Biblio

Recently, network usage has evolved from resource sharing between hosts to content distribution and retrieval. Some emerging network architectures, like Named Data Networking (NDN), focus on the design of content-oriented network paradigm. However, these clean-slate network architectures are difficult to be deployed progressively and deal with the new communication requirements. Multi-Identifier Network (MIN) is a promising network architecture that contains push and pull communication semantics and supports the resolution, routing and extension of multiple network identifiers. MIN's original design was proposed in 2019, which has been improved over the past two years. In this paper, we present the current design and implementation of MIN. We also propose a fallback-based identifier extension scheme to improve the extensibility of the network. We demonstrate that MIN outperforms NDN in the scenario of progressive deployment via IP tunnel.

The disadvantages and inextensibility of the traditional network require more novel thoughts for the future network architecture, as for ICN (Information-Centric Network), is an information centered and self-caching network, ICN is deeply rooted in the 5G era, of which concept is user-centered and content-centered. Although the ICN enables cache replacement of content, an information distribution scheduling algorithm is still needed to allocate resources properly due to its limited cache capacity. This paper starts with data popularity, information epilepsy and other data related attributes in the ICN environment. Then it analyzes the factors affecting the cache, proposes the concept and calculation method of Gene value. Since the ICN is still in a theoretical state, this paper describes an ICN scenario that is close to the reality and processes a greedy caching algorithm named GDGCA (Gene Driven Greedy Caching Algorithm). The GDGCA tries to design an optimal simulation model, which based on the thoughts of throughput balance and satisfaction degree (SSD), then compares with the regular distributed scheduling algorithm in related research fields, such as the QoE indexes and satisfaction degree under different Poisson data volumes and cycles, the final simulation results prove that GDGCA has better performance in cache scheduling of ICN edge router, especially with the aid of Information Gene value.