The concurrent presence of different types of traffic in multimedia applications might aggravate a burden on the underlying data network, which is bound to affect the transmission quality of the specified traffic. Rec...The concurrent presence of different types of traffic in multimedia applications might aggravate a burden on the underlying data network, which is bound to affect the transmission quality of the specified traffic. Recently, several proposals for fulfilling the quality of service(QoS) guarantees have been presented. However, they can only support coarse-grained QoS with no guarantee of throughput, jitter, delay or loss rate for different applications. To address these more challenging problems, an adaptive scheduling algorithm for Parallel data Processing with Multiple Feedback(PPMF) queues based on software defined networks(SDN) is proposed in this paper, which can guarantee the quality of service of high priority traffic in multimedia applications. PPMF combines the queue bandwidth feedback mechanism to realise the automatic adjustment of the queue bandwidth according to the priority of the packet and network conditions, which can effectively solve the problem of network congestion that has been experienced by some queues for a long time. Experimental results show PPMF significantly outperforms other existing scheduling approaches in achieving 35--80% improvement on average time delay by adjusting the bandwidth adaptively, thus ensuring the transmission quality of the specified traffic and avoiding effectively network congestion.展开更多
In this paper,we study cross-layer scheduling scheme on multimedia application which considers both streaming traffic and data traffic over cognitive ad hoc networks.A cross-layer design is proposed to optimize SU'...In this paper,we study cross-layer scheduling scheme on multimedia application which considers both streaming traffic and data traffic over cognitive ad hoc networks.A cross-layer design is proposed to optimize SU's utility,which is used as an approach to balance the transmission efficiency and heterogeneous traffic in cognitive ad hoc networks.A framework is provided for utility-based optimal subcarrier assignment,power allocation strategy and corresponding modulation scheme,subject to the interference threshold to primary user(PU) and total transmit power constraint.Bayesian learning is adopted in subcarrier allocation strategy to avoid collision and alleviate the burden of information exchange on limited common control channel(CCC).In addition,the M/G/l queuing model is also introduced to analyze the expected delay of streaming traffic.Numerical results are given to demonstrate that the proposed scheme significantly reduces the blocking probability and outperforms the mentioned single-channel dynamic resource scheduling by almost 8%in term of system utility.展开更多
To improve the quality of multimedia services and stimulate secure sensing in Internet of Things applications, such as healthcare and traffic monitoring, mobile crowdsensing(MCS) systems must address security threats ...To improve the quality of multimedia services and stimulate secure sensing in Internet of Things applications, such as healthcare and traffic monitoring, mobile crowdsensing(MCS) systems must address security threats such as jamming, spoofing and faked sensing attacks during both sensing and information exchange processes in large-scale dynamic and heterogeneous networks. In this article, we investigate secure mobile crowdsensing and present ways to use deep learning(DL) methods, such as stacked autoencoder, deep neural networks, convolutional neural networks, and deep reinforcement learning, to improve approaches to MCS security, including authentication, privacy protection, faked sensing countermeasures, intrusion detection and anti-jamming transmissions in MCS. We discuss the performance gain of these DLbased approaches compared to traditional security schemes and identify the challenges that must be addressed to implement these approaches in practical MCS systems.展开更多
基金supported by National Key Basic Research Program of China(973 Program)under grant no.2012CB315802National Natural Science Foundation of China under grant no.61671081 and no.61132001Prospective Research on Future Networks of Jiangsu Future Networks Innovation Institute under grant no.BY2013095-4-01
文摘The concurrent presence of different types of traffic in multimedia applications might aggravate a burden on the underlying data network, which is bound to affect the transmission quality of the specified traffic. Recently, several proposals for fulfilling the quality of service(QoS) guarantees have been presented. However, they can only support coarse-grained QoS with no guarantee of throughput, jitter, delay or loss rate for different applications. To address these more challenging problems, an adaptive scheduling algorithm for Parallel data Processing with Multiple Feedback(PPMF) queues based on software defined networks(SDN) is proposed in this paper, which can guarantee the quality of service of high priority traffic in multimedia applications. PPMF combines the queue bandwidth feedback mechanism to realise the automatic adjustment of the queue bandwidth according to the priority of the packet and network conditions, which can effectively solve the problem of network congestion that has been experienced by some queues for a long time. Experimental results show PPMF significantly outperforms other existing scheduling approaches in achieving 35--80% improvement on average time delay by adjusting the bandwidth adaptively, thus ensuring the transmission quality of the specified traffic and avoiding effectively network congestion.
基金This work was supported by the National Natural Science Foundations of China （Grant No. 61201143）, the Fundamental Research Fund for the Central Universities （Grant No. HIT. NSRIF. 2010091）, the National Science Foundation for Post-doctoral Scientists of China （Grant No. 2012M510956）, and the Post-doc- toral Fund of Heilongjiang Province （GrantNo. LBHZ11128）.
文摘In this paper,we study cross-layer scheduling scheme on multimedia application which considers both streaming traffic and data traffic over cognitive ad hoc networks.A cross-layer design is proposed to optimize SU's utility,which is used as an approach to balance the transmission efficiency and heterogeneous traffic in cognitive ad hoc networks.A framework is provided for utility-based optimal subcarrier assignment,power allocation strategy and corresponding modulation scheme,subject to the interference threshold to primary user(PU) and total transmit power constraint.Bayesian learning is adopted in subcarrier allocation strategy to avoid collision and alleviate the burden of information exchange on limited common control channel(CCC).In addition,the M/G/l queuing model is also introduced to analyze the expected delay of streaming traffic.Numerical results are given to demonstrate that the proposed scheme significantly reduces the blocking probability and outperforms the mentioned single-channel dynamic resource scheduling by almost 8%in term of system utility.
基金supported in part by the National Natural Science Foundation of China under Grant 61671396 and 91638204in part by the open research fund of National Mobile Communications Research Laboratory,Southeast University(No.2018D08)in part by Science and Technology Innovation Project of Foshan City,China(Grant No.2015IT100095)
文摘To improve the quality of multimedia services and stimulate secure sensing in Internet of Things applications, such as healthcare and traffic monitoring, mobile crowdsensing(MCS) systems must address security threats such as jamming, spoofing and faked sensing attacks during both sensing and information exchange processes in large-scale dynamic and heterogeneous networks. In this article, we investigate secure mobile crowdsensing and present ways to use deep learning(DL) methods, such as stacked autoencoder, deep neural networks, convolutional neural networks, and deep reinforcement learning, to improve approaches to MCS security, including authentication, privacy protection, faked sensing countermeasures, intrusion detection and anti-jamming transmissions in MCS. We discuss the performance gain of these DLbased approaches compared to traditional security schemes and identify the challenges that must be addressed to implement these approaches in practical MCS systems.
