Dynamic Performance Optimization for Cloud Computing Using MMm Queueing System

Abstract EN

Successful development of cloud computing has attracted more and more people and enterprises to use it.

On one hand, using cloud computing reduces the cost; on the other hand, using cloud computing improves the efficiency.

As the users are largely concerned about the Quality of Services (QoS), performance optimization of the cloud computing has become critical to its successful application.

In order to optimize the performance of multiple requesters and services in cloud computing, by means of queueing theory, we analyze and conduct the equation of each parameter of the services in the data center.

Then, through analyzing the performance parameters of the queueing system, we propose the synthesis optimization mode, function, and strategy.

Lastly, we set up the simulation based on the synthesis optimization mode; we also compare and analyze the simulation results to the classical optimization methods (short service time first and first in, first out method), which show that the proposed model can optimize the average wait time, average queue length, and the number of customer.