MRPGA: A Genetic-Algorithm-based In-network Caching for Information-Centric Networking

Abstract

In-network caching is a basic feature of ICN architecture. Traditional ICN is distributed, which means the locations of content blocks cannot be adjusted precisely. Therefore, the cache allocation in traditional ICN is hard to approach optimization. With the aid of centralized controllers provided by SDN, ICN can manipulate the cache allocation with high flexibility. Heuristic algorithms have been applied to the cache allocation of ICN with centralized controllers but cannot guarantee the feasibility of solutions because of the feature of randomness. This paper proposes a caching strategy named MRPGA based on genetic algorithms. The mechanism of MRPGA guarantees the feasibility of solutions and accelerates convergence. Also, the simulations show that MRPGA figures out a better cache distribution in a shorter time than the genetic algorithm.