testing, the first scenario (multi threads) takes less time than the second (pool threads), although not significantly. 4874 milliseconds are needed to transfer 50 files, each weighing 90 MB, utilizing multiple threads. However, it takes 5541 milliseconds to send these files using the pool threads. Keep in mind that utilizing the first scenario is bad for computer hardware. In order to load files into the system, this work used hash table software structure in conjunction with network technologies like TCP sockets, APIs, threads, and thread pool techniques between the client and servers.