A multicast routing algorithm of multiple QoS constraints based on widest-bandwidth （MRQW） which takes available bandwidth as the prime metric, considering the constraints of the surplus energy of the node, delay an...A multicast routing algorithm of multiple QoS constraints based on widest-bandwidth （MRQW） which takes available bandwidth as the prime metric, considering the constraints of the surplus energy of the node, delay and delay jitter, is presented. The process of routing based on MRQW is provided for as well. Correctness proof and the complexity analysis of the MRQW are also given in the paper. Simulation results show that the MRQW has a good performance in creating multicast trees. It not only satisfys multiple QoS constraints but also makes multicast links have larger available bandwidth展开更多
In order to solve the problems of small sample over-fitting and local minima when neural networks learn online, a novel method of predicting network bandwidth based on support vector machines(SVM) is proposed. The pre...In order to solve the problems of small sample over-fitting and local minima when neural networks learn online, a novel method of predicting network bandwidth based on support vector machines(SVM) is proposed. The prediction and learning online will be completed by the proposed moving window learning algorithm(MWLA). The simulation research is done to validate the proposed method, which is compared with the method based on neural networks.展开更多
Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabi...Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.展开更多
The growing popularity of Internet applications and services has rendered high subjective video quality crucial to the user experience. Increasing needs for better video resolution and faster transmission bandwidths p...The growing popularity of Internet applications and services has rendered high subjective video quality crucial to the user experience. Increasing needs for better video resolution and faster transmission bandwidths present challenges to the goal of achieving balance between video quality and coding cost. In this paper, we propose a Perceptive Variable Bit-Rate Control （PVBRC） framework for the state-of-the-art video coding standard High-Efficiency Video Coding （HEVC）/H.265. PVBRC allocates a bit-rate to a picture while taking a Comprehensive Picture Quality Assessment （CPQA） model and perceptive target bit-rate allocation into consideration. The CPQA model calculates the objective and perceptive quality of both source and reconstructed pictures by referring to the human vision system. The coding bit-rate is then dynamically allocated by the result of the CPQA model according to differences in picture content. In PVBRC, the quantization parameter for current picture encoding is updated by an effective fuzzy logical controller to satisfy the transmission requirements of the Internet of Things. Experimental results show that the proposed PVBRC can achieve average bit savings by 11.49% when compared with constant bit-rate control under the same objective and subjective video quality.展开更多
In communication networks （CNs）, the uncertainty is caused by the dynamic nature of the traffic demands. Therefore there is a need to incorporate the uncertainty into the network bandwidth capacity design. For this ...In communication networks （CNs）, the uncertainty is caused by the dynamic nature of the traffic demands. Therefore there is a need to incorporate the uncertainty into the network bandwidth capacity design. For this purpose, this paper developed a fuzzy methodology for network bandwidth design under demand uncertainty. This methodology is usually used for offiine traffic engineering optimization, which takes a centralized view of bandwidth design, resource utilization, and performance evaluation. In this proposed methodology, uncertain traffic demands are first handled into a fuzzy number via a fuzzification method. Then a fuzzy optimization model for the network bandwidth allocation problem is formulated with the consideration of the trade-off between resource utilization and network performance. Accordingly, the optimal network bandwidth capacity can be obtained by maximizing network revenue in CNs. Finally, an illustrative numerical example is presented for the purpose of verification.展开更多
The granularity of the flexible bandwidth optical network is the spectral slots, which is much smaller than that of the wavelength switch optical network. For the dynamic clients＇ connections setup and tear down proc...The granularity of the flexible bandwidth optical network is the spectral slots, which is much smaller than that of the wavelength switch optical network. For the dynamic clients＇ connections setup and tear down processes, it will give rise to fragmentation of spectral resources. It is the decline in the probability of finding sufficient contiguous spectrum for new connections that result in the fragmentation of spectral resource. To be more specific, these spectra may be unavailable and waste. In this case, the severe waste of the spectrum will lead to low efficiency in spectral utilization and will not adapt to large capacity requirements of transmission in the future. Because path computation element （PCE） framework has the characteristics of the central disposal and deployment of the spectrum resource, we construct the spectral resource allocation scenario based on PCE framework in the flexible bandwidth optical network to use spectrum resource effectively Based on the principle of the generation of the fragmentation, we put forward a spectrum resource defragmentation algorithm to consolidate the available spectrum for clients＇ connections. The simulation results indicate that this algorithm is able to reduce fragmentation of network, improve the continuity of spectral resource, reduce the blocking rate of services in the network and improve the spectral efficiency significantly.展开更多
基金This project was supported by the National Natural Science Foundation of China (90304018)and the Natural ScienceFoundation of Hubei Province of China (2004ABA023)
文摘A multicast routing algorithm of multiple QoS constraints based on widest-bandwidth （MRQW） which takes available bandwidth as the prime metric, considering the constraints of the surplus energy of the node, delay and delay jitter, is presented. The process of routing based on MRQW is provided for as well. Correctness proof and the complexity analysis of the MRQW are also given in the paper. Simulation results show that the MRQW has a good performance in creating multicast trees. It not only satisfys multiple QoS constraints but also makes multicast links have larger available bandwidth
文摘In order to solve the problems of small sample over-fitting and local minima when neural networks learn online, a novel method of predicting network bandwidth based on support vector machines(SVM) is proposed. The prediction and learning online will be completed by the proposed moving window learning algorithm(MWLA). The simulation research is done to validate the proposed method, which is compared with the method based on neural networks.
文摘Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.
基金supported by Foundation of Science and Technology Department of Sichuan Province (Nos. 2017JY0007 and 2017HH0075)
文摘The growing popularity of Internet applications and services has rendered high subjective video quality crucial to the user experience. Increasing needs for better video resolution and faster transmission bandwidths present challenges to the goal of achieving balance between video quality and coding cost. In this paper, we propose a Perceptive Variable Bit-Rate Control （PVBRC） framework for the state-of-the-art video coding standard High-Efficiency Video Coding （HEVC）/H.265. PVBRC allocates a bit-rate to a picture while taking a Comprehensive Picture Quality Assessment （CPQA） model and perceptive target bit-rate allocation into consideration. The CPQA model calculates the objective and perceptive quality of both source and reconstructed pictures by referring to the human vision system. The coding bit-rate is then dynamically allocated by the result of the CPQA model according to differences in picture content. In PVBRC, the quantization parameter for current picture encoding is updated by an effective fuzzy logical controller to satisfy the transmission requirements of the Internet of Things. Experimental results show that the proposed PVBRC can achieve average bit savings by 11.49% when compared with constant bit-rate control under the same objective and subjective video quality.
基金partially supported by the grants from the National Natural Science Foundation of Chinathe Knowledge Innovation Program of the Chinese Academy of Sciences+1 种基金the GRANT-IN-AID FOR SCIEN-TIFIC RESEARCH (No. 19500070)MEXT.ORC (2004-2008), Japan
文摘In communication networks （CNs）, the uncertainty is caused by the dynamic nature of the traffic demands. Therefore there is a need to incorporate the uncertainty into the network bandwidth capacity design. For this purpose, this paper developed a fuzzy methodology for network bandwidth design under demand uncertainty. This methodology is usually used for offiine traffic engineering optimization, which takes a centralized view of bandwidth design, resource utilization, and performance evaluation. In this proposed methodology, uncertain traffic demands are first handled into a fuzzy number via a fuzzification method. Then a fuzzy optimization model for the network bandwidth allocation problem is formulated with the consideration of the trade-off between resource utilization and network performance. Accordingly, the optimal network bandwidth capacity can be obtained by maximizing network revenue in CNs. Finally, an illustrative numerical example is presented for the purpose of verification.
基金supported by the National Bascic Research Program of China(2010CB328204)the National Natural Science Foundation of China(60932004)+2 种基金the Hi-Tech Research and Development Program of China(2009AA01Z255)RFDP Project(20090005110013)the Fundamental Research Funds for the Central Universities(2011RC0406)
文摘The granularity of the flexible bandwidth optical network is the spectral slots, which is much smaller than that of the wavelength switch optical network. For the dynamic clients＇ connections setup and tear down processes, it will give rise to fragmentation of spectral resources. It is the decline in the probability of finding sufficient contiguous spectrum for new connections that result in the fragmentation of spectral resource. To be more specific, these spectra may be unavailable and waste. In this case, the severe waste of the spectrum will lead to low efficiency in spectral utilization and will not adapt to large capacity requirements of transmission in the future. Because path computation element （PCE） framework has the characteristics of the central disposal and deployment of the spectrum resource, we construct the spectral resource allocation scenario based on PCE framework in the flexible bandwidth optical network to use spectrum resource effectively Based on the principle of the generation of the fragmentation, we put forward a spectrum resource defragmentation algorithm to consolidate the available spectrum for clients＇ connections. The simulation results indicate that this algorithm is able to reduce fragmentation of network, improve the continuity of spectral resource, reduce the blocking rate of services in the network and improve the spectral efficiency significantly.
