Real-world complex networks are inherently heterogeneous;they have different types of nodes,attributes,and relationships.In recent years,various methods have been proposed to automatically learn how to encode the stru...Real-world complex networks are inherently heterogeneous;they have different types of nodes,attributes,and relationships.In recent years,various methods have been proposed to automatically learn how to encode the structural and semantic information contained in heterogeneous information networks(HINs)into low-dimensional embeddings;this task is called heterogeneous network embedding(HNE).Efficient HNE techniques can benefit various HIN-based machine learning tasks such as node classification,recommender systems,and information retrieval.Here,we provide a comprehensive survey of key advancements in the area of HNE.First,we define an encoder-decoder-based HNE model taxonomy.Then,we systematically overview,compare,and summarize various state-of-the-art HNE models and analyze the advantages and disadvantages of various model categories to identify more potentially competitive HNE frameworks.We also summarize the application fields,benchmark datasets,open source tools,andperformance evaluation in theHNEarea.Finally,wediscuss open issues and suggest promising future directions.We anticipate that this survey will provide deep insights into research in the field of HNE.展开更多
On the multilingual online social networks of global information sharing,the wanton spread of rumors has an enormous negative impact on people's lives.Thus,it is essential to explore the rumor-spreading rules in m...On the multilingual online social networks of global information sharing,the wanton spread of rumors has an enormous negative impact on people's lives.Thus,it is essential to explore the rumor-spreading rules in multilingual environment and formulate corresponding control strategies to reduce the harm caused by rumor propagation.In this paper,considering the multilingual environment and intervention mechanism in the rumor-spreading process,an improved ignorants–spreaders-1–spreaders-2–removers(I2SR)rumor-spreading model with time delay and the nonlinear incidence is established in heterogeneous networks.Firstly,based on the mean-field equations corresponding to the model,the basic reproduction number is derived to ensure the existence of rumor-spreading equilibrium.Secondly,by applying Lyapunov stability theory and graph theory,the global stability of rumor-spreading equilibrium is analyzed in detail.In particular,aiming at the lowest control cost,the optimal control scheme is designed to optimize the intervention mechanism,and the optimal control conditions are derived using the Pontryagin's minimum principle.Finally,some illustrative examples are provided to verify the effectiveness of the theoretical results.The results show that optimizing the intervention mechanism can effectively reduce the densities of spreaders-1 and spreaders-2 within the expected time,which provides guiding insights for public opinion managers to control rumors.展开更多
Heterogeneous small cell network is one of the most effective solutions to overcome spectrum scarcity for the next generation of mobile networks.Dual connectivity(DC)can improve the throughput for each individual user...Heterogeneous small cell network is one of the most effective solutions to overcome spectrum scarcity for the next generation of mobile networks.Dual connectivity(DC)can improve the throughput for each individual user by allowing concurrent access to two heterogeneous radio networks.In this paper,we propose a joint user association and fair scheduling algorithm(JUAFS)to deal with the resource allocation and load balancing issues for DC heterogeneous small cell networks.Considering different coverage sizes,numbers of users,and quality of experience characteristics of heterogeneous cells,we present a proportional fair scheduling for user association among cells and utilize interference graph to minimize the transmission conflict probability.Simulation results show the performance improvement of the proposed algorithm in spectrum efficiency and fairness comparing to the existing schemes.展开更多
In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communi...In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission first.If there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be sent.This situation will cause excessive delay of LP data and packet dropping probability.In order to solve this problem,the data transmission process of high priority queue and low priority queue is studied.Considering the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority data.The quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further obtained.Then,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be expressed.The simulation results verify the correctness of the theoretical derivation.Meanwhile,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.展开更多
In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned...In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.展开更多
In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous network...In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous networks due to low utilization of bandwidth.To address this problem,a network-aware adaptive PS load distribution scheme is proposed,which accelerates model synchronization by proactively adjusting the communication load on PSs according to network states.We evaluate the proposed scheme on MXNet,known as a realworld distributed training platform,and results show that our scheme achieves up to 2.68 times speed-up of model training in the dynamic and heterogeneous network environment.展开更多
Although small cell offloading technology can alleviate the congestion in macrocell, aggressively offloading data traffic from macrocell to small cell can also degrade the performance of small cell due to the heavy lo...Although small cell offloading technology can alleviate the congestion in macrocell, aggressively offloading data traffic from macrocell to small cell can also degrade the performance of small cell due to the heavy load. Because of collision and backoff, the degradation is significant especially in network with contention-based channel access, and finally decreases throughput of the whole network. To find an optimal fraction of traffic to be offloaded in heterogeneous network, we combine Markov chain with the Poisson point process model to analyze contention-based throughput in irregularly deployment networks. Then we derive the close-form solution of the throughput and find that it is a function of the transmit power and density of base stations.Based on this, we propose the load-aware offloading strategies via power control and base station density adjustment. The numerical results verify our analysis and show a great performance gain compared with non-load-aware offloading.展开更多
In this paper,a new communication model is built named grouping D2D(GD2D).Different from the traditional D2D coordination,we proposed GD2D communication in licensed and unlicensed spectrum simultaneously.We formulate ...In this paper,a new communication model is built named grouping D2D(GD2D).Different from the traditional D2D coordination,we proposed GD2D communication in licensed and unlicensed spectrum simultaneously.We formulate a resource allocation problem,which aims at maximizing the energy efficiency(EE)of the system while guaranteeing the quality-of-service(Qos)of users.To efficiently solve this problem,the non-convex optimization problem is first transformed into a convex optimization problem.By transforming the fractional-form problem into an equivalent subtractive-form problem,an iterative power allocation algorithm is proposed to maximize the system EE.Moreover,the optimal closedform power allocation expressions are derived by the Lagrangian approach.Simulation results show that our algorithm achieves higher EE performance than the traditional D2D communication scheme.展开更多
Convergence and collaboration of heterogeneous networks in the next generation public mobile networks will be a subject of universal significance. Convergence of heterogeneous networks, as an effective approach to imp...Convergence and collaboration of heterogeneous networks in the next generation public mobile networks will be a subject of universal significance. Convergence of heterogeneous networks, as an effective approach to improve the coverage and capacity of public mobile network, to enable communication services, to provide Internet access and to enable mobile computing from everywhere, has drawn widespread attention for its good prospects in application. Construction of security system for wireless heterogeneous networks and development of new security models, key security techniques and approaches are critical and mandatory in heterogeneous networks development. Key technology of wireless heterogeneous networks security covers security routing protocol, access authentication, intrusion detection system, cooperative communication between nodes, etc.展开更多
The heterogeneous network convergence is the trend of future network development. However, many bottlenecks exist in the converged system such as high time delay, high energy consumption, and low data rate. Multi-Radi...The heterogeneous network convergence is the trend of future network development. However, many bottlenecks exist in the converged system such as high time delay, high energy consumption, and low data rate. Multi-Radio Cooperation (MRC) technology is specially designed to overcome these bottlenecks and to satisfy the requirements of heterogeneous network convergence. MRC can improve network capacity, reduce the energy consumption of radio devices, and decrease handover latency between heterogeneous networks by the cooperation of multiple radios, and by efficient management and feasible allocation of multi-radio resources. MRC makes real seamless heterogeneous network convergence possible.展开更多
The research of three-dimensional integrated communication technology plays a key role in achieving the ubiquitous connectivity,ultra-high data rates,and emergency communications in the sixth generation(6G)networks.Ae...The research of three-dimensional integrated communication technology plays a key role in achieving the ubiquitous connectivity,ultra-high data rates,and emergency communications in the sixth generation(6G)networks.Aerial networking provides a prom⁃ising solution to flexible,scalable,low-cost and reliable coverage for wireless devices.The integration of aerial network and terrestrial network has been an inevitable paradigm in the 6G era.However,energy-efficient communications and networking among aerial net⁃work and terrestrial network face great challenges.This paper is dedicated to discussing green communications of the air-ground integrated heterogeneous network(AGIHN).We first provide a brief introduction to the characteristics of AGIHN in 6G networks.Further,we analyze the challenges of green AGIHN from the aspects of green terrestrial networks and green aerial networks.Finally,several solutions to and key technologies of the green AGIHN are discussed.展开更多
Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when ...Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency.However,because of the transmit power differences in different tiers of HetNets and irregular service demand,a load imbalance typically exists among different serving nodes.To offload more traffic to LPNs and coordinate the Inter-Cell Interference(ICI),Third-Generation Partnership Project(3GPP)has facilitated the development of the Cell Range Expansion(CRE),enhanced Inter-Cell Interference Coordination(eICIC)and Further enhanced ICIC(FeICIC).In this paper,we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe(LPS)approach.Our solution allows the separation of User Association(UA)functions at the User Equipment(UE)and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength(max-RSS)based UA scheme,where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system.The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions.Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.展开更多
As a promising technology to improve spectrum efficiency and transmission coverage,Heterogeneous Network(HetNet)has attracted the attention of many scholars in recent years.Additionally,with the introduction of the No...As a promising technology to improve spectrum efficiency and transmission coverage,Heterogeneous Network(HetNet)has attracted the attention of many scholars in recent years.Additionally,with the introduction of the Non-Orthogonal Multiple Access(NOMA)technology,the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource,which makes the NOMA-assisted HetNet a hot topic.However,traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains,which is impractical for practical HetNets due to the impact of channel delays and random perturbation.To further improve energy utilization and system robustness,in this paper,we investigate a robust resource allocation problem to maximize the total Energy Efficiency(EE)of Small-Cell Users(SCUs)in NOMA-assisted HetNets under imperfect channel state information.By considering bounded channel uncertainties,the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users,the maximum transmit power of small base station,the Resource Block(RB)assignment,and the quality of service requirement of each SCU.The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method.A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation.Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.展开更多
A cosimulation platform was established for distributed control systems via heterogeneous network,which integrated OPNET and Matlab/Simulink.The communication node in this cosimulation platform was built based on OSI ...A cosimulation platform was established for distributed control systems via heterogeneous network,which integrated OPNET and Matlab/Simulink.The communication node in this cosimulation platform was built based on OSI model and UDP protocol,which was adopted as the transportation layer protocol.Data exchanged between the data source module and the specified node.It was fulfilled by revising the corresponding protocol modules based on the characteristics of UDP.The effectiveness of the constructed simulation platform was demonstrated by a numerical example.展开更多
TISPAN,from a fixed access perspective,proposes Resource and Admission Control Subsystem[0](RACS) as a solution to Quality of Service(QoS) problem for NGN bearer network.In contrast,3GPP has an approach to this from t...TISPAN,from a fixed access perspective,proposes Resource and Admission Control Subsystem[0](RACS) as a solution to Quality of Service(QoS) problem for NGN bearer network.In contrast,3GPP has an approach to this from the perspective of mobile access.In the latest 3GPP R7 draft,integration of Policy Control Function(PCF) with Flow Based Charging(FBC) function of the R6 brought forward policy control and charging.With the development of fixed mobile convergence,the inconsistence in architectures and interfaces of different resource and admission control[0] solutions will have a huge impact on manufacture and network implementation of NGN related equipment.To solve this problem,both 3GPP and TISPAN have been working on the convergence of Gq'/Rx reference points.Harmonized Policy Control and Charging(PCC) proposed by the Next Generation Mobile Network(NGMN) forum,i.e.cooperative resource control architecture for heterogeneous networks,represents an evolutional sign post for resource control technology for heterogeneous network architecture.展开更多
To provide any subscriber from anywhere at anytime with services that have both secured Quality of Service(QoS) and simultaneous expansion of network coverage and communications capacity is a key problem that has to b...To provide any subscriber from anywhere at anytime with services that have both secured Quality of Service(QoS) and simultaneous expansion of network coverage and communications capacity is a key problem that has to be considered and solved in heterogeneous network convergence.Key technologies for a secured QoS and communications capacity analysis under heterogeneous environment are important subjects for research.Key technologies for a secured QoS are mainly on radio resource management algorithms covering Call Admission Control(CAC) algorithm,vertical handover algorithm,heterogeneous resource allocation algorithm and network selection algorithm.The applications of a novel multi-hop in heterogeneous convergence system serve the purposes of network coverage expansion,transmission power reduction,system communication capacity and throughput increase.展开更多
A network selection optimization algorithm based on the Markov decision process(MDP)is proposed so that mobile terminals can always connect to the best wireless network in a heterogeneous network environment.Consideri...A network selection optimization algorithm based on the Markov decision process(MDP)is proposed so that mobile terminals can always connect to the best wireless network in a heterogeneous network environment.Considering the different types of service requirements,the MDP model and its reward function are constructed based on the quality of service(QoS)attribute parameters of the mobile users,and the network attribute weights are calculated by using the analytic hierarchy process(AHP).The network handoff decision condition is designed according to the different types of user services and the time-varying characteristics of the network,and the MDP model is solved by using the genetic algorithm and simulated annealing(GA-SA),thus,users can seamlessly switch to the network with the best long-term expected reward value.Simulation results show that the proposed algorithm has good convergence performance,and can guarantee that users with different service types will obtain satisfactory expected total reward values and have low numbers of network handoffs.展开更多
The future network world will be embedded with different generations of wireless technologies,such as 3G,4G and 5G.At the same time,the development of new devices equipped with multiple interfaces is growing rapidly i...The future network world will be embedded with different generations of wireless technologies,such as 3G,4G and 5G.At the same time,the development of new devices equipped with multiple interfaces is growing rapidly in recent years.As a consequence,the vertical handover protocol is developed in order to provide ubiquitous connectivity in the heterogeneous wireless environment.Indeed,by using this protocol,the users have opportunities to be connected to the Internet through a variety of wireless technologies at any time and anywhere.The main challenge of this protocol is how to select the best access network in terms of Quality of Service(QoS)for users.For that,many algorithms have been proposed and developed to deal with the issue in recent studies.However,all existing algorithms permit only the selection of one access network from the available networks during the vertical handover process.To cope with this problem,in this paper we propose a new approach based on k-partite graph.Firstly,we introduce k-partite graph theory to model the vertical handover problem.Secondly,the selection of the best path is performed by a robust and lightweight mechanism based on cost function and Dijkstra’s algorithm.The experimental results show that the proposed approach can achieve better performance of QoS than the existing algorithms for FTP traffic and video streaming.展开更多
We propose a novel rumor propagation model with guidance mechanism in hetero geneous complex networks.Firstly,the sharp threshold of rumor propagation,global stability of the information-equilibrium and information-pr...We propose a novel rumor propagation model with guidance mechanism in hetero geneous complex networks.Firstly,the sharp threshold of rumor propagation,global stability of the information-equilibrium and information-prevailingequilibrium under R_(0)<1 and R_(0)>1 is carried out by Lyapunov method and LaSalle's invariant principle.Next,we design an aperiodically intermittent stochastic stabilization method to suppress the rumor propagation.By using the Ito formula and exponential martingale inequality,the expression of the minimum control intensity is calculated.This method can effectively stabilize the rumor propagation by choosing a suitable perturb intensity and a perturb time ratio,while minimizing the control cost.Finally,numerical examples are given to illustrate the analysis and method of the paper.展开更多
Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning models.However,any metapath...Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning models.However,any metapaths consisting of multiple,simple metarelations must be driven by domain experts.These sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this problem.Specifically,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given metapaths.Thereafter,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node type.Next,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link type.Finally,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the models.Extensive experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.展开更多
基金supported by the National Key Research and Development Plan of China(2017YFB0503700,2016YFB0501801)the National Natural Science Foundation of China(61170026,62173157)+1 种基金the Thirteen Five-Year Research Planning Project of National Language Committee(No.YB135-149)the Fundamental Research Funds for the Central Universities(Nos.CCNU20QN022,CCNU20QN021,CCNU20ZT012).
文摘Real-world complex networks are inherently heterogeneous;they have different types of nodes,attributes,and relationships.In recent years,various methods have been proposed to automatically learn how to encode the structural and semantic information contained in heterogeneous information networks(HINs)into low-dimensional embeddings;this task is called heterogeneous network embedding(HNE).Efficient HNE techniques can benefit various HIN-based machine learning tasks such as node classification,recommender systems,and information retrieval.Here,we provide a comprehensive survey of key advancements in the area of HNE.First,we define an encoder-decoder-based HNE model taxonomy.Then,we systematically overview,compare,and summarize various state-of-the-art HNE models and analyze the advantages and disadvantages of various model categories to identify more potentially competitive HNE frameworks.We also summarize the application fields,benchmark datasets,open source tools,andperformance evaluation in theHNEarea.Finally,wediscuss open issues and suggest promising future directions.We anticipate that this survey will provide deep insights into research in the field of HNE.
基金the National Natural Science Foundation of People’s Republic of China(Grant Nos.U1703262 and 62163035)the Special Project for Local Science and Technology Development Guided by the Central Government(Grant No.ZYYD2022A05)Xinjiang Key Laboratory of Applied Mathematics(Grant No.XJDX1401)。
文摘On the multilingual online social networks of global information sharing,the wanton spread of rumors has an enormous negative impact on people's lives.Thus,it is essential to explore the rumor-spreading rules in multilingual environment and formulate corresponding control strategies to reduce the harm caused by rumor propagation.In this paper,considering the multilingual environment and intervention mechanism in the rumor-spreading process,an improved ignorants–spreaders-1–spreaders-2–removers(I2SR)rumor-spreading model with time delay and the nonlinear incidence is established in heterogeneous networks.Firstly,based on the mean-field equations corresponding to the model,the basic reproduction number is derived to ensure the existence of rumor-spreading equilibrium.Secondly,by applying Lyapunov stability theory and graph theory,the global stability of rumor-spreading equilibrium is analyzed in detail.In particular,aiming at the lowest control cost,the optimal control scheme is designed to optimize the intervention mechanism,and the optimal control conditions are derived using the Pontryagin's minimum principle.Finally,some illustrative examples are provided to verify the effectiveness of the theoretical results.The results show that optimizing the intervention mechanism can effectively reduce the densities of spreaders-1 and spreaders-2 within the expected time,which provides guiding insights for public opinion managers to control rumors.
基金supported in part by the National Natural Science Foundation of China under Grant 61871433,61828103in part by the Research Platform of South China Normal University and Foshan。
文摘Heterogeneous small cell network is one of the most effective solutions to overcome spectrum scarcity for the next generation of mobile networks.Dual connectivity(DC)can improve the throughput for each individual user by allowing concurrent access to two heterogeneous radio networks.In this paper,we propose a joint user association and fair scheduling algorithm(JUAFS)to deal with the resource allocation and load balancing issues for DC heterogeneous small cell networks.Considering different coverage sizes,numbers of users,and quality of experience characteristics of heterogeneous cells,we present a proportional fair scheduling for user association among cells and utilize interference graph to minimize the transmission conflict probability.Simulation results show the performance improvement of the proposed algorithm in spectrum efficiency and fairness comparing to the existing schemes.
基金2020 MajorNatural Science Research Project of Jiangsu Province Colleges and Universities:Research on Forensic Modeling and Analysis of the Internet of Things(20KJA520004)2020 Open Project of National and Local Joint Engineering Laboratory of Radio Frequency Integration andMicro-assembly Technology:Research on the Security Performance of Radio Frequency Energy Collection Cooperative Communication Network(KFJJ20200201)+1 种基金2021 Jiangsu Police Officer Academy Scientific Research Project:Research on D2D Cache Network Resource Optimization Based on Edge Computing Technology(2021SJYZK01)High-level Introduction of Talent Scientific Research Start-up Fund of Jiangsu Police Institute(JSPI19GKZL407).
文摘In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission first.If there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be sent.This situation will cause excessive delay of LP data and packet dropping probability.In order to solve this problem,the data transmission process of high priority queue and low priority queue is studied.Considering the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority data.The quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further obtained.Then,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be expressed.The simulation results verify the correctness of the theoretical derivation.Meanwhile,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.
文摘In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.
基金partially supported by the computing power networks and new communication primitives project under Grant No. HC-CN-2020120001the National Natural Science Foundation of China under Grant No. 62102066Open Research Projects of Zhejiang Lab under Grant No. 2022QA0AB02
文摘In distributed machine learning(DML)based on the parameter server(PS)architecture,unbalanced communication load distribution of PSs will lead to a significant slowdown of model synchronization in heterogeneous networks due to low utilization of bandwidth.To address this problem,a network-aware adaptive PS load distribution scheme is proposed,which accelerates model synchronization by proactively adjusting the communication load on PSs according to network states.We evaluate the proposed scheme on MXNet,known as a realworld distributed training platform,and results show that our scheme achieves up to 2.68 times speed-up of model training in the dynamic and heterogeneous network environment.
基金supported by the National High-Tech R&D Program (863 Program) under grant No. 2015AA01A705Beijing Municipal Science and Technology Commission research fund project under grant No. D151100000115002+1 种基金China Scholarship Council under grant No. 201406470038BUPT youth scientific research innovation program under grant No. 500401238
文摘Although small cell offloading technology can alleviate the congestion in macrocell, aggressively offloading data traffic from macrocell to small cell can also degrade the performance of small cell due to the heavy load. Because of collision and backoff, the degradation is significant especially in network with contention-based channel access, and finally decreases throughput of the whole network. To find an optimal fraction of traffic to be offloaded in heterogeneous network, we combine Markov chain with the Poisson point process model to analyze contention-based throughput in irregularly deployment networks. Then we derive the close-form solution of the throughput and find that it is a function of the transmit power and density of base stations.Based on this, we propose the load-aware offloading strategies via power control and base station density adjustment. The numerical results verify our analysis and show a great performance gain compared with non-load-aware offloading.
基金supported in part by the National Natural Science Foundation of China under Grant no.61473066 and Grant no.61601109in part by the Fundamental Research Funds for the Central Universities under Grant No.N152305001.
文摘In this paper,a new communication model is built named grouping D2D(GD2D).Different from the traditional D2D coordination,we proposed GD2D communication in licensed and unlicensed spectrum simultaneously.We formulate a resource allocation problem,which aims at maximizing the energy efficiency(EE)of the system while guaranteeing the quality-of-service(Qos)of users.To efficiently solve this problem,the non-convex optimization problem is first transformed into a convex optimization problem.By transforming the fractional-form problem into an equivalent subtractive-form problem,an iterative power allocation algorithm is proposed to maximize the system EE.Moreover,the optimal closedform power allocation expressions are derived by the Lagrangian approach.Simulation results show that our algorithm achieves higher EE performance than the traditional D2D communication scheme.
基金the Jiangsu Natural Science Foundation under Grant No.BK2007236Jiangsu Six-Categories Top Talent Fundunder Grand No.SJ207001
文摘Convergence and collaboration of heterogeneous networks in the next generation public mobile networks will be a subject of universal significance. Convergence of heterogeneous networks, as an effective approach to improve the coverage and capacity of public mobile network, to enable communication services, to provide Internet access and to enable mobile computing from everywhere, has drawn widespread attention for its good prospects in application. Construction of security system for wireless heterogeneous networks and development of new security models, key security techniques and approaches are critical and mandatory in heterogeneous networks development. Key technology of wireless heterogeneous networks security covers security routing protocol, access authentication, intrusion detection system, cooperative communication between nodes, etc.
基金the Natural Science Foundation of Jiangsu Province under Grant No.BK2007729
文摘The heterogeneous network convergence is the trend of future network development. However, many bottlenecks exist in the converged system such as high time delay, high energy consumption, and low data rate. Multi-Radio Cooperation (MRC) technology is specially designed to overcome these bottlenecks and to satisfy the requirements of heterogeneous network convergence. MRC can improve network capacity, reduce the energy consumption of radio devices, and decrease handover latency between heterogeneous networks by the cooperation of multiple radios, and by efficient management and feasible allocation of multi-radio resources. MRC makes real seamless heterogeneous network convergence possible.
基金This work was supported by National Natural Science Foundation of Chi⁃na under Grant Nos.61901051 and 61932005.
文摘The research of three-dimensional integrated communication technology plays a key role in achieving the ubiquitous connectivity,ultra-high data rates,and emergency communications in the sixth generation(6G)networks.Aerial networking provides a prom⁃ising solution to flexible,scalable,low-cost and reliable coverage for wireless devices.The integration of aerial network and terrestrial network has been an inevitable paradigm in the 6G era.However,energy-efficient communications and networking among aerial net⁃work and terrestrial network face great challenges.This paper is dedicated to discussing green communications of the air-ground integrated heterogeneous network(AGIHN).We first provide a brief introduction to the characteristics of AGIHN in 6G networks.Further,we analyze the challenges of green AGIHN from the aspects of green terrestrial networks and green aerial networks.Finally,several solutions to and key technologies of the green AGIHN are discussed.
文摘Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency.However,because of the transmit power differences in different tiers of HetNets and irregular service demand,a load imbalance typically exists among different serving nodes.To offload more traffic to LPNs and coordinate the Inter-Cell Interference(ICI),Third-Generation Partnership Project(3GPP)has facilitated the development of the Cell Range Expansion(CRE),enhanced Inter-Cell Interference Coordination(eICIC)and Further enhanced ICIC(FeICIC).In this paper,we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe(LPS)approach.Our solution allows the separation of User Association(UA)functions at the User Equipment(UE)and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength(max-RSS)based UA scheme,where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system.The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions.Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.
基金This work was supported by the National Natural Science Foundation of China(No.61601071,62071078)the National Key Research and Development Program of China(No.2019YFC1511300)+2 种基金the Natural Science Foundation of Chongqing(No.cstc2019jcyj-xfkxX0002)the Chongqing Entrepreneurship and Innovation Program for the Returned Overseas Chinese Scholars(No.cx2020095)the Graduate Scientific Research Innovation Project of Chongqing(No.CYS20251,CYS20253).
文摘As a promising technology to improve spectrum efficiency and transmission coverage,Heterogeneous Network(HetNet)has attracted the attention of many scholars in recent years.Additionally,with the introduction of the Non-Orthogonal Multiple Access(NOMA)technology,the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource,which makes the NOMA-assisted HetNet a hot topic.However,traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains,which is impractical for practical HetNets due to the impact of channel delays and random perturbation.To further improve energy utilization and system robustness,in this paper,we investigate a robust resource allocation problem to maximize the total Energy Efficiency(EE)of Small-Cell Users(SCUs)in NOMA-assisted HetNets under imperfect channel state information.By considering bounded channel uncertainties,the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users,the maximum transmit power of small base station,the Resource Block(RB)assignment,and the quality of service requirement of each SCU.The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method.A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation.Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.
基金National Natural Science Foundation of China(No.61573237)Natural Science Foundation of Shanghai,China(No.13ZR1416300)
文摘A cosimulation platform was established for distributed control systems via heterogeneous network,which integrated OPNET and Matlab/Simulink.The communication node in this cosimulation platform was built based on OSI model and UDP protocol,which was adopted as the transportation layer protocol.Data exchanged between the data source module and the specified node.It was fulfilled by revising the corresponding protocol modules based on the characteristics of UDP.The effectiveness of the constructed simulation platform was demonstrated by a numerical example.
文摘TISPAN,from a fixed access perspective,proposes Resource and Admission Control Subsystem[0](RACS) as a solution to Quality of Service(QoS) problem for NGN bearer network.In contrast,3GPP has an approach to this from the perspective of mobile access.In the latest 3GPP R7 draft,integration of Policy Control Function(PCF) with Flow Based Charging(FBC) function of the R6 brought forward policy control and charging.With the development of fixed mobile convergence,the inconsistence in architectures and interfaces of different resource and admission control[0] solutions will have a huge impact on manufacture and network implementation of NGN related equipment.To solve this problem,both 3GPP and TISPAN have been working on the convergence of Gq'/Rx reference points.Harmonized Policy Control and Charging(PCC) proposed by the Next Generation Mobile Network(NGMN) forum,i.e.cooperative resource control architecture for heterogeneous networks,represents an evolutional sign post for resource control technology for heterogeneous network architecture.
基金the National Basic Research Program of China("973"Program)under Grant No.2007CB310606the Specialized Foundation for the Achievements Transformation of Science and Technology in Jiangsu Province under Grant No.BA2006101
文摘To provide any subscriber from anywhere at anytime with services that have both secured Quality of Service(QoS) and simultaneous expansion of network coverage and communications capacity is a key problem that has to be considered and solved in heterogeneous network convergence.Key technologies for a secured QoS and communications capacity analysis under heterogeneous environment are important subjects for research.Key technologies for a secured QoS are mainly on radio resource management algorithms covering Call Admission Control(CAC) algorithm,vertical handover algorithm,heterogeneous resource allocation algorithm and network selection algorithm.The applications of a novel multi-hop in heterogeneous convergence system serve the purposes of network coverage expansion,transmission power reduction,system communication capacity and throughput increase.
基金partially supported by Nation Science Foundation of China (61661025, 61661026)Foundation of A hundred Youth Talents Training Program of Lanzhou Jiaotong University (152022)
文摘A network selection optimization algorithm based on the Markov decision process(MDP)is proposed so that mobile terminals can always connect to the best wireless network in a heterogeneous network environment.Considering the different types of service requirements,the MDP model and its reward function are constructed based on the quality of service(QoS)attribute parameters of the mobile users,and the network attribute weights are calculated by using the analytic hierarchy process(AHP).The network handoff decision condition is designed according to the different types of user services and the time-varying characteristics of the network,and the MDP model is solved by using the genetic algorithm and simulated annealing(GA-SA),thus,users can seamlessly switch to the network with the best long-term expected reward value.Simulation results show that the proposed algorithm has good convergence performance,and can guarantee that users with different service types will obtain satisfactory expected total reward values and have low numbers of network handoffs.
文摘The future network world will be embedded with different generations of wireless technologies,such as 3G,4G and 5G.At the same time,the development of new devices equipped with multiple interfaces is growing rapidly in recent years.As a consequence,the vertical handover protocol is developed in order to provide ubiquitous connectivity in the heterogeneous wireless environment.Indeed,by using this protocol,the users have opportunities to be connected to the Internet through a variety of wireless technologies at any time and anywhere.The main challenge of this protocol is how to select the best access network in terms of Quality of Service(QoS)for users.For that,many algorithms have been proposed and developed to deal with the issue in recent studies.However,all existing algorithms permit only the selection of one access network from the available networks during the vertical handover process.To cope with this problem,in this paper we propose a new approach based on k-partite graph.Firstly,we introduce k-partite graph theory to model the vertical handover problem.Secondly,the selection of the best path is performed by a robust and lightweight mechanism based on cost function and Dijkstra’s algorithm.The experimental results show that the proposed approach can achieve better performance of QoS than the existing algorithms for FTP traffic and video streaming.
基金Project supported by the Guangzhou Science and Technology Project(Grant No.20210202710)Scientific Research Project of Guangzhou University(Grant No.YG2020010)。
文摘We propose a novel rumor propagation model with guidance mechanism in hetero geneous complex networks.Firstly,the sharp threshold of rumor propagation,global stability of the information-equilibrium and information-prevailingequilibrium under R_(0)<1 and R_(0)>1 is carried out by Lyapunov method and LaSalle's invariant principle.Next,we design an aperiodically intermittent stochastic stabilization method to suppress the rumor propagation.By using the Ito formula and exponential martingale inequality,the expression of the minimum control intensity is calculated.This method can effectively stabilize the rumor propagation by choosing a suitable perturb intensity and a perturb time ratio,while minimizing the control cost.Finally,numerical examples are given to illustrate the analysis and method of the paper.
基金supported by the National Key Research and Development Program(No.2019YFE0105300)the National Natural Science Foundation of China(No.62103143)+2 种基金the Hunan Province Key Research and Development Program(No.2022WK2006)the Special Project for the Construction of Innovative Provinces in Hunan(Nos.2020TP2018 and 2019GK4030)the Scientific Research Fund of Hunan Provincial Education Department(No.22B0471).
文摘Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning models.However,any metapaths consisting of multiple,simple metarelations must be driven by domain experts.These sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this problem.Specifically,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given metapaths.Thereafter,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node type.Next,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link type.Finally,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the models.Extensive experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.
