A Distributed Energy Consumption Optimization Algorithm for Content-Centric Networks via Dual Decomposition

Due to the in-network caching capability, Content-Centric Networking (CCN) has emerged as one of the most promising architectures for the diffusion of contents over the Internet. Most existing works on CCN focus on network resource utilization, and the energy efficiency aspect is largely ignored. In this paper, we formulate the energy consumption issue as a Mixed Integer Linear Programming (MILP) problem, and propose a centralized solution via spanning tree heuristic and a fully distributed energy consumption optimization algorithm via dual decomposition (DD) to solve the problem for CCN. The dual decomposition method transforms the centralized energy consumption optimization problem into the router status, link status, and link flow subproblems. Simulation results reveal that the proposed scheme exhibits a fast convergence speed, and achieves superior energy efficiency compared to other widely used schemes in CCN.