Performance Evaluation of Reliable Data Scheduling for Erlang Multimedia in Cloud Computing

Cloud computing emerges huge number of servers connected via a real-time computer network such as broadband network. Cloud computing refers to a distributed network as it has a capability to run an application on many servers simultaneously. In this paper we present a queuing model that takes reliable data scheduler into account and computes performance characteristics like mean waiting time, mean traversal time, utilization, throughput, and mean queue length. Reliable data will be aware and dynamically scheduled in order to make the decision after the arrival of requested job. In addition to these scheduling algorithms we investigate the resource allocation solutions with a distributed Erlang multimedia data. A queuing model is employed in order to study, analyze, and evaluate the performance of each scheduling algorithm. An approximation method based on Mean Value Analysis (MVA) in queuing theory will be introduced. Results regarding performance metrics from both simulation and approximation then are compared. The difference between simulation's and approximation method is insignificant. Results as well confirm that schedulers can be effectively applied in a Cloud Computing environment in terms of fairness and load balancing centric.