Performance Measurement of Distributed Systems via Single-Host Parallel Requesting using (Single, Multi and Pool) Threads

Distributed systems and cloud computing are essential in IT (ICT). Scholars have not contemplated merging distributed systems and cloud computing to measure execution time in milliseconds and capacity in gigabytes. Distributed Systems and Cloud Computing Execute Time and Capacity Methodology This title covered two networking types. Multi-scenario distributed networking begins. A TCP socket links a client-server application (Transmission Control Protocol). This example also networks between computers. In another example, Remote Method Invocation Technology (RMI) links subservers to the main server to handle all client inquiries. Second-generation networking involves distributed systems and cloud computing. Google's API downloaded files to my machine and sent them to the main server. Other examples include using numerous computers or a client server software on the same machine. Multi-client and server threads helped the system find correct results. Pool threads were used elsewhere. This thesis examines execution time and file capacity. The system showed how cloud computing affects distributed systems in two ways to apply many scenarios and draw conclusions (execution time and capacity). This project utilizes TCP sockets, RMI, and API. Threads and a hash table software structure were used to load data into the system between the client and the server.