Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable si...Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.展开更多
To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SO...To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SON). In this paper, a novel CCO scheme is proposed to maximize utility function of the integrated coverage and capacity. It starts with the analysis on the throughput proportional fairness(PF) algorithm and then proposes the novel Coverage and Capacity Proportional Fairness(CCPF) allocation algorithm along with a proof of the algorithms convergence. This proposed algorithm is applied in a coverage capacity optimization scheme which can guarantee the reasonable network capacity by the coverage range accommodation. Next, we simulate the proposed CCO scheme based on telecom operators' real network data and compare with three typical resource allocation algorithms: round robin(RR), proportional fairness(PF) and max C/I. In comparison of the PF algorithm, the numerical results show that our algorithm increases the average throughput by 1.54 and 1.96 times with constructed theoretical data and derived real network data respectively.展开更多
To fulfill the explosive growth of network capacity, fifth generation(5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio acc...To fulfill the explosive growth of network capacity, fifth generation(5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio access network(H-CRAN), as a promising network paradigm in 5G system, is a hot research topic in recent years. However, the densely deployment of RRHs in H-CRAN leads to downlink/uplink traffic asymmetry and severe inter-cell interference which could seriously impair the network throughput and resource utilization. To simultaneously solve these two problems, we proposed a dynamic resource allocation(DRA) scheme for H-CRAN in TDD mode. Firstly, we design a clustering algorithm to group the RRHs into different sets. Secondly, we adopt coordinated multipoint technology to eliminate the interference in each set. Finally, we formulate the joint frame structure, power and subcarrier selection problem as a mixed strategy noncooperative game. The simulation results are presented to validate the effectiveness of our proposed algorithm by compared with the existing work.展开更多
To meet the increasing demand of wireless broadband applications in future 5G cellular networks, Device-to-Device(D2D) communications serve as a candidate paradigm to improve spectrum efficiency. Considering the chall...To meet the increasing demand of wireless broadband applications in future 5G cellular networks, Device-to-Device(D2D) communications serve as a candidate paradigm to improve spectrum efficiency. Considering the challenges after D2 D transmission is introduced for future cellular networks, this paper deals with mode selection and resource allocation issues related with D2 D communications. First, we propose a mode selection scheme which aims at guaranteeing the transmission of cellular users and also considering the potential interference. We analyze the condition under which D2 D underlay mode should be used. Second, we answer the question of "how to effectively reuse cellular resource once underlaying mode is adopted". We further present a resource allocation scheme that focuses on minimizing overall interference as well as a power control method to improve the performance of D2 D systems. Simulation results demonstrate that system parameters greatly affect the switching condition of mode selection and probability of choosing underlay mode. Furthermore, for D2 D underlaying scenario, the proposed resource allocation algorithm guarantees the transmission of cellular users with consideration of transmission requirements of D2 D users. Hence, the proposed scheme can achieve better user experience.展开更多
Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the ph...Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.展开更多
Resource scheduling algorithm for ForCES(Forwarding and Control Element Separation) networks need to meet the flexibility,programmability and scalability of node resources.DBC(Deadline Budget Constrain) algorithm reli...Resource scheduling algorithm for ForCES(Forwarding and Control Element Separation) networks need to meet the flexibility,programmability and scalability of node resources.DBC(Deadline Budget Constrain) algorithm relies on users select cost or time priority,then scheduling to meet the requirements of users.However,this priority strategy of users is relatively simple,and cannot adapt to dynamic change of resources,it is inevitable to reduce the QoS.In order to improve QoS,we refer to the economic model and resource scheduling model of cloud computing,use SAL(Service Level Agreement) as pricing strategy,on the basis of DBC algorithm,propose an DABP(Deadline And Budget Priority based on DBC) algorithm for ForCES networks,DABP combines both budget and time priority to scheduling.In simulation and test,we compare the task finish time and cost of DABP algorithm with DP(Deadline Priority) algorithm and BP(Budget Priority) algorithm,the analysis results show that DABP algorithm make the task complete with less cost within deadline,benifical to load balancing of ForCES networks.展开更多
Scalable video coding(SVC) is a powerful tool to solve the network heterogeneity and terminal diversity in video applications. However, in related works about the optimization of SVC-based video streaming over Softwar...Scalable video coding(SVC) is a powerful tool to solve the network heterogeneity and terminal diversity in video applications. However, in related works about the optimization of SVC-based video streaming over Software Defined Network(SDN), most of the them are focused either on the number of transmission layers or on the optimization of transmission path for specific layer. In this paper, we propose a noval optimization algorithm for SVC to dynamically adjust the number of layers and optimize the transmission paths simultaneously. We establish the problem model based on the 0/1 knapsack model, and then solve it with Artificial Fish Swarm Algorithm. Additionally, the simulations are carried out on the Mininet platform, which show that our approach can dynamically adjust the number of layers and select the optimal paths at the same time. As a result, it can achieve an effective allocation of network resources which mitigates the congestion and reduces the loss of non-SVC stream.展开更多
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
The tremendous performance gain of heterogeneous networks(Het Nets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for Het Nets becomes much more challengi...The tremendous performance gain of heterogeneous networks(Het Nets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for Het Nets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker(KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.展开更多
In this paper, we propose a mathe- matical model for long reach Passive Optical Networks （PON） planning. The model consid- ers the traffic demand, user requirements and physical constraints. It can support conven- t...In this paper, we propose a mathe- matical model for long reach Passive Optical Networks （PON） planning. The model consid- ers the traffic demand, user requirements and physical constraints. It can support conven- tional star-like topologies as well as cascade PON networks. Then a two-stage evolutional algorithm is described to solve this problem. The first stage was to find a proper splitter can- didate site set, composing the outer loop. The second stage aimed to get the optimal topology when the splitter locations were selected, com- posing the internal loop. In this algorithm, the Pr/ifer sequence is used to build up a one-to-one correspondence between a PON network configuration and a chromosome. Compared with the results obtained by the enumeration method, the proposed model and algorithm are shown to be effective and accu- rate.展开更多
In this paper, we overview the principle of Orthogonal Frequency Division Multiplexing Passive Optical Network （OFDM-PON） systems, with a particular focus on upstream architectures capable of achieving 10Gbit/s colo...In this paper, we overview the principle of Orthogonal Frequency Division Multiplexing Passive Optical Network （OFDM-PON） systems, with a particular focus on upstream architectures capable of achieving 10Gbit/s colorless upstream transmission using Reflective Semiconductor Optical Amplifier （RSOA）. We propose an architecture of RSOA based OFDM-PON which can achieve 10Gbit/s upstream transmission over a single wavelength. A novel Dynamic Subcarrier Assignment （DSA） algorithm is also proposed to support my architecture, namely Service based Polling in Pipeline （SPP） dynamic subcarrier algorithm. A simulation was conducted to study the performance of SPP algorithm. Compared with the traditional dynamic bandwidth allocation algorithms, service based polling meets the quality of in pipeline algorithm service requirements excellently, and adapts orthogonal frequency division multiplexing passive optical network better with higher bandwidth efficiency and lower algorithm complexity.展开更多
The resource allocation problem in data centre networks refers to a map of the workloads provided by the cloud users/tenants to the Substrate Network(SN)which are provided by the cloud providers.Existing studies consi...The resource allocation problem in data centre networks refers to a map of the workloads provided by the cloud users/tenants to the Substrate Network(SN)which are provided by the cloud providers.Existing studies consider the dynamic arrival and departure of the workloads,while the dynamics of the substrate are ignored.In this paper,we first propose the resource allocation with the dynamic SN,and denote it as GraphMap-DS.Then,we propose an efficient mapping algorithm for GraphMap-DS.The performance of the proposed algorithm is evaluated by performing simulation experiments.Our results show that the proposed algorithm can effectively solve the GraphMap-DS.展开更多
基金ACKNOWLEDGEMENTS This work is supported by National Natural Science Foundation of China （No. 61171079）. The authors would like to thank the editors and the anonymous reviewers for their detailed constructive comments that helped to improve the presentation of this paper.
文摘Most resource allocation algorithms are based on interference power constraint in cognitive radio networks.Instead of using conventional primary user interference constraint,we give a new criterion called allowable signal to interference plus noise ratio(SINR) loss constraint in cognitive transmission to protect primary users.Considering power allocation problem for cognitive users over flat fading channels,in order to maximize throughput of cognitive users subject to the allowable SINR loss constraint and maximum transmit power for each cognitive user,we propose a new power allocation algorithm.The comparison of computer simulation between our proposed algorithm and the algorithm based on interference power constraint is provided to show that it gets more throughput and provides stability to cognitive radio networks.
基金supported by the 863 Program (2015AA01A705)NSFC (61271187)
文摘To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SON). In this paper, a novel CCO scheme is proposed to maximize utility function of the integrated coverage and capacity. It starts with the analysis on the throughput proportional fairness(PF) algorithm and then proposes the novel Coverage and Capacity Proportional Fairness(CCPF) allocation algorithm along with a proof of the algorithms convergence. This proposed algorithm is applied in a coverage capacity optimization scheme which can guarantee the reasonable network capacity by the coverage range accommodation. Next, we simulate the proposed CCO scheme based on telecom operators' real network data and compare with three typical resource allocation algorithms: round robin(RR), proportional fairness(PF) and max C/I. In comparison of the PF algorithm, the numerical results show that our algorithm increases the average throughput by 1.54 and 1.96 times with constructed theoretical data and derived real network data respectively.
基金jointly supported by Project 61501052 and 61302080 of the National Natural Science Foundation of China
文摘To fulfill the explosive growth of network capacity, fifth generation(5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio access network(H-CRAN), as a promising network paradigm in 5G system, is a hot research topic in recent years. However, the densely deployment of RRHs in H-CRAN leads to downlink/uplink traffic asymmetry and severe inter-cell interference which could seriously impair the network throughput and resource utilization. To simultaneously solve these two problems, we proposed a dynamic resource allocation(DRA) scheme for H-CRAN in TDD mode. Firstly, we design a clustering algorithm to group the RRHs into different sets. Secondly, we adopt coordinated multipoint technology to eliminate the interference in each set. Finally, we formulate the joint frame structure, power and subcarrier selection problem as a mixed strategy noncooperative game. The simulation results are presented to validate the effectiveness of our proposed algorithm by compared with the existing work.
基金supported by the National Natural Science Foundation of China(No.61501371)National 863 High Tech R&D Program of China(project number:2014AA01A703)+1 种基金National Science and Technology Major Project of the Ministry of Science and Technology of China(project number:2014ZX03001025-006)The international Exchange and Cooperation Projects of Shaanxi Province(project number:2016KW-046)
文摘To meet the increasing demand of wireless broadband applications in future 5G cellular networks, Device-to-Device(D2D) communications serve as a candidate paradigm to improve spectrum efficiency. Considering the challenges after D2 D transmission is introduced for future cellular networks, this paper deals with mode selection and resource allocation issues related with D2 D communications. First, we propose a mode selection scheme which aims at guaranteeing the transmission of cellular users and also considering the potential interference. We analyze the condition under which D2 D underlay mode should be used. Second, we answer the question of "how to effectively reuse cellular resource once underlaying mode is adopted". We further present a resource allocation scheme that focuses on minimizing overall interference as well as a power control method to improve the performance of D2 D systems. Simulation results demonstrate that system parameters greatly affect the switching condition of mode selection and probability of choosing underlay mode. Furthermore, for D2 D underlaying scenario, the proposed resource allocation algorithm guarantees the transmission of cellular users with consideration of transmission requirements of D2 D users. Hence, the proposed scheme can achieve better user experience.
基金This research was partially supported by the National Grand Fundamental Research 973 Program of China under Grant （No. 2013CB329103）, Natural Science Foundation of China grant （No. 61271171）, the Fundamental Research Funds for the Central Universities （ZYGX2013J002, ZYGX2012J004, ZYGX2010J002, ZYGX2010J009）, Guangdong Science and Technology Project （2012B090500003, 2012B091000163, 2012556031）.
文摘Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.
基金This work was supported in part by a grant from the National Basic Research Program of China(973 Program) under Grant No.2012CB315902,the National Natural Science Foundation of China under Grant No.61379120,61170215,the Program for Zhejiang Leading Team of Science and Technology Innovation under Grant No.2011R50010-12,2011R50010-18.Zhejiang Provincial Key Laboratory of New Network Standards and Technologies (NNST)
文摘Resource scheduling algorithm for ForCES(Forwarding and Control Element Separation) networks need to meet the flexibility,programmability and scalability of node resources.DBC(Deadline Budget Constrain) algorithm relies on users select cost or time priority,then scheduling to meet the requirements of users.However,this priority strategy of users is relatively simple,and cannot adapt to dynamic change of resources,it is inevitable to reduce the QoS.In order to improve QoS,we refer to the economic model and resource scheduling model of cloud computing,use SAL(Service Level Agreement) as pricing strategy,on the basis of DBC algorithm,propose an DABP(Deadline And Budget Priority based on DBC) algorithm for ForCES networks,DABP combines both budget and time priority to scheduling.In simulation and test,we compare the task finish time and cost of DABP algorithm with DP(Deadline Priority) algorithm and BP(Budget Priority) algorithm,the analysis results show that DABP algorithm make the task complete with less cost within deadline,benifical to load balancing of ForCES networks.
文摘Scalable video coding(SVC) is a powerful tool to solve the network heterogeneity and terminal diversity in video applications. However, in related works about the optimization of SVC-based video streaming over Software Defined Network(SDN), most of the them are focused either on the number of transmission layers or on the optimization of transmission path for specific layer. In this paper, we propose a noval optimization algorithm for SVC to dynamically adjust the number of layers and optimize the transmission paths simultaneously. We establish the problem model based on the 0/1 knapsack model, and then solve it with Artificial Fish Swarm Algorithm. Additionally, the simulations are carried out on the Mininet platform, which show that our approach can dynamically adjust the number of layers and select the optimal paths at the same time. As a result, it can achieve an effective allocation of network resources which mitigates the congestion and reduces the loss of non-SVC stream.
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 by the National Natural Science Foundation of China under Grant No.61371075the 863 project SS2015AA011306
文摘The tremendous performance gain of heterogeneous networks(Het Nets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for Het Nets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker(KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.
基金supported by National High Technology Research and Development Program of China under Grant No.2011AA01A104National 973 Program underGrant No. 2013CB329204National Natural Science Foundation of China under Grant No.61100206
文摘In this paper, we propose a mathe- matical model for long reach Passive Optical Networks （PON） planning. The model consid- ers the traffic demand, user requirements and physical constraints. It can support conven- tional star-like topologies as well as cascade PON networks. Then a two-stage evolutional algorithm is described to solve this problem. The first stage was to find a proper splitter can- didate site set, composing the outer loop. The second stage aimed to get the optimal topology when the splitter locations were selected, com- posing the internal loop. In this algorithm, the Pr/ifer sequence is used to build up a one-to-one correspondence between a PON network configuration and a chromosome. Compared with the results obtained by the enumeration method, the proposed model and algorithm are shown to be effective and accu- rate.
基金supported by NSFC Project No.61372119863 Program No.2011AA01A104Doctoral Scientific Fund Project of the Ministry of Education of China(No.20120005110010)
文摘In this paper, we overview the principle of Orthogonal Frequency Division Multiplexing Passive Optical Network （OFDM-PON） systems, with a particular focus on upstream architectures capable of achieving 10Gbit/s colorless upstream transmission using Reflective Semiconductor Optical Amplifier （RSOA）. We propose an architecture of RSOA based OFDM-PON which can achieve 10Gbit/s upstream transmission over a single wavelength. A novel Dynamic Subcarrier Assignment （DSA） algorithm is also proposed to support my architecture, namely Service based Polling in Pipeline （SPP） dynamic subcarrier algorithm. A simulation was conducted to study the performance of SPP algorithm. Compared with the traditional dynamic bandwidth allocation algorithms, service based polling meets the quality of in pipeline algorithm service requirements excellently, and adapts orthogonal frequency division multiplexing passive optical network better with higher bandwidth efficiency and lower algorithm complexity.
基金supported by the National Basic Research of China(973 Program)under Grant No.2011CB302601the National Natural Science Foundation of China under Grants No.90818028,No.6903043,No.61202117the National High Technology Research and Development Program of China(863 Program)under Grant No.2012AA011201
文摘The resource allocation problem in data centre networks refers to a map of the workloads provided by the cloud users/tenants to the Substrate Network(SN)which are provided by the cloud providers.Existing studies consider the dynamic arrival and departure of the workloads,while the dynamics of the substrate are ignored.In this paper,we first propose the resource allocation with the dynamic SN,and denote it as GraphMap-DS.Then,we propose an efficient mapping algorithm for GraphMap-DS.The performance of the proposed algorithm is evaluated by performing simulation experiments.Our results show that the proposed algorithm can effectively solve the GraphMap-DS.
