Cognitive radio is an exciting emerging technology that has the potential of dealing with the urgent requirement and scarcity of the radio spectrum. Although having multiple radio interfaces and available spectrum ban...Cognitive radio is an exciting emerging technology that has the potential of dealing with the urgent requirement and scarcity of the radio spectrum. Although having multiple radio interfaces and available spectrum bands can generally increase the effective throughput, a problem arises as to what the best strategy to dynamically assign available bands to secondary users for maximizing throughput by minimizing the interference, and what the best scheme to allocate the spectrum holes to unlicensed users to maximize the fairness. This paper presents a distributed and heuristic spectrum assignment algorithm for multi-radio wireless cognitive networks in a cognitive network environment. The proposed algorithm (Fairness Bargaining with Maximum throughput, FBMT) considers the problems including system throughput and the fairness. Extensive simulation studies in 802.11 based multi-radio cognitive networks have been performed. The results indicate that the proposed algorithm can facilitate a large increase in network throughput and acquire a good fairness performance in comparison with a common spectrum assignment mechanism that is used as a benchmark in the literature.展开更多
Trust management frameworks are used to evaluate and manage trust relationships between network nodes and enhance network security. However, trust management frameworks themselves are vulnerable to attacks. Attacks ag...Trust management frameworks are used to evaluate and manage trust relationships between network nodes and enhance network security. However, trust management frameworks themselves are vulnerable to attacks. Attacks against trust management frameworks are described in this paper with a trust management framework to resist them. The trustworthiness between nodes is evaluated to classify node behavior using a three-dimensional classifier based on a fuzzy integral. Different behaviors are mapped to different behavioral spaces to detect malicious nodes and identify their behavior types. The security of ad hoc networks is then improved by various measures to handle different types of malicious behavior. Simula- tions of the model on the System In The Loop （SITL） platform show that this trust management framework can separate normal nodes and malicious nodes and can distinguish different types of malicious nodes.展开更多
文摘Cognitive radio is an exciting emerging technology that has the potential of dealing with the urgent requirement and scarcity of the radio spectrum. Although having multiple radio interfaces and available spectrum bands can generally increase the effective throughput, a problem arises as to what the best strategy to dynamically assign available bands to secondary users for maximizing throughput by minimizing the interference, and what the best scheme to allocate the spectrum holes to unlicensed users to maximize the fairness. This paper presents a distributed and heuristic spectrum assignment algorithm for multi-radio wireless cognitive networks in a cognitive network environment. The proposed algorithm (Fairness Bargaining with Maximum throughput, FBMT) considers the problems including system throughput and the fairness. Extensive simulation studies in 802.11 based multi-radio cognitive networks have been performed. The results indicate that the proposed algorithm can facilitate a large increase in network throughput and acquire a good fairness performance in comparison with a common spectrum assignment mechanism that is used as a benchmark in the literature.
基金Supported by the National Natural Science Foundation of China (No.60972016)
文摘Trust management frameworks are used to evaluate and manage trust relationships between network nodes and enhance network security. However, trust management frameworks themselves are vulnerable to attacks. Attacks against trust management frameworks are described in this paper with a trust management framework to resist them. The trustworthiness between nodes is evaluated to classify node behavior using a three-dimensional classifier based on a fuzzy integral. Different behaviors are mapped to different behavioral spaces to detect malicious nodes and identify their behavior types. The security of ad hoc networks is then improved by various measures to handle different types of malicious behavior. Simula- tions of the model on the System In The Loop （SITL） platform show that this trust management framework can separate normal nodes and malicious nodes and can distinguish different types of malicious nodes.
