Internet of Things （IoT） applications such as environmental monitoring, healthcare, surveillance, event recognition and traffic con- trol are amongst the most commonly deployed applications over the Interact. These ...Internet of Things （IoT） applications such as environmental monitoring, healthcare, surveillance, event recognition and traffic con- trol are amongst the most commonly deployed applications over the Interact. These applications involve multimedia content that has to be collected, processed and delivered appropriately over the Interact for further processing by human or machines. These applications come with their own set of requirements such as quality, computational power and bandwidth. It is, therefore, vital to minimize power consumption and bandwidth usage in loT devices without compromising the quality of multimedia delivery. Since the delivery of the multimedia can be destined to a machine or human, it is important to distinguish multimedia quality between the two, Quality of Experience （QoE） for video services involves human visual system, but what will involve a machine or process？ To distinguish between the two, this paper defines a new concept of Acceptable Quality of Things （AQoT） which involves lot devices and their applications. AQoT aims at minimizing bandwidth without compromising quality in loT devices, Experimental re- suits based on human detection and license number plate detection use eases have demonstrated that the AQoT concept can sig- nificantly reduce bandwidth usage.展开更多
In this paper,we proposed a quality of transmission(QoT)prediction technique for the quality of service(QoS)link setup based on machine learning classifiers,with synthetic data generated using the transmission equatio...In this paper,we proposed a quality of transmission(QoT)prediction technique for the quality of service(QoS)link setup based on machine learning classifiers,with synthetic data generated using the transmission equations instead of the Gaussian noise(GN)model.The proposed technique uses some link and signal characteristics as input features.The bit error rate(BER)of the signals was compared with the forward error correction threshold BER,and the comparison results were employed as labels.The transmission equations approach is a better alternative to the GN model(or other similar margin-based models)in the absence of real data(i.e.,at the deployment stage of a network)or the case that real data are scarce(i.e.,for enriching the dataset/reducing probing lightpaths);furthermore,the three classifiers trained using the data of the transmission equations are more reliable and practical than those trained using the data of the GN model.Meanwhile,we noted that the priority of the three classifiers should be support vector machine(SVM)>K nearest neighbor(KNN)>logistic regression(LR)as shown in the results obtained by the transmission equations,instead of SVM>LR>KNN as in the results of the GN model.展开更多
In future optical transport networks,lightpath performance analysis is of great practical significance for fully automated management.In general,the quality of transmission(QoT)of lightpaths,measured by optical qualit...In future optical transport networks,lightpath performance analysis is of great practical significance for fully automated management.In general,the quality of transmission(QoT)of lightpaths,measured by optical quality factor or optical signal-to-noise ratio,has a complex time-varying process,along with the interactions of the other lightpath state parameters(LSPs),such as transmit power,chromatic dispersion,polarization mode dispersion.Current studies are mostly focused on lightpath QoT estimation,but ignoring lightpath-level data analytics.In this case,our article proposes a novel lightpath performance analysis method considering recurrence plot(RP)and cross recurrence plot(CRP).Firstly,we give a detailed interpretation on the recurrence patterns of LSPs via a qualitative 2-D RP representation and its quantitative measure.It can potentially enable the accurate and fast lightpath failure detection with a low computational burden.On the other hand,CRP is devoted to modeling the relationships between lightpath QoT and LSPs,and the correlation degree is determined by a geometric mean of multiple indexes of cross recurrence quantification analysis.From the view of application,such CRP analysis can provide the effective knowledge sharing to guarantee more credible QoT prediction.Extensive experiments on a real-world optical network dataset have clearly demonstrated the effectiveness of our proposal.展开更多
文摘Internet of Things （IoT） applications such as environmental monitoring, healthcare, surveillance, event recognition and traffic con- trol are amongst the most commonly deployed applications over the Interact. These applications involve multimedia content that has to be collected, processed and delivered appropriately over the Interact for further processing by human or machines. These applications come with their own set of requirements such as quality, computational power and bandwidth. It is, therefore, vital to minimize power consumption and bandwidth usage in loT devices without compromising the quality of multimedia delivery. Since the delivery of the multimedia can be destined to a machine or human, it is important to distinguish multimedia quality between the two, Quality of Experience （QoE） for video services involves human visual system, but what will involve a machine or process？ To distinguish between the two, this paper defines a new concept of Acceptable Quality of Things （AQoT） which involves lot devices and their applications. AQoT aims at minimizing bandwidth without compromising quality in loT devices, Experimental re- suits based on human detection and license number plate detection use eases have demonstrated that the AQoT concept can sig- nificantly reduce bandwidth usage.
文摘In this paper,we proposed a quality of transmission(QoT)prediction technique for the quality of service(QoS)link setup based on machine learning classifiers,with synthetic data generated using the transmission equations instead of the Gaussian noise(GN)model.The proposed technique uses some link and signal characteristics as input features.The bit error rate(BER)of the signals was compared with the forward error correction threshold BER,and the comparison results were employed as labels.The transmission equations approach is a better alternative to the GN model(or other similar margin-based models)in the absence of real data(i.e.,at the deployment stage of a network)or the case that real data are scarce(i.e.,for enriching the dataset/reducing probing lightpaths);furthermore,the three classifiers trained using the data of the transmission equations are more reliable and practical than those trained using the data of the GN model.Meanwhile,we noted that the priority of the three classifiers should be support vector machine(SVM)>K nearest neighbor(KNN)>logistic regression(LR)as shown in the results obtained by the transmission equations,instead of SVM>LR>KNN as in the results of the GN model.
基金supported in part by the Science and Technology Project of Hebei Education Department,Grant ZD2021088in part by the S&T Major Project of the Science and Technology Ministry of China,Grant 2017YFE0135700。
文摘In future optical transport networks,lightpath performance analysis is of great practical significance for fully automated management.In general,the quality of transmission(QoT)of lightpaths,measured by optical quality factor or optical signal-to-noise ratio,has a complex time-varying process,along with the interactions of the other lightpath state parameters(LSPs),such as transmit power,chromatic dispersion,polarization mode dispersion.Current studies are mostly focused on lightpath QoT estimation,but ignoring lightpath-level data analytics.In this case,our article proposes a novel lightpath performance analysis method considering recurrence plot(RP)and cross recurrence plot(CRP).Firstly,we give a detailed interpretation on the recurrence patterns of LSPs via a qualitative 2-D RP representation and its quantitative measure.It can potentially enable the accurate and fast lightpath failure detection with a low computational burden.On the other hand,CRP is devoted to modeling the relationships between lightpath QoT and LSPs,and the correlation degree is determined by a geometric mean of multiple indexes of cross recurrence quantification analysis.From the view of application,such CRP analysis can provide the effective knowledge sharing to guarantee more credible QoT prediction.Extensive experiments on a real-world optical network dataset have clearly demonstrated the effectiveness of our proposal.
