  In this paper, cooperative caching is investigated in fog radio access
networks (F-RAN). To maximize the offloaded traffic, cooperative caching
optimization problem is formulated. By analyzing the relationship between
clustering and cooperation and utilizing the solutions of the knapsack
problems, the above challenging optimization problem is transformed into a
clustering subproblem and a content placement subproblem. To further reduce
complexity, we propose an effective graph-based approach to solve the two
subproblems. In the graph-based clustering approach, a node graph and a
weighted graph are constructed. By setting the weights of the vertices of the
weighted graph to be the incremental offloaded traffics of their corresponding
complete subgraphs, the objective cluster sets can be readily obtained by using
an effective greedy algorithm to search for the max-weight independent subset.
In the graph-based content placement approach, a redundancy graph is
constructed by removing the edges in the complete subgraphs of the node graph
corresponding to the obtained cluster sets. Furthermore, we enhance the caching
decisions to ensure each duplicate file is cached only once. Compared with
traditional approximate solutions, our proposed graph-based approach has lower
complexity. Simulation results show remarkable improvements in terms of
offloaded traffic by using our proposed approach.
