Dynamic Artificial-Immune-System Models of Default Detection for Sensing Networks

Models analyzing a signaling mechanism in Artificial Immune System (AIS) could be expanded with advance of sensing networks. In principle, if a sensing network has enough nodes linked to propagate signals, it could be viewed as a continuous field, and be analyzed by field analysis methodology, meanwhile, it could be analyzed by random and probability methodology for that its nodes are also discrete. The two kinds of methodology should be applied to describe key characteristics of AIS, which is self-adaptation taking the forms of stability, immunity, and repellency. The paper proposes some models of the two kinds of methodology.