Wireless sensor networks generate a huge quantity of data which required to be accumulated until it is needed. An appropriate data storage protocol will permit for rapid storage and querying with negligible communications over the network. For accumulating data in the network, it is vital to guarantee that the data can be accessed from other nodes for an elongated period of time. Without a suitable data storage method, the query would have to be flooded all through the network to discover the appropriate node. Flooding is extremely costly; consequently a better scheme would keep energy by discovering a way to lessen the communication costs. Numerous protocols have been formulated which tries to make data storage and querying well-organized. In view of the fact that WSNs are deployed by means of a large number of nodes, these nodes have to be cost-efficient with the intention of making the WSN reasonable to maintain. This indicates that nodes are extremely limited in their existing energy and computational power. Since these nodes have such restricted capacity, protocols for conventional wireless networks cannot be exploited for any of the nodes' operations, hence new protocols must be formulated. The prime challenge for these new protocols is to lessen energy costs as much as feasible. In this paper, optimal data storage protocol based on swarm intelligence is proposed using an Enhanced Bat Algorithm (EBA) that can construct global optimal data storage position in linear, grid, and mesh network topologies. In order to reduce the computation of optimal data storage in the mesh network topology, near-optimal data storage EBA algorithm is presented to find a local optimal position. The proposed algorithm is compared against three data storage protocols such as Geographic Hash Table (GHT), Optimal Data Storage (ODS) and Distributed Index-based Dominating Set (DIDS). An investigation is done on the network lifetime, delay, throughput and packet loss for each protocol and it is found that EBA-ODS outperforms other protocols. © Research India Publications.