With the rapid development of lunar exploration,a large amount of scientific data and media stream service needs to be transmitted through Lunar Space Communication Networks(LSCNs).Due to limited transmitter power and...With the rapid development of lunar exploration,a large amount of scientific data and media stream service needs to be transmitted through Lunar Space Communication Networks(LSCNs).Due to limited transmitter power and intermittent,long delay and packet loss connections,the reliable and efficient multi-priority services’transmission in LSCNs becomes an urgent problem.Firstly,we propose a Streaming Transmission Model(STM)based on temporal and spatial topology graph to describe the delay and energy consumption for data transmission in LSCNs.Then,we further devise a Coded Forward Scheme based on STM,termed CFS-STM,to achieve multi-priority service in two steps:i).Link Stability Function(LSF)is established by solving an optimization problem to choose the appropriate single-hop path.ii).Raptor code is employed to further save delay and energy with adjustable code-rate according to the different channel conditions.Experiment results show that,CFS-STM can significantly improve the transmission efficiency of multi-service priority streaming delivery in LSCNs.展开更多
Application layer multicast （ALM） has been widely applied in Internet, as a substitute for IP multicast. However, it causes network load to increase because it adopts unlcast in data transmission, which limits the a...Application layer multicast （ALM） has been widely applied in Internet, as a substitute for IP multicast. However, it causes network load to increase because it adopts unlcast in data transmission, which limits the application. In this article, in order to improve the ALM performance in P2P-SIP network, an ALM model was proposed which reduced network load via merging messages in concast mode. Finally network simulations prove that this model has better benefit on single node load and average network load. Therefore, it is suitable for streaming media service in P2P-SIP Network.展开更多
The integration of cloud and IoT edge devices is of significance in reducing the latency of IoT stream data processing by moving services closer to the edge-end.In this connection,a key issue is to determine when and ...The integration of cloud and IoT edge devices is of significance in reducing the latency of IoT stream data processing by moving services closer to the edge-end.In this connection,a key issue is to determine when and where services should be deployed.Common service deployment strategies used to be static based on the rules defined at the design time.However,dynamically changing IoT environments bring about unexpected situations such as out-of-range stream fluctuation,where the static service deployment solutions are not efficient.In this paper,we propose a dynamic service deployment mechanism based on the prediction of upcoming stream data.To effectively predict upcoming workloads,we combine the online machine learning methods with an online optimization algorithm for service deployment.A simulation-based evaluation demonstrates that,compared with those state-of-the art approaches,the approach proposed in this paper has a lower latency of stream processing.展开更多
Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of A...Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of ABR streaming in various aspects,including operational cost,streaming delays,Quality of Experience(QoE),etc.Therefore,the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming services.These problems become more worthy of investigation with the emergence of the edge-cloud continuum,which makes the resource allocation for video transcoding more complicated.To this end,this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming,including designing a rate profile for video transcoding,providing resources for video transcoding in clouds,and caching multi-bitrate video contents in networks,etc.We analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service(QoS)optimization problems.The goal is to minimize resource consumption while guaranteeing the QoS for ABR streaming.We also discuss some promising research directions for the ABR streaming services.展开更多
The 3rd generation partnership project (3GPP) has defined the protocols and codecs for implementing media streaming services over packet-switched 3G mobile networks. The specification is based on IETF RFCs on audio/vi...The 3rd generation partnership project (3GPP) has defined the protocols and codecs for implementing media streaming services over packet-switched 3G mobile networks. The specification is based on IETF RFCs on audio/video transport.It also adds new features to achieve better adaptation to the mobile network environment. In this paper, we propose an algorithm for handover detection and fast buffer refill that is based on the existing feedback and signaling mechanisms. The proposed algorithm refills the receiver buffer at a faster pace during a limited time frame after a hard handover is detected in order to achieve higher video quality.展开更多
Although Video-On-Demand (VOD) has been in existence for years, its cross-platform applicability in cloud service environments is still in increasing need. In this paper, an Adaptive Video-On-Demand (AVOD) framework t...Although Video-On-Demand (VOD) has been in existence for years, its cross-platform applicability in cloud service environments is still in increasing need. In this paper, an Adaptive Video-On-Demand (AVOD) framework that is suitable for private cloud environments is proposed. Private cloud has the key advantage of satisfying the real need of both consumers and providers. Hence, demands such as reasonable benefits for provider and high quality for consumers are essential design considerations in this framework. The difficulty is that these two factors are always high in one end and low in the other, and hard to find a delicate balance. Cloud service could be an opportunity for the multimedia providers to obtain higher benefits and cost less for the consumers but with an even better quality in service. An adaptive framework for such a cloud service environment is proposed to resolve this problem. Some interesting phenomena are observed from the experimental results including CPU utilization, data reading and writing speed, memory usage, port configuration execution time, and bandwidth.展开更多
The object-based scalable coding in MPEG-4 is investigated, and a prioritized transmission scheme of MPEG-4 audio-visual objects （AVOs） over the DiffServ network with the QoS guarantee is proposed. MPEG-4 AVOs are e...The object-based scalable coding in MPEG-4 is investigated, and a prioritized transmission scheme of MPEG-4 audio-visual objects （AVOs） over the DiffServ network with the QoS guarantee is proposed. MPEG-4 AVOs are extracted and classified into different groups according to their priority values and scalable layers （visual importance）. These priority values are mapped to the 1P DiffServ per hop behaviors （PHB）. This scheme can selectively discard packets with low importance, in order to avoid the network congestion. Simulation results show that the quality of received video can gracefully adapt to network state, as compared with the ‘best-effort＇ manner. Also, by allowing the content provider to define prioritization of each audio-visual object, the adaptive transmission of object-based scalable video can be customized based on the content.展开更多
The CES 2024(International Consumer Electronics Show)was held this January in Las Vegas,USA.Newegg Commerce,Inc.,a global well-known e-commerce platform for science and technology companies,officially collaborated wit...The CES 2024(International Consumer Electronics Show)was held this January in Las Vegas,USA.Newegg Commerce,Inc.,a global well-known e-commerce platform for science and technology companies,officially collaborated with TikTok to report at the CES 2024 and introduced new representative products from high-quality Chinese tech brands to both on-site visitors and online followers via TikTok’s live streaming service,helping these tech products attract a lot of fans.展开更多
基金supported by the National Natural Sciences Foundation of China under Grant 61701136,Grant 61831008,and Grant 61525103Guangdong Science and Technology Planning Project Grant 2018B030322004the project“Verification Platform of Multi-tier Coverage Communication Network for Oceans(LZC0020)”。
文摘With the rapid development of lunar exploration,a large amount of scientific data and media stream service needs to be transmitted through Lunar Space Communication Networks(LSCNs).Due to limited transmitter power and intermittent,long delay and packet loss connections,the reliable and efficient multi-priority services’transmission in LSCNs becomes an urgent problem.Firstly,we propose a Streaming Transmission Model(STM)based on temporal and spatial topology graph to describe the delay and energy consumption for data transmission in LSCNs.Then,we further devise a Coded Forward Scheme based on STM,termed CFS-STM,to achieve multi-priority service in two steps:i).Link Stability Function(LSF)is established by solving an optimization problem to choose the appropriate single-hop path.ii).Raptor code is employed to further save delay and energy with adjustable code-rate according to the different channel conditions.Experiment results show that,CFS-STM can significantly improve the transmission efficiency of multi-service priority streaming delivery in LSCNs.
基金National Natural Science Foundation of China ( No. 71171045 ) Fundamental Research Funds for the Central Universities,China ( No. 11D10413,No. 11D10417,No. 12D10416 ) Donghua University Research Foundation for Young Teacher,China ( No. 104-10-0044010 )
文摘Application layer multicast （ALM） has been widely applied in Internet, as a substitute for IP multicast. However, it causes network load to increase because it adopts unlcast in data transmission, which limits the application. In this article, in order to improve the ALM performance in P2P-SIP network, an ALM model was proposed which reduced network load via merging messages in concast mode. Finally network simulations prove that this model has better benefit on single node load and average network load. Therefore, it is suitable for streaming media service in P2P-SIP Network.
基金supported by the General Program of National Natural Science Fouddation of China:Analytical Method Reserach of Loop and Recursion(No.61872262/F020106)the Key Project of the National Natural Science Foundation of China:Research on Big Service Theory and Methods in Big Data Environment(No.61832004).
文摘The integration of cloud and IoT edge devices is of significance in reducing the latency of IoT stream data processing by moving services closer to the edge-end.In this connection,a key issue is to determine when and where services should be deployed.Common service deployment strategies used to be static based on the rules defined at the design time.However,dynamically changing IoT environments bring about unexpected situations such as out-of-range stream fluctuation,where the static service deployment solutions are not efficient.In this paper,we propose a dynamic service deployment mechanism based on the prediction of upcoming stream data.To effectively predict upcoming workloads,we combine the online machine learning methods with an online optimization algorithm for service deployment.A simulation-based evaluation demonstrates that,compared with those state-of-the art approaches,the approach proposed in this paper has a lower latency of stream processing.
基金supported in part by the Natural Science Foundation of Jiangsu Province under Grant BK20200486.
文摘Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of ABR streaming in various aspects,including operational cost,streaming delays,Quality of Experience(QoE),etc.Therefore,the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming services.These problems become more worthy of investigation with the emergence of the edge-cloud continuum,which makes the resource allocation for video transcoding more complicated.To this end,this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming,including designing a rate profile for video transcoding,providing resources for video transcoding in clouds,and caching multi-bitrate video contents in networks,etc.We analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service(QoS)optimization problems.The goal is to minimize resource consumption while guaranteeing the QoS for ABR streaming.We also discuss some promising research directions for the ABR streaming services.
文摘The 3rd generation partnership project (3GPP) has defined the protocols and codecs for implementing media streaming services over packet-switched 3G mobile networks. The specification is based on IETF RFCs on audio/video transport.It also adds new features to achieve better adaptation to the mobile network environment. In this paper, we propose an algorithm for handover detection and fast buffer refill that is based on the existing feedback and signaling mechanisms. The proposed algorithm refills the receiver buffer at a faster pace during a limited time frame after a hard handover is detected in order to achieve higher video quality.
文摘Although Video-On-Demand (VOD) has been in existence for years, its cross-platform applicability in cloud service environments is still in increasing need. In this paper, an Adaptive Video-On-Demand (AVOD) framework that is suitable for private cloud environments is proposed. Private cloud has the key advantage of satisfying the real need of both consumers and providers. Hence, demands such as reasonable benefits for provider and high quality for consumers are essential design considerations in this framework. The difficulty is that these two factors are always high in one end and low in the other, and hard to find a delicate balance. Cloud service could be an opportunity for the multimedia providers to obtain higher benefits and cost less for the consumers but with an even better quality in service. An adaptive framework for such a cloud service environment is proposed to resolve this problem. Some interesting phenomena are observed from the experimental results including CPU utilization, data reading and writing speed, memory usage, port configuration execution time, and bandwidth.
文摘The object-based scalable coding in MPEG-4 is investigated, and a prioritized transmission scheme of MPEG-4 audio-visual objects （AVOs） over the DiffServ network with the QoS guarantee is proposed. MPEG-4 AVOs are extracted and classified into different groups according to their priority values and scalable layers （visual importance）. These priority values are mapped to the 1P DiffServ per hop behaviors （PHB）. This scheme can selectively discard packets with low importance, in order to avoid the network congestion. Simulation results show that the quality of received video can gracefully adapt to network state, as compared with the ‘best-effort＇ manner. Also, by allowing the content provider to define prioritization of each audio-visual object, the adaptive transmission of object-based scalable video can be customized based on the content.
文摘The CES 2024(International Consumer Electronics Show)was held this January in Las Vegas,USA.Newegg Commerce,Inc.,a global well-known e-commerce platform for science and technology companies,officially collaborated with TikTok to report at the CES 2024 and introduced new representative products from high-quality Chinese tech brands to both on-site visitors and online followers via TikTok’s live streaming service,helping these tech products attract a lot of fans.
