Adaptation of Reputation Management Systems to Dynamic Network Conditions in Ad Hoc Networks

Reputation management systems have been proposed as a cooperation enforcement solution in ad hoc networks. Typically, the functions of reputation management (evaluation, detection, and reaction) are carried out homogeneously across time and space. However, the dynamic nature of ad hoc networks causes node behavior to vary both spatially and temporally due to changes in local and network-wide conditions. When reputation management functions do not adapt to such changes, their effectiveness, measured in terms of accuracy (correct identification of node behavior) and promptness (timely identification of node misbehavior), may be compromised. We propose an adaptive reputation management system that realizes that changes in node behavior may be driven by changes in network conditions and that accommodates such changes by adapting its operating parameters. We introduce a time-slotted approach to allow the evaluation function to quickly and accurately capture changes in node behavior. We show how the duration of an evaluation slot can adapt according to the network´s activity to enhance the system accuracy and promptness. We then show how the detection function can utilize a Sequential Probability Ratio Test (SPRT) to distinguish between cooperative and misbehaving neighbors. The SPRT adapts to changes in neighbors´ behavior that are a by-product of changing network conditions, by using the node´s own behavior as a benchmark. We compare our proposed solution to a nonadaptive system, showing the ability of our system to achieve high accuracy and promptness in dynamic environments. To the best of our knowledge, this is the first work to explore the adaptation of the reputation management functions to changes in network conditions.