Fast Replica Placement and Update Strategies in Tree Networks Data replication enhances data availability and thereby improves the system reliability and efficiency while reduces access latency and communication cost. A critical issue in data replication is to wisely place data replicas which involves identifying the best possible nodes to duplicate data according to user requests. In this paper, we address the problem of replica placement and update in tree networks, where some nodes of the network contain pre-existing replicas. It is obvious that reusing a pre-existing replica leads to smaller cost than creating a new replica, thus it is necessary to take full advantage of the pre-existing replicas. The only previous work that consider the same problem tries to find the optimal solution by developing a dynamic programming algorithm which runs in O(N5). However, this approach is not suitable for practical situation where the user requests change frequently. In this paper, we develop efficient algorithms to accelerate the replica placement without causing obvious degradation in solution quality. We first propose an efficient heuristic algorithm (named GreedyRP) for quickly placing replicas when users change their requests. Then a tabu search algorithm (named TSRP) is customized to further refine the solution obtained by algorithm GreedyRP. Experimental results show that, on tree networks with 600 nodes and 150 pre-existing replicas, the proposed algorithms can accelerate the previous work by 87.97% while the quality degradation is bounded by 2.49% in comparison to the optimal solution.