We present the lowest-path cost to destination scheme for identification of the most suitable node for data caching. The scheme identifies the network node that yields the lowest-cost path for delivering data to demanding users. This scheme is applied to information centric networks (ICN) that consider two different data consumption modes: frequently and sporadically. We consider the use of Software-Defined Networking (SDN) to realize the distribution of data on identified network nodes and enable routing towards ICN caching nodes. We apply two different methods to evaluate the path costs: Dijkstra algorithm and Integer Linear Programming (ILP). Our results show that both adopted schemes provide similar results, converging into the identification of the same ICN caching nodes. We provide example of different scenarios and resulting costs. We also apply the proposed scheme to identify a stand-by node in case the most economical nodes fails, using the proposed scheme. We show that there is a trade-off between the extent of demand and the location of routers in the network.