Neighborhoods as an abstraction for Fish-Eye State Routing

From the beginning of data networking, dynamic routing has been a challenge. Due to the constantly increasing number of devices and the introduction of multi-hop wireless networks, dynamic routing will remain an important issue for any future network architecture. Using more elaborate routing metrics for such environments is regarded as the general solution but neglects the introduction of significant overhead required to exchange the information. In this paper, we present a routing scheme which is based on metric dependent neighborhood to calculate the forwarding graph. The proposed routing scheme supports aggregation of this metric related information while disseminating routing updates to retain scalability. Simulation results with an exemplary metric based on link stability information show the feasibility of this aggregation approach and the improvement with respect to node reachability and reliable communication in self-organizing wireless networks. Moreover, we implemented this routing scheme on an autonomic networking architecture (ANA).