In this paper,a hybrid cache placement scheme for multihop wireless service networks is proposed. In this scheme,hot nodes in data transferring path are mined up by means of rout-ing navigation graph,and whole network...In this paper,a hybrid cache placement scheme for multihop wireless service networks is proposed. In this scheme,hot nodes in data transferring path are mined up by means of rout-ing navigation graph,and whole network is covered with network clustering scheme. A hot node has been chosen for cache place-ment in each cluster,and the nodes within a cluster access cache data with no more than two hops. The cache placement scheme reduces data access latency and workload of the server node. It also reduces the average length of data transferring,which means that fewer nodes are involved. The network system energy con-sumption decreased as involved relay nodes reduced. The per-formance analysis shows that the scheme achieves significant system performance improvement in network environment,with a large number of nodes.展开更多
With the rapid development of 5G technology,the proportion of video traffic on the Internet is increasing,bringing pressure on the network infrastructure.Edge computing technology provides a feasible solution for opti...With the rapid development of 5G technology,the proportion of video traffic on the Internet is increasing,bringing pressure on the network infrastructure.Edge computing technology provides a feasible solution for optimizing video content distribution.However,the limited edge node cache capacity and dynamic user requests make edge caching more complex.Therefore,we propose a recommendation-driven edge Caching network architecture for the Full life cycle of video streaming(FlyCache)designed to improve users’Quality of Experience(QoE)and reduce backhaul traffic consumption.FlyCache implements intelligent caching management across three key stages:before-playback,during-playback,and after-playback.Specifically,we introduce a cache placement policy for the before-playback stage,a dynamic prefetching and cache admission policy for the during-playback stage,and a progressive cache eviction policy for the after-playback stage.To validate the effectiveness of FlyCache,we developed a user behavior-driven edge caching simulation framework incorporating recommendation mechanisms.Experiments conducted on the MovieLens and synthetic datasets demonstrate that FlyCache outperforms other caching strategies in terms of byte hit rate,backhaul traffic,and delayed startup rate.展开更多
In remote terrestrial-satellite networks, caching is a very promising technique to alleviate the burden of space cloudlet(e.g., cache-enabled satellite user terminal) and to improve subscribers' quality of experie...In remote terrestrial-satellite networks, caching is a very promising technique to alleviate the burden of space cloudlet(e.g., cache-enabled satellite user terminal) and to improve subscribers' quality of experience(Qo E) in terms of buffering delay and achievable video streaming rate. In this paper, we studied a Qo E-driven caching placement optimization problem for video streaming that takes into account the required video streaming rate and the social relationship among users. Social ties between users are used to designate a set of helpers with caching capability, which can cache popular files proactively when the cloudlet is idle. We model the utility function of Qo E as a logarithmic function. Then, the caching placement problem is formulated as an optimization problem to maximize the user's average Qo E subject to the storage capacity constraints of the helpers and the cloudlets. Furthermore, we reformulate the problem into a monotone submodular optimization problem with a partition matroid constraint, and an efficient greedy algorithm with 1-1 e approximation ratio is proposed to solve it. Simulation results show that the proposed caching placement approach significantly outperforms the traditional approaches in terms of Qo E, while yields about the same delay and hit ratio performance compare to the delay-minimized scheme.展开更多
With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has ensued.The emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also...With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has ensued.The emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also significantly improve user experience.Integrating with the MEC and satellite networks,the network is empowered popular content ubiquitously and seamlessly.Addressing the research gap between multilayer satellite networks and MEC,we study the caching placement problem in this paper.Initially,we introduce a three-layer distributed network caching management architecture designed for efficient and flexible handling of large-scale networks.Considering the constraint on satellite capacity and content propagation delay,the cache placement problem is then formulated and transformed into a markov decision process(MDP),where the content coded caching mechanism is utilized to promote the efficiency of content delivery.Furthermore,a new generic metric,content delivery cost,is proposed to elaborate the performance of caching decision in large-scale networks.Then,we introduce a graph convolutional network(GCN)-based multi-agent advantage actor-critic(A2C)algorithm to optimize the caching decision.Finally,extensive simulations are conducted to evaluate the proposed algorithm in terms of content delivery cost and transferability.展开更多
Non-orthogonal multiple access(NOMA)based fog radio access networks(F-RANs)offer high spectrum efficiency,ultra-low delay,and huge network throughput,and this is made possible by edge computing and communication funct...Non-orthogonal multiple access(NOMA)based fog radio access networks(F-RANs)offer high spectrum efficiency,ultra-low delay,and huge network throughput,and this is made possible by edge computing and communication functions of the fog access points(F-APs).Meanwhile,caching-enabled F-APs are responsible for edge caching and delivery of a large volume of multimedia files during the caching phase,which facilitates further reduction in the transmission energy and burden.The need of the prevailing situation in industry is that in NOMA-based F-RANs,energy-efficient resource allocation,which consists of cache placement(CP)and radio resource allocation(RRA),is crucial for network performance enhancement.To this end,in this paper,we first characterize an NOMA-based F-RAN in which F-APs of caching capabilities underlaid with the radio remote heads serve user equipments via the NOMA protocol.Then,we formulate a resource allocation problem for maximizing the defined performance indicator,namely network profit,which takes caching cost,revenue,and energy efficiency into consideration.The NP-hard problem is decomposed into two sub-problems,namely the CP sub-problem and RRA sub-problem.Finally,we propose an iterative method and a Stackelberg game based method to solve them,and numerical results show that the proposed solution can significantly improve network profit compared to some existing schemes in NOMA-based F-RANs.展开更多
Along with natural disasters,the destruction of communication infrastructures leads to the congestion or failure of communication networks.Unmanned aerial vehicles(UAVs),which are with a high flexibility,can be employ...Along with natural disasters,the destruction of communication infrastructures leads to the congestion or failure of communication networks.Unmanned aerial vehicles(UAVs),which are with a high flexibility,can be employed as temporary base stations to establish emergency networks.To relieve the backhaul burden of UAVs,some imperative contents can be cached by terrestrial cache-enabled rescuers(CERs)and provide for victims with device-to-device(D2D)transmissions.To support the effectiveness and timeliness of emergency communication,the delay-bounded quality-of-service(QoS)requirement and network throughput are desired to be comprehensively considered,which imposes a new challenge for caching placement and CER deployment.In this paper,we focus on joint caching placement and CER deployment to maximize the effective capacity subject to delay-bounded QoS requirement.The overall non-convex problem is transformed into the caching placement and the CER deployment sub-problems.Then,we develop the QoS-aware caching placement scheme with fixed CER deployment density and obtain the QoS-aware CER deployment density with fixed caching placement.Based on the block-coordinate descent method,we also propose the joint caching placement and CER deployment scheme,which can not only effectively enhance average effective capacity but also guarantee the delay-bounded QoS requirement.Also,numerical simulations are conducted to show the performances of the proposed schemes.展开更多
基金Supported by the National Basic Research Program of China (973 Program)(2004CB318201)National High Technology Research and Development Program of China (863 Program)(2008AA01A402) Program for Changjiang Scholars and Innovative Research Team in University of China (IRT0725)
文摘In this paper,a hybrid cache placement scheme for multihop wireless service networks is proposed. In this scheme,hot nodes in data transferring path are mined up by means of rout-ing navigation graph,and whole network is covered with network clustering scheme. A hot node has been chosen for cache place-ment in each cluster,and the nodes within a cluster access cache data with no more than two hops. The cache placement scheme reduces data access latency and workload of the server node. It also reduces the average length of data transferring,which means that fewer nodes are involved. The network system energy con-sumption decreased as involved relay nodes reduced. The per-formance analysis shows that the scheme achieves significant system performance improvement in network environment,with a large number of nodes.
基金supported by the National Natural Science Foundation of China(NSFC)[Grant No.62072469].
文摘With the rapid development of 5G technology,the proportion of video traffic on the Internet is increasing,bringing pressure on the network infrastructure.Edge computing technology provides a feasible solution for optimizing video content distribution.However,the limited edge node cache capacity and dynamic user requests make edge caching more complex.Therefore,we propose a recommendation-driven edge Caching network architecture for the Full life cycle of video streaming(FlyCache)designed to improve users’Quality of Experience(QoE)and reduce backhaul traffic consumption.FlyCache implements intelligent caching management across three key stages:before-playback,during-playback,and after-playback.Specifically,we introduce a cache placement policy for the before-playback stage,a dynamic prefetching and cache admission policy for the during-playback stage,and a progressive cache eviction policy for the after-playback stage.To validate the effectiveness of FlyCache,we developed a user behavior-driven edge caching simulation framework incorporating recommendation mechanisms.Experiments conducted on the MovieLens and synthetic datasets demonstrate that FlyCache outperforms other caching strategies in terms of byte hit rate,backhaul traffic,and delayed startup rate.
基金supported by Natural Science Foundation of China under Grant No.91738202,91438206
文摘In remote terrestrial-satellite networks, caching is a very promising technique to alleviate the burden of space cloudlet(e.g., cache-enabled satellite user terminal) and to improve subscribers' quality of experience(Qo E) in terms of buffering delay and achievable video streaming rate. In this paper, we studied a Qo E-driven caching placement optimization problem for video streaming that takes into account the required video streaming rate and the social relationship among users. Social ties between users are used to designate a set of helpers with caching capability, which can cache popular files proactively when the cloudlet is idle. We model the utility function of Qo E as a logarithmic function. Then, the caching placement problem is formulated as an optimization problem to maximize the user's average Qo E subject to the storage capacity constraints of the helpers and the cloudlets. Furthermore, we reformulate the problem into a monotone submodular optimization problem with a partition matroid constraint, and an efficient greedy algorithm with 1-1 e approximation ratio is proposed to solve it. Simulation results show that the proposed caching placement approach significantly outperforms the traditional approaches in terms of Qo E, while yields about the same delay and hit ratio performance compare to the delay-minimized scheme.
基金supported by the National Key Research and Development Program of China under Grant 2020YFB1807700the National Natural Science Foundation of China(NSFC)under Grant(No.62201414,62201432)+2 种基金the Qinchuangyuan Project(OCYRCXM-2022-362)the Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University under Grant YJSJ24017the Guangzhou Science and Technology Program under Grant 202201011732。
文摘With the explosive growth of highdefinition video streaming data,a substantial increase in network traffic has ensued.The emergency of mobile edge caching(MEC)can not only alleviate the burden on core network,but also significantly improve user experience.Integrating with the MEC and satellite networks,the network is empowered popular content ubiquitously and seamlessly.Addressing the research gap between multilayer satellite networks and MEC,we study the caching placement problem in this paper.Initially,we introduce a three-layer distributed network caching management architecture designed for efficient and flexible handling of large-scale networks.Considering the constraint on satellite capacity and content propagation delay,the cache placement problem is then formulated and transformed into a markov decision process(MDP),where the content coded caching mechanism is utilized to promote the efficiency of content delivery.Furthermore,a new generic metric,content delivery cost,is proposed to elaborate the performance of caching decision in large-scale networks.Then,we introduce a graph convolutional network(GCN)-based multi-agent advantage actor-critic(A2C)algorithm to optimize the caching decision.Finally,extensive simulations are conducted to evaluate the proposed algorithm in terms of content delivery cost and transferability.
基金the National Natural Science Foundation of China(Nos.U21A20444 and 61901044)Young Elite Scientist Sponsorship Program by China Institute of Communications。
文摘Non-orthogonal multiple access(NOMA)based fog radio access networks(F-RANs)offer high spectrum efficiency,ultra-low delay,and huge network throughput,and this is made possible by edge computing and communication functions of the fog access points(F-APs).Meanwhile,caching-enabled F-APs are responsible for edge caching and delivery of a large volume of multimedia files during the caching phase,which facilitates further reduction in the transmission energy and burden.The need of the prevailing situation in industry is that in NOMA-based F-RANs,energy-efficient resource allocation,which consists of cache placement(CP)and radio resource allocation(RRA),is crucial for network performance enhancement.To this end,in this paper,we first characterize an NOMA-based F-RAN in which F-APs of caching capabilities underlaid with the radio remote heads serve user equipments via the NOMA protocol.Then,we formulate a resource allocation problem for maximizing the defined performance indicator,namely network profit,which takes caching cost,revenue,and energy efficiency into consideration.The NP-hard problem is decomposed into two sub-problems,namely the CP sub-problem and RRA sub-problem.Finally,we propose an iterative method and a Stackelberg game based method to solve them,and numerical results show that the proposed solution can significantly improve network profit compared to some existing schemes in NOMA-based F-RANs.
基金This work was supported in part by National Natural Science Foundation of China(Nos.61771368 and 61671347)the Young Elite Scientists Sponsorship Program by CAST(No.2016QNRC001)+1 种基金the Youth Talent Support Fund of Science and Technology of Shaanxi Province(No.2018KJXX-025)Part of this work has been accepted by the IEEE Conference on Computer Communications Workshops(INFOCOM Workshop on Intelligent Wireless Emergency Communications Networks),Toronto,Canada,2020[1].
文摘Along with natural disasters,the destruction of communication infrastructures leads to the congestion or failure of communication networks.Unmanned aerial vehicles(UAVs),which are with a high flexibility,can be employed as temporary base stations to establish emergency networks.To relieve the backhaul burden of UAVs,some imperative contents can be cached by terrestrial cache-enabled rescuers(CERs)and provide for victims with device-to-device(D2D)transmissions.To support the effectiveness and timeliness of emergency communication,the delay-bounded quality-of-service(QoS)requirement and network throughput are desired to be comprehensively considered,which imposes a new challenge for caching placement and CER deployment.In this paper,we focus on joint caching placement and CER deployment to maximize the effective capacity subject to delay-bounded QoS requirement.The overall non-convex problem is transformed into the caching placement and the CER deployment sub-problems.Then,we develop the QoS-aware caching placement scheme with fixed CER deployment density and obtain the QoS-aware CER deployment density with fixed caching placement.Based on the block-coordinate descent method,we also propose the joint caching placement and CER deployment scheme,which can not only effectively enhance average effective capacity but also guarantee the delay-bounded QoS requirement.Also,numerical simulations are conducted to show the performances of the proposed schemes.
