Biblio

In recent years, ICN (Information-Centric Networking) has been under the spotlight as a network that mainly focuses on transmitted and received data rather than on the hosts that transmit and receive data. Generally, the communication networks such as ICNs are required to be robust against network failures caused by attacks and disasters. One of the metrics for the robustness of conventional host-centric networks, e.g., TCP/IP network, is reachability between nodes in the network after network failures, whereas the key metric for the robustness of ICNs is content availability. In this paper, we focus on an arbitrary ICN network and derive the content availability for a given probability of node removal. Especially, we analytically obtain the average content availability over an entire network in the case where just a single path from a node to a repository, i.e., contents server, storing contents is available and where multiple paths to the repository are available, respectively. Furthermore, through several numerical evaluations, we investigate the effect of the structure of network topology as well as the pattern and scale of the network failures on the content availability in ICN. Our findings include that, regardless of patterns of network failures, the content availability is significantly improved by caching contents at routers and using multiple paths, and that the content availability is more degraded at cluster-based node removal compared with random node removal.

The network robustness is defined by how well its vertices are connected to each other to keep the network strong and sustainable. The change of network robustness may reveal events as well as periodic trend patterns that affect the interactions among vertices in the network. The evaluation of network robustness may be helpful to many applications, such as event detection, disease transmission, and network security, etc. There are many existing metrics to evaluate the robustness of networks, for example, node connectivity, edge connectivity, algebraic connectivity, graph expansion, R-energy, and so on. It is a natural and urgent problem how to choose a reasonable metric to effectively measure and evaluate the network robustness in the real applications. In this paper, based on some general principles, we design and implement a benchmark, namely BMNR, for the metrics of network robustness. The benchmark consists of graph generator, graph attack and robustness metric evaluation. We find that R-energy can evaluate both connected and disconnected graphs, and can be computed more efficiently.