The popularity of distributed file systems continues to grow in last years. The reasons they are preferred over traditional centralized systems include fault tolerance, availability, scalability and performance. In this paper, we propose a framework for analyzing peer-to-peer content distributed technologies and their applications in the cooperative solving of combinatorial optimization problems. Our approach, which follows the Content Addressable Network model, is scalable, fault-tolerant and self-organizing; we improved also load distribution at the insertion and deletion of nodes. We use this network for the classical ”graph coloring” problem, in order to reduce the computational time for its cooperative solving.