A novel content updating policy based on dynamic storage balancing for clustered streaming media system

The problem of dynamic content deployment for clustered streaming media system consisting of homogeneous servers is discussed in this paper. We propose a dynamic storage balancing (DSB) based content updating strategy to lower the service blocking probability, to balance the load of media servers and to reduce the update cost. A relatively short time window is adopted to predict the changing popularity of all multimedia files. Unlike other exiting policies applying the predicted result to replicating and de-replicating, we assign it properly to each replica in the cluster for the purpose of unifying every server's access probability (AP), in other words, making the system be in a condition of DSB. Then we gradually replicate the newly popular objects to enhance the ability of DSB. Meanwhile, we adopt a de-replication strategy with zero in-service request migration cost to avoid storage space being exhausted by replicas of previously popular objects. The simulation analysis shows that the proposed policy can achieve an outstanding system performance.