The erratic behavior of wireless channels is still a major hurdle in the implementation of robust applications in wireless networks. In the past it has been argued that self-stabilization is a remedy to provide the needed robustness. This assumption has not been verified to the extent necessary to convince engineers implementing such applications. A major reason is that the time in which a self-stabilizing system returns to a valid state is unpredictable and potentially unbound. Failure rates typically depend 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 its neighbors' states. When the frequency of state changes is too high, the system may never reach a state sufficiently stable for a specific task. In this paper we substantiate the conditions under which self-stabilization leads to fault tolerance in wireless networks and look at the myths about the power of self-stabilization as a particular instance of self-organization. We investigate the influences of the error rate and the neighbor state exchange rate on the stability and the convergence time on topology information acquired in real network experiments.
['Stefan Lohs', 'Jörg Nolte', 'Gerry Siegemund', 'Volker Turau']
Self-Stabilization - A Mechanism to Make Networked Embedded Systems More Reliable?