In modern wireless communication network, the increased consumer demands for multi-type applications and high quality services have become a prominent trend, and put considerable pressure on the wireless network. In t...In modern wireless communication network, the increased consumer demands for multi-type applications and high quality services have become a prominent trend, and put considerable pressure on the wireless network. In that case, the Quality of Experience(Qo E) has received much attention and has become a key performance measurement for the application and service. In order to meet the users' expectations, the management of the resource is crucial in wireless network, especially the Qo E based resource allocation. One of the effective way for resource allocation management is accurate application identification. In this paper, we propose a novel deep learning based method for application identification. We first analyse the requirement of managing Qo E for wireless communication, and review the limitation of the traditional identification methods. After that, a deep learning based method is proposed for automatically extracting the features and identifying the type of application. The proposed method is evaluated by using the practical wireless traffic data, and the experiments verify the effectiveness of our method.展开更多
With the increasing popularity of cloud computing, there is an increased de mand for cloud resources in cloud. It has be come even more urgent to find solutions to improve resource utilization. From the per spective o...With the increasing popularity of cloud computing, there is an increased de mand for cloud resources in cloud. It has be come even more urgent to find solutions to improve resource utilization. From the per spective of a cloud consumer, a cloud applica tion processes a large information flow in volving user actions that access resources, but little work has so far been devoted to research from the perspective of the interaction be tween the user and the cloud application. In this paper, we analyze the interaction in detail, and propose a general mathematical interac tion model to formulate the challenge pertain ing to storage resource allocation as an opti mization problem, focusing on minimizing both the user＇s cost and server＇s consumption. A potential response mechanism is then de signed based on the interaction model. Fur thermore, the proposed model is used to ex plore strategies when multiple users access the same file simultaneously. Additionally, an improved queuing system, namely M/ G~ oo queue with standby, is introduced. Finally, an evaluation is presented to verify the interac- tion model.展开更多
The pursuit of high data rate and assurance of quality of experience(QoE) for end users represent the main goals of future wireless communication systems.By introducing MOS(Mean Opinion Score) based assessment models ...The pursuit of high data rate and assurance of quality of experience(QoE) for end users represent the main goals of future wireless communication systems.By introducing MOS(Mean Opinion Score) based assessment models for different types of applications,this paper proposed novel QoE-oriented radio resource allocation(RRA) algorithms for multiuser-multiservice femtocell networks.An optimal QoE-oriented RRA strategy is first analyzed using time-sharing method which is applicable to best effort applications.RRA algorithms based on the cross-layer architecture are then proposed for all types of applications by considering parameters extracted from different layers of networking protocols.In the proposed algorithms,a priority mechanism is employed to ensure fairness.Simulation results show that the proposed algorithms can significantly improve the overall perceived quality from the users' perspective in comparison with traditional Quality of Service(QoS)oriented algorithms.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
Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confli...Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confliction. In the intra-cluster part, the random color selection method is effective in reducing the retry times in an application. In the inter-cluster part, a quick assign algorithm and a dynamic maximum link algorithm are proposed to meet the quick networking or minimum frame size requirements. In the simulation, the dynamic maximum link algorithm produces higher reductions in the frame length than the quick assign algorithm. When the number of routers is 140, the total number of time slots is reduced by 25%. However, the first algorithm needs more control messages, and the average difference in the number of control messages is 3 410. Consequently, the dynamic maximum link algorithm is utilized for adjusting the link schedule to the minimum delay with a relatively high throughput rate, and the quick assign algorithm is utilized for speeding up the networking process.展开更多
基金supported by NSAF under Grant(No.U1530117)National Natural Science Foundation of China(No.61471022 and No.61201156)
文摘In modern wireless communication network, the increased consumer demands for multi-type applications and high quality services have become a prominent trend, and put considerable pressure on the wireless network. In that case, the Quality of Experience(Qo E) has received much attention and has become a key performance measurement for the application and service. In order to meet the users' expectations, the management of the resource is crucial in wireless network, especially the Qo E based resource allocation. One of the effective way for resource allocation management is accurate application identification. In this paper, we propose a novel deep learning based method for application identification. We first analyse the requirement of managing Qo E for wireless communication, and review the limitation of the traditional identification methods. After that, a deep learning based method is proposed for automatically extracting the features and identifying the type of application. The proposed method is evaluated by using the practical wireless traffic data, and the experiments verify the effectiveness of our method.
基金supported in part by the National Natural Science Foundation of China under Grant No. 61271199the Fundamental Research Funds in Beijing Jiaotong University under Grant No. W11JB00630
文摘With the increasing popularity of cloud computing, there is an increased de mand for cloud resources in cloud. It has be come even more urgent to find solutions to improve resource utilization. From the per spective of a cloud consumer, a cloud applica tion processes a large information flow in volving user actions that access resources, but little work has so far been devoted to research from the perspective of the interaction be tween the user and the cloud application. In this paper, we analyze the interaction in detail, and propose a general mathematical interac tion model to formulate the challenge pertain ing to storage resource allocation as an opti mization problem, focusing on minimizing both the user＇s cost and server＇s consumption. A potential response mechanism is then de signed based on the interaction model. Fur thermore, the proposed model is used to ex plore strategies when multiple users access the same file simultaneously. Additionally, an improved queuing system, namely M/ G~ oo queue with standby, is introduced. Finally, an evaluation is presented to verify the interac- tion model.
基金supported in part by the National Nature Science Foundation of China under Grant 61372117the 863 project under grant No.2014AA01A701the National Key Technology Support Program under grant No.2012BAH41F03
文摘The pursuit of high data rate and assurance of quality of experience(QoE) for end users represent the main goals of future wireless communication systems.By introducing MOS(Mean Opinion Score) based assessment models for different types of applications,this paper proposed novel QoE-oriented radio resource allocation(RRA) algorithms for multiuser-multiservice femtocell networks.An optimal QoE-oriented RRA strategy is first analyzed using time-sharing method which is applicable to best effort applications.RRA algorithms based on the cross-layer architecture are then proposed for all types of applications by considering parameters extracted from different layers of networking protocols.In the proposed algorithms,a priority mechanism is employed to ensure fairness.Simulation results show that the proposed algorithms can significantly improve the overall perceived quality from the users' perspective in comparison with traditional Quality of Service(QoS)oriented algorithms.
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 by Beijing Education and Scientific Research Programthe National High Technical Research and Development Program of China (863 Program) under Grant No. 2011AA040101+2 种基金the National Natural Science Foundation of China under Grants No. 61173150, No. 61003251Beijing Science and Technology Program under Grant No. Z111100054011078the State Scholarship Fund
文摘Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confliction. In the intra-cluster part, the random color selection method is effective in reducing the retry times in an application. In the inter-cluster part, a quick assign algorithm and a dynamic maximum link algorithm are proposed to meet the quick networking or minimum frame size requirements. In the simulation, the dynamic maximum link algorithm produces higher reductions in the frame length than the quick assign algorithm. When the number of routers is 140, the total number of time slots is reduced by 25%. However, the first algorithm needs more control messages, and the average difference in the number of control messages is 3 410. Consequently, the dynamic maximum link algorithm is utilized for adjusting the link schedule to the minimum delay with a relatively high throughput rate, and the quick assign algorithm is utilized for speeding up the networking process.
