There has been extensive research on cooperative distributed data caching in ad hoc networks. However, most of the work has focused on how to reduce the average delay of requests and improve the packet delivery ratio, etc; not much work has been done to study the steady-state status achieved by distributed caching algorithms. Information related to steady-state status includes the convergence time of the caching algorithms, the final data cache placement in the network, the stabilized cost performance, and the performance comparison of distributed caching algorithms with an optimal centralized caching solution. Previous theoretical results show that to minimize the average access cost in the network, the optimal number of replicas of each data object is proportional to the square root (or two-thirds) of the data’s access frequency. In this work, we empirically show that the optimal replica number not only depends on the access frequencies of data, but also depends on the storage capacity of each node. We propose a heuristic model studying both cooperative, hybrid, and selfish caching steady-states in ad hoc networks. We formulate and solve the data caching problem optimally using integer linear programming (ILP) in order to validate our findings with regard to access frequency. We also provide empirical data regarding the steady-state cost of data based on the storage capacity of the nodes in the network. Via extensive ns-2 simulations [10], we gain some insight regarding the steady-states of distributed data caching.