Optimizing the profit of on-demand multimedia service via a server-dependent queuing system
This study presents a profit maximization model that adopts the number of requests for image or voice transferring services on a network as decision variables for when to switch a second server on and off based on the costs of using a second server and of users waiting. A Markovian queue with a number of servers depending upon queue length and finite capacity is discussed. The data of interarrival time and service times of requests are collected by observing a queuing system. An empirical Bayesian method is then applied to estimate the traffic intensity of the system, which denotes the need for host computers. The mean number of transfer requests in the system and the queue length of transfer requests are calculated as the characteristic values of the system.
Recently, a cost minimization method to determine the lot size for the EOQ/EPQ models with backorders was published. This method is based on the well-known arithmetic-geometric mean inequality. Although the cost minimization method is correct and interesting, it does not focus on deriving the backorders level. This paper proposes another simple approach. The proposed method finds both the lot size and the backorders level.