Sliding window non-parametric cumulative sum: a quick algorithm to detect selfish behaviour in wireless networks

When a node is not abiding by the rules of the protocol of a wireless network for its own benefit, it can cause severe degradation to network performance. Therefore it is important to detect such selfish behaviour. However, this is not an easy task. The main difficulty comes from the random operation of the carrier-sense multiple-access with collision avoidance (CSMA/CA) protocol, and is exacerbated by the nature of the wireless medium itself. The authors propose in this study a simple and quick algorithm, called sliding window non-parametric cumulative sum (SWN-CUSUM), to detect selfish nodes that deliberately modify its backoff window to gain unfair access to the network resources. SWN-CUSUM uses a sliding window to prevent unlimited build-up of the cumulating sum used in the protocol. The efficiency of this detection algorithm has been validated by extensive simulations using a Qualnet simulator. Comparative analysis of the proposed algorithm with a traditional CUSUM method demonstrates its superior performance with high detection accuracy and low false alarm rate. In addition, the authors compared SWN-CUSUM with other detection techniques, such as sequential probability ratio test and exponentially weighted moving average, the results show that our algorithm has a good performance in detection delay.