Influence of Topology-Fluctuations on Self-Stabilizing Algorithms

Self-stabilizing systems have in theory the unique and provable ability, to always return to a valid system state even in the face of failures. These properties are certainly desirable for domains like wireless ad-hoc networks with numerous unpredictable faults. Unfortunately, the time in which the system returns to a valid state is not predictable and potentially unbound. The failure rate typically depends on physical phenomena and in self-stabilizing systems each node tries to react to failures in an inherently adaptive fashion by the cyclic observation of the states of its neighbors. When state changes are either too quick or too slow the system might never reach a state that is sufficiently stable for a specific task. In this paper, we investigate the influences of the error rate on the (stability) convergence time on the basis of topology information acquired in real network experiments. This allows us to asses the asymptotic behavior of relevant self-stabilizing algorithms in typical wireless networks.