The shared data space model has proven to be an effective paradigm for building distributed applications. However, building an efficient distributed implementation remains a challenge. A plethora of different implementations exists. Each of them has a specific policy for distributing data across nodes. Often, these policies are tailored to a specific application domain. Thus, those systems may often perform poorly with applications extraneous to their domain. In this paper, we propose that implementations of a distributed shared data space system should provide mechanisms for tailoring data distribution policies. Through this flexibility the shared data space system can cope with a wide spectrum of application classes. The need for this flexibility is illustrated by experiments which show that there is no single distribution policy that works well in all cases.
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