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In the spatial data grid, the distribution of query and the data is unevenly some resource become hotspot and the hotspots are changing over time, which may cause the global load unbalanced, this dynamic problem becomes a key challenge in Data Grid. Data replication is a way to deal with this problem, which improves data availability, reduces latency and increases throughput. In this paper, we present a new replication approach which is adaptive, completely decentralized, and based on swarm intelligence which is intrinsically a bottom-up approach. Every site in the grid system has a single agent, which is serving as containers for data, following simple rules of behavior and without knowing any global information. The strategy that agents follow includes which data to create replica and where the replica is locating. The local interactions and simple action between agents give a fairly optimal replication location solution globally. We carried the experiments using OptorSim for the EU Data Grid Testbed 1. Experimental results show that our approach performs better than No replication and when the scale of jobs is big, our method will outperform the Economic Model, but the space consumption is proportional.