Our basic idea is to intentionally cache data at a set of network central locations (NCLs), which can be easily accessed by other nodes in the network. We develop an efficient approach to NCL selection in DTNs based on a probabilistic selection metric. The selected NCLs achieve high chances for prompt response to user queries with low overhead in network storage and transmission. We propose a data access scheme to probabilistically coordinate multiple caching nodes for responding to user queries. We furthermore optimize the tradeoff between data accessibility and caching overhead, to minimize the average number of cached data copies in the network. We propose a utility-based cache replacement scheme to dynamically adjust cache locations based on query history, and our scheme achieves good tradeoff between the data accessibility and access delay. Extensive trace-driven simulations show that our approach significantly improves data access performance compared to existing schemes.
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