MAC layer misbehavior effectiveness and collective aggressive reaction approach

Current wireless MAC protocols are designed to provide an equal share of throughput to all nodes in the network. However, the presence of misbehaving nodes (selfish nodes which deviate from standard protocol behavior in order to get higher bandwidth) poses severe threats to the fairness aspects of MAC protocols. In this paper, we investigate various types of MAC layer misbehaviors, and evaluate their effectiveness in terms of their impact on important performance aspects including throughput, and fairness to other users. We observe that the effects of misbehavior are prominent only when the network traffic is sufficiently large and the extent of misbehavior is reasonably aggressive. In addition, we find that performance gains achieved using misbehavior exhibit diminishing returns with respect to its aggressiveness, for all types of misbehaviors considered. We identify crucial common characteristics among such misbehaviors, and employ our learning to design an effective measure to react towards such misbehaviors. Employing two of the most effective misbehaviors, we study the effect of collective aggressiveness of non-selfish nodes as a possible strategy to react towards selfish misbehavior. Particularly, we demonstrate that a collective aggressive reaction approach is able to ensure fairness in the network, however at the expense of overall network throughput degradation.