An event-driven dynamic load balancing strategy for streaming media clustered server systems

Based on stochastic switching model, an event-driven dynamic load balancing strategy is presented for the streaming media clustered server systems. This strategy increases the server cluster availability by balancing the workloads among the servers within a cluster. Additionally, it improves the access hit ratio of cached files in delivery servers to alleviate the limitation of I/O bandwidth of storage node. First, the load balancing problem is formulated as a two-layer semi-Markov switching state-space control process. Then, an online policy iteration algorithm is proposed to optimize the file grouping policy. By utilizing the features of the event-driven policy, the proposed optimization algorithm is adaptive and with less computational cost. Simulation results demonstrate the effectiveness of the proposed approach.