Distributed GA for popularity based partial cache management in ICN

Information Centric Networks (ICNs) is a new architecture for the Future Internet to deliver content at large-scale. It relies on named data and caching features, which consists of storing content across the delivery path to serve forthcoming requests. In this paper, we study the problem of finding the optimal assignment of the objects in the available caches in ICN. The optimization problem is to cache objects in order to minimize overall network overhead. We formulate this problem as a combinatorial optimization problem. We show that this optimization problem is NP complete. Metaheuristic methods are considered as effective methods for solving this problem, Genetic Algorithm (GA) is one of those algorithms that can solve this problem efficiently. We will adapt cache management system based on GA for solving the considered problem. In contrast to traditional locally caching systems this algorithm consider both global and local search and make caching decisions about where and which item will be cached in order to minimize overall network overhead.