Browsing Engineering and Informatics by Author "Xu, L."
Analysis of the MAC protocol in low rate wireless personal area networks with bursty ON-OFF trafficGao, J.L.; Hu, J.; Min, Geyong; Xu, L. (2013)Supported by the IEEE 802.15.4 standard, embedded sensor networks have become popular and been widely deployed in recent years. The IEEE 802.15.4 medium access control (MAC) protocol is uniquely designed to meet the desirable requirements of the low end-to-end delay, low packet loss, and low power consumption in the low rate wireless personal areas networks (LR-WPANs). This paper develops an analytical model to quantify the key performance metrics of the MAC protocol in LR-WPANs with bursty ONOFF traffic. This study fills the gap in the literature by removing the assumptions of saturated traffic or nonbursty unsaturated traffic conditions, which are unable to capture the characteristics of bursty multimedia traffic in sensor networks. This analytical model can be used to derive the QoS performance metrics in terms of throughput and total delay. The accuracy of the model is verified through NS-2 (http://www.isi.edu/nsnam/ns/) simulation experiments. This model is adopted to investigate the performance of the MAC protocol in LR-WPANs under various traffic patterns, different loads, and various numbers of stations. Numerical results show that the traffic patterns and traffic burstiness have a significant impact on the delay performance of LR-WPANs.
Anomaly diagnosis based on regression and classification analysis of statistical traffic featuresLiu, Lei; Jin, X.L.; Min, Geyong; Xu, L. (2014-08-24)Traffic anomalies caused by Distributed Denial-of-Service (DDoS) attacks are major threats to both network service providers and legitimate customers. The DDoS attacks regularly consume and exhaust the resources of victims and hence result in abnormal bursty traffic through end-user systems. Additionally, malicious traffic aggregated into normal traffic often show dramatic changes in the traffic nature and statistical features. This study focuses on early detection of traffic anomalies caused by DDoS attacks in light of analyzing the network traffic behavior. Key statistical features including variance, autocorrelation, and self-similarity are employed to characterize the network traffic. Further, artificial neural network and support vector machine subject to the performance metrics are employed to predict and classify the abnormal traffic. The proposed diagnosis mechanism is validated through experiments where the datasets consist of two groups. The first group is the Massachusetts Institute of Technology Lincoln Laboratory dataset containing labeled DoS attack. The second group collected from DDoS attack simulation experiments covers three representative traffic shapes resulting from the dynamic attack rate configuration, namely, constant intensity, ramp-up behavior, and pulsing behavior. The experimental results demonstrate that the developed mechanism can effectively and precisely alert the abnormal traffic within short response period.
Congestion control based on cross-layer game optimization in wireless mesh networksMa, X.; Xu, L.; Min, Geyong (2013)Due to the attractive characteristics of high capacity, high-speed, wide coverage and low transmission power, Wireless Mesh Networks become the ideal choice for the next-generation wireless communication systems. However, the network congestion of WMNs deteriorates the quality of service provided to end users. Game theory optimization model is a novel modeling tool for the study of multiple entities and the interaction between them. On the other hand, cross-layer design is shown to be practical for optimizing the performance of network communications. Therefore, a combination of the game theory and cross-layer optimization, named cross-layer game optimization, is proposed to reduce network congestion in WMNs. In this paper, the network congestion control in the transport layer and multi-path flow assignment in the network layer of WMNs are investigated. The proposed cross-layer game optimization algorithm is then employed to enable source nodes to change their set of paths and adjust their congestion window according to the round-trip time to achieve a Nash equilibrium. Finally, evaluation results show that the proposed cross-layer game optimization scheme achieves high throughput with low transmission delay.