This paper describes the entire process of completing a multicast streaming media server and applying it to a cellphone live streaming system. By using the RTSP protocol, the streaming media server controls the connec...This paper describes the entire process of completing a multicast streaming media server and applying it to a cellphone live streaming system. By using the RTSP protocol, the streaming media server controls the connection of video capture client, data stream reception and processing as well as playback interaction. The media server can publish real-time data from a data acquisition terminal or a historical data file in the server to the Web so that users on the network can view all the videos through a variety of terminals anytime and anywhere, without having to wait for all the data downloaded completely. The streaming media server of the system is developed based on an open-source streaming media library Live555. The developed server can run on a Windows or a Linux system. The standard RTSP/RTP protocol is used and the video media format is H264. The paper mainly introduces the design of a streaming media server, including data processing for real time, designing a data source, the implementation of multi-acquisition end and multi-player operation, RTSP interaction and RTP packaging, and the setting up of the data buffer in the server. Experiment results are given to show the effect of the system implementation.展开更多
In Peer-to-Peer(P2P) streaming systems,video data may be lost since peers can join and leave the overlay network randomly,thereby deteriorating the video playback quality.In this paper we propose a new hybrid mesh and...In Peer-to-Peer(P2P) streaming systems,video data may be lost since peers can join and leave the overlay network randomly,thereby deteriorating the video playback quality.In this paper we propose a new hybrid mesh and Distributed Hash Table(DHT) based P2P streaming system,called HQMedia,to provide high playback quality to users by maintaining high data dissemination resilience with a low overhead.In HQMedia,peers are classified into Super Peers(SP) and Common Peers(CP) according to their online time.SPs and CPs form a mesh structure,while SPs alone form a new Streaming DHT(SDHT) structure.In this hybrid architecture,we propose a joint scheduling and compensation mechanism.If any frames cannot be obtained during the scheduling phase,an SDHT-based compensation mechanism is invoked for retrieving the missing frames near the playback point.We evaluate the performance of HQMedia by both theoretical analysis and intensive simulation experiments on large-scale networks to demonstrate the effectiveness and scalability of the proposed system.Numerical results show that HQMedia significantly outperforms existing mesh-based and treebased P2P live streaming systems by improving playback quality with only less than 1% extra maintenance overhead.展开更多
Streaming audio and video content currently accounts for the majority of the Internet traffic and is typically deployed over the top of the existing infrastructure. We are facing the challenge of a plethora of media p...Streaming audio and video content currently accounts for the majority of the Internet traffic and is typically deployed over the top of the existing infrastructure. We are facing the challenge of a plethora of media players and adaptation algorithms showing different behavior but lacking a common framework for both objective and subjective evaluation of such systems. This paper aims to close this gap by proposing such a framework, describing its architecture, providing an example evaluation, and discussing open issues.展开更多
In order to solve the problem that the existing data scheduling algorithm cannot make full use of neighbors' bandwidth resources when allocating data request among several senders in the multisender based P2P stre...In order to solve the problem that the existing data scheduling algorithm cannot make full use of neighbors' bandwidth resources when allocating data request among several senders in the multisender based P2P streaming system,a peer priority based scheduling algorithm is proposed.The algorithm calculates neighbors' priority based on peers' historical service evaluation as well as how many wanted data that the neighbor has.The data request allocated to each neighbor is adjusted dynamically according to the priority when scheduling.Peers with high priority are preferred to allocate more data request.Experiment shows the algorithm can make full use of neighbors' bandwidth resources to transmit data to reduce server pressure effectively and improve system scalability.展开更多
Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view inclu...Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view including video data,peers' service capability and online stability based on locality sensitive hashing.MDOPS organizes all Live/VoD peers and the above multi-dimensional information in a one-dimensinal DHT,uses range resource information publish/search and introduces multiple load balancing methods.MDOPS maintains an additional candidate coordinating peer list with high qualified peers who own the video data the peer would possibly access currently and in future.This list could speed up the process of searching peers for data scheduling layer.Simulation experiment based on trace of real streaming system has testified that MDOPS can effectively improve the quality of search results and smooth load distribution among peers without increasing the cost of resource publish/search.展开更多
P2P streaming application must realize network address translation （NAT） traversal. To handle low success ratio of the existing NAT traversal algorithm, UPnP-STUN （UPUN） and port-mapping sample estimation （PMSE）...P2P streaming application must realize network address translation （NAT） traversal. To handle low success ratio of the existing NAT traversal algorithm, UPnP-STUN （UPUN） and port-mapping sample estimation （PMSE） algorithm are recommended in this paper. UPUN is the combination of UPnP and STUN, and PMSE utilizes port mapping samples added by symmetric NAT for different sessions to estimate regularity of port mapping of symmetric NAT, which takes advantage of the Bernoulli law of large numbers. Besides, for the situation that both peers are behind NAT, and to handle heavy relay server load when many inner peers want to communicate with each other, a peer auxiliary-relay （PAR） algorithm is presented. PAR lets outer peers with sufficient bandwidth act as relay servers to alleviate pressure of real server, which could avoid NAT traversal failure caused by single point failure of relay server. Finally, experiments show that the proposed algorithms could improve the success ratio significantly for NAT traversal in P2P streaming application as well as improve P2P streaming application applicability.展开更多
360 video streaming services over the network are becoming popular. In particular, it is easy to experience 360 video through the already popular smartphone. However, due to the nature of 360 video, it is difficult to...360 video streaming services over the network are becoming popular. In particular, it is easy to experience 360 video through the already popular smartphone. However, due to the nature of 360 video, it is difficult to provide stable streaming service in general network environment because the size of data to send is larger than that of conventional video. Also, the real user's viewing area is very small compared to the sending amount. In this paper, we propose a system that can provide high quality 360 video streaming services to the users more efficiently in the cloud. In particular, we propose a streaming system focused on using a head mount display (HMD).展开更多
With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.展开更多
The exponential expansion of the Internet of Things(IoT),Industrial Internet of Things(IIoT),and Transportation Management of Things(TMoT)produces vast amounts of real-time streaming data.Ensuring system dependability...The exponential expansion of the Internet of Things(IoT),Industrial Internet of Things(IIoT),and Transportation Management of Things(TMoT)produces vast amounts of real-time streaming data.Ensuring system dependability,operational efficiency,and security depends on the identification of anomalies in these dynamic and resource-constrained systems.Due to their high computational requirements and inability to efficiently process continuous data streams,traditional anomaly detection techniques often fail in IoT systems.This work presents a resource-efficient adaptive anomaly detection model for real-time streaming data in IoT systems.Extensive experiments were carried out on multiple real-world datasets,achieving an average accuracy score of 96.06%with an execution time close to 7.5 milliseconds for each individual streaming data point,demonstrating its potential for real-time,resourceconstrained applications.The model uses Principal Component Analysis(PCA)for dimensionality reduction and a Z-score technique for anomaly detection.It maintains a low computational footprint with a sliding window mechanism,enabling incremental data processing and identification of both transient and sustained anomalies without storing historical data.The system uses a Multivariate Linear Regression(MLR)based imputation technique that estimates missing or corrupted sensor values,preserving data integrity prior to anomaly detection.The suggested solution is appropriate for many uses in smart cities,industrial automation,environmental monitoring,IoT security,and intelligent transportation systems,and is particularly well-suited for resource-constrained edge devices.展开更多
Over the past few years,video live streaming has gained immense popularity as a leading internet application.In current solutions offered by cloud service providers,the Group of Pictures(GOP)length of the video source...Over the past few years,video live streaming has gained immense popularity as a leading internet application.In current solutions offered by cloud service providers,the Group of Pictures(GOP)length of the video source often significantly impacts end-to-end(E2E)latency.However,designing an optimized GOP structure to reduce this effect remains a significant challenge.This paper presents two key contributions.First,it explores how the GOP length at the video source influences E2E latency in mainstream cloud streaming services.Experimental results reveal that the mean E2E latency increases linearly with longer GOP lengths.Second,this paper proposes EGOP(an Enhanced GOP structure)that can be implemented in streaming media servers.Experiments demonstrate that EGOP maintains a consistent E2E latency,unaffected by the GOP length of the video source.Specifically,even with a GOP length of 10 s,the E2E latency remains at 1.35 s,achieving a reduction of 6.98 s compared to Volcano-Engine(the live streaming service provider for TikTok).This makes EGOP a promising solution for low-latency live streaming.展开更多
With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks e...With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.展开更多
No-wash bioassays based on nanoparticles are used widely in biochemical procedures because of their responsive sensing and no need forwashing processes.Essential for no-wash biosensing are the interactions between nan...No-wash bioassays based on nanoparticles are used widely in biochemical procedures because of their responsive sensing and no need forwashing processes.Essential for no-wash biosensing are the interactions between nanoparticles and biomolecules,but it is challenging toachieve controlled bioconjugation of molecules on nanomaterials.Reported here is a way to actively improve nanoparticle-based no-washbioassays by enhancing the binding between biomolecules and gold nanoparticles via acoustic streaming generated by a gigahertz piezoelectricnanoelectromechanical resonator.Tunable micro-vortices are generated at the device-liquid interface,thereby accelerating the internalcirculating flow of the solution,bypassing the diffusion limitation,and thus improving the binding between the biomolecules and goldnanoparticles.Combined with fluorescence quenching,an enhanced and ultrafast no-wash biosensing assay is realized for specific proteins.The sensing method presented here is a versatile tool for different types of biomolecule detection with high efficiency and simplicity.展开更多
In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits...In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits.Consumers now frequently rely on external sources to make well-informed purchasing decisions,leading to the emergence of live shopping as a prominent avenue for gathering product information and completing transactions.E-commerce live streaming has experienced rapid growth,leveraging its ability to generate traffic and capture consumer attention.The integration of content and live streaming not only meets users’psychological needs but also facilitates seamless communication between buyers and sellers.From the perspective of content marketing typologies,this paper examines content marketing across three key dimensions:informational content,entertainment content,and emotional content.It further explores the impact of content marketing on consumers’purchase intentions within the context of e-commerce live streaming.展开更多
Unmanned aerial vehicles(UAVs)bring more innovation and attraction to outdoor mobile high-definition(HD)live streaming with its unique perspective.Due to the heavy computational requirements of HD live broadcast tasks...Unmanned aerial vehicles(UAVs)bring more innovation and attraction to outdoor mobile high-definition(HD)live streaming with its unique perspective.Due to the heavy computational requirements of HD live broadcast tasks and the limited hardware performance of UAV equipment,how to reduce the system response delay and improve the energy efficiency of terminal equipment directly affects the secure broadcast of the system.Secure task offloading in this scenario is considered a promising solution and has received academic attention.In this paper,we simulate the UAV-aided outdoor mobile HD live streaming scenarios and optimize the relevant task offloading strategies.First,we design the total cost function of task offloading that jointly optimizes secure time latency and energy consumption.Additionally,we propose a collaborative computing model for multi-UAV task offloading.This model combines the idea of simulated annealing(SA)and introduces the compression factor to enhance the particle swarm optimization(PSO)to realize secure task offloading.The simulation results show that the proposed strategy has better performance in balancing network latency and energy consumption.Compared with the discrete teaching–learning-based optimization(DTLBO)and quantum PSO(QPSO)task offloading strategies,the fitness value of the proposed strategy is decreased by an average of 26.73%and 16.42%,respectively.展开更多
Urbanization and environmental degradation have led to significant declines in water quality and aquatic ecosystem health,highlighting the urgent need for effective restoration efforts.This study applies an integrated...Urbanization and environmental degradation have led to significant declines in water quality and aquatic ecosystem health,highlighting the urgent need for effective restoration efforts.This study applies an integrated analysis approach to estimate the economic value and benefits of improvements in water quality and aquatic ecosystem services resulting from the Ecological Stream Restoration Project.Using survey data analyzed through the choice experiment(CE)method,we assessed respondents’preferences for various ecosystem services,including water-friendly services,ecological functions,water-level control,and water-quality purification.Three empirical analysis models—the Conditional Logit Model(CLM),Nested Logit Model(NL),and Error Component Logit Model(ECL)—were applied,with the ECL model identified as the most suitable for this study.From the physical impact assessment,we derived compensating variations to estimate the annual economic benefits of the project.The estimated annual economic value of water quality improvement due to the Anyangcheon Ecological Stream Restoration Project ranged from approximately KRW 10.54 billion to KRW 21.44 billion,while the economic value of aquatic ecosystem improvement was estimated to range from KRW 6.05 billion to KRW 12.30 billion annually.This study provides analytic framework that can inform future ecological restoration projects and sustainable water management policies.展开更多
To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hyd...To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hydrogen integrated energy system(EHH-IES)optimal scheduling model considering carbon emission stream(CES)and wind-solar accommodation.First,the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate,branch carbon intensity,and node carbon potential,realizing accurate tracking of carbon flow in the process of multi-energy coupling.Second,a stepped carbon pricing mechanism is established to dynamically adjust carbon trading costs based on the deviation between actual carbon emissions and initial quotas,strengthening the emission reduction incentive.Finally,a lowcarbon economic dispatch model is constructed with the objectives of minimizing operation cost,carbon trading cost,wind-solar curtailment penalty cost,and energy loss.Simulation results show that compared with the traditional economic dispatch scheme 3,the proposed schemel reduces carbon emissions by 53.97%and wind-solar curtailment by 68.89%with a 16.10%increase in total cost.This verifies that the model can effectively improve clean energy utilization and reduce carbon emissions,achieving low-carbon economic operation of EHH-IES,with CES theory ensuring precise carbon flow tracking across multi-energy links.展开更多
The proliferation of streaming service system in various application areas gains increasing importance and also poses more challenges in the research of streaming service system. In this paper, we propose a novel dyna...The proliferation of streaming service system in various application areas gains increasing importance and also poses more challenges in the research of streaming service system. In this paper, we propose a novel dynamic model composed of a set of differential equations to describe the evolution of streaming service systems. And in the model, we focus on how the policies for admission control and peer selection influence on the system. We first introduce a flexible abstraction of streaming service systems. The abstraction is generally enough to capture the essences of streaming service systems with different structures, physical characteristics,software protocols and client behaviors. Then, by analyzing the state which is defined as the number of requests, a novel dynamic model is developed in microscopic scale to characterize the behaviors of streaming service systems. The model proposed in this paper demonstrates the interactions between clients and servers and also between different servers. The interactions are primarily influenced by the admission control policy and peer selection policy. Finally, some experiments are designed to verify the validation and reasonability of the model.展开更多
Recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,etc.The recent developments of deep learning(DL...Recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,etc.The recent developments of deep learning(DL)models find helpful in the detection and classification of anomalies.This article designs an oversampling with an optimal deep learning-based streaming data classification(OS-ODLSDC)model.The aim of the OSODLSDC model is to recognize and classify the presence of anomalies in the streaming data.The proposed OS-ODLSDC model initially undergoes preprocessing step.Since streaming data is unbalanced,support vector machine(SVM)-Synthetic Minority Over-sampling Technique(SVM-SMOTE)is applied for oversampling process.Besides,the OS-ODLSDC model employs bidirectional long short-term memory(Bi LSTM)for AD and classification.Finally,the root means square propagation(RMSProp)optimizer is applied for optimal hyperparameter tuning of the Bi LSTM model.For ensuring the promising performance of the OS-ODLSDC model,a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDS 2018,KDD-Cup 1999,and NSL-KDD datasets.展开更多
With the widespread use of streaming media application on the Internet, a significant change in Internet workload will be provoked. Caching is one of the applied techniques for enhancing the scalability of streaming s...With the widespread use of streaming media application on the Internet, a significant change in Internet workload will be provoked. Caching is one of the applied techniques for enhancing the scalability of streaming system and reducing the workload of server/network. Aiming at the characteristics of broadband network in community, we propose a popularity-based server-proxy caching strategy for streaming medias, and implement the prototype of streaming proxy caching based on this strategy, using RTSP as control protocol and RTP for content transport. This system can play a role in decreasing server load, reducing the traffic from streaming server to proxy, and improving the start-up latency of the client. Key words streaming server - proxy - cache - streaming media - real time streaming protocol CLC number TP 302 - TP 333 Foundation item: Supported by the National High Technology Development 863 Program of China (2001AA111011).Biography: Tan Jin (1962-), male, Ph. D candidate, research direction: network communications, multimedia technologies, and web caching.展开更多
文摘This paper describes the entire process of completing a multicast streaming media server and applying it to a cellphone live streaming system. By using the RTSP protocol, the streaming media server controls the connection of video capture client, data stream reception and processing as well as playback interaction. The media server can publish real-time data from a data acquisition terminal or a historical data file in the server to the Web so that users on the network can view all the videos through a variety of terminals anytime and anywhere, without having to wait for all the data downloaded completely. The streaming media server of the system is developed based on an open-source streaming media library Live555. The developed server can run on a Windows or a Linux system. The standard RTSP/RTP protocol is used and the video media format is H264. The paper mainly introduces the design of a streaming media server, including data processing for real time, designing a data source, the implementation of multi-acquisition end and multi-player operation, RTSP interaction and RTP packaging, and the setting up of the data buffer in the server. Experiment results are given to show the effect of the system implementation.
基金supported by the National Programs for Science and Technology under Grant No. 2009ZX03004-002the National Natural Science Foundation of China Major Project under Grant No. 60833002+2 种基金the National Natural Science Foundation of China under Grant No.60772142the National Science and Technology Major Projects under Grant No. 2008ZX03003-005the Science and Technology Research Project of Chongqing Education Commission under Grant No. KJ120825
文摘In Peer-to-Peer(P2P) streaming systems,video data may be lost since peers can join and leave the overlay network randomly,thereby deteriorating the video playback quality.In this paper we propose a new hybrid mesh and Distributed Hash Table(DHT) based P2P streaming system,called HQMedia,to provide high playback quality to users by maintaining high data dissemination resilience with a low overhead.In HQMedia,peers are classified into Super Peers(SP) and Common Peers(CP) according to their online time.SPs and CPs form a mesh structure,while SPs alone form a new Streaming DHT(SDHT) structure.In this hybrid architecture,we propose a joint scheduling and compensation mechanism.If any frames cannot be obtained during the scheduling phase,an SDHT-based compensation mechanism is invoked for retrieving the missing frames near the playback point.We evaluate the performance of HQMedia by both theoretical analysis and intensive simulation experiments on large-scale networks to demonstrate the effectiveness and scalability of the proposed system.Numerical results show that HQMedia significantly outperforms existing mesh-based and treebased P2P live streaming systems by improving playback quality with only less than 1% extra maintenance overhead.
基金supported in part by the Austrian Research Promotion Agency(FFG)under the next generation video streaming project "PROMETHEUS"
文摘Streaming audio and video content currently accounts for the majority of the Internet traffic and is typically deployed over the top of the existing infrastructure. We are facing the challenge of a plethora of media players and adaptation algorithms showing different behavior but lacking a common framework for both objective and subjective evaluation of such systems. This paper aims to close this gap by proposing such a framework, describing its architecture, providing an example evaluation, and discussing open issues.
基金Supported by the National High Technology Research and Development Program of China(No.2009AA01A339,2008AA01A317)the National Natural Science Foundation of China for Distinguished Young Scholars(No.60903218F0208)the Science and Technology Support Plan of China(No.2008BAH28B04)
文摘In order to solve the problem that the existing data scheduling algorithm cannot make full use of neighbors' bandwidth resources when allocating data request among several senders in the multisender based P2P streaming system,a peer priority based scheduling algorithm is proposed.The algorithm calculates neighbors' priority based on peers' historical service evaluation as well as how many wanted data that the neighbor has.The data request allocated to each neighbor is adjusted dynamically according to the priority when scheduling.Peers with high priority are preferred to allocate more data request.Experiment shows the algorithm can make full use of neighbors' bandwidth resources to transmit data to reduce server pressure effectively and improve system scalability.
基金Supported by the National High Technology Research and Development Programme of China(No.2008AA01A317)the National Natural Science Foundation of China(No.60903218)
文摘Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view including video data,peers' service capability and online stability based on locality sensitive hashing.MDOPS organizes all Live/VoD peers and the above multi-dimensional information in a one-dimensinal DHT,uses range resource information publish/search and introduces multiple load balancing methods.MDOPS maintains an additional candidate coordinating peer list with high qualified peers who own the video data the peer would possibly access currently and in future.This list could speed up the process of searching peers for data scheduling layer.Simulation experiment based on trace of real streaming system has testified that MDOPS can effectively improve the quality of search results and smooth load distribution among peers without increasing the cost of resource publish/search.
基金Supported by the Nat/onal Science and Technology Support Projects of China（No. 2008BAH28B04） and the National Natural Science Foundation of China _（No..60903218F0208） andthe National High Technology Research and Development Programme of China （No. 2008AA01A317）
文摘P2P streaming application must realize network address translation （NAT） traversal. To handle low success ratio of the existing NAT traversal algorithm, UPnP-STUN （UPUN） and port-mapping sample estimation （PMSE） algorithm are recommended in this paper. UPUN is the combination of UPnP and STUN, and PMSE utilizes port mapping samples added by symmetric NAT for different sessions to estimate regularity of port mapping of symmetric NAT, which takes advantage of the Bernoulli law of large numbers. Besides, for the situation that both peers are behind NAT, and to handle heavy relay server load when many inner peers want to communicate with each other, a peer auxiliary-relay （PAR） algorithm is presented. PAR lets outer peers with sufficient bandwidth act as relay servers to alleviate pressure of real server, which could avoid NAT traversal failure caused by single point failure of relay server. Finally, experiments show that the proposed algorithms could improve the success ratio significantly for NAT traversal in P2P streaming application as well as improve P2P streaming application applicability.
文摘360 video streaming services over the network are becoming popular. In particular, it is easy to experience 360 video through the already popular smartphone. However, due to the nature of 360 video, it is difficult to provide stable streaming service in general network environment because the size of data to send is larger than that of conventional video. Also, the real user's viewing area is very small compared to the sending amount. In this paper, we propose a system that can provide high quality 360 video streaming services to the users more efficiently in the cloud. In particular, we propose a streaming system focused on using a head mount display (HMD).
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
基金funded by the Ongoing Research Funding Program(ORF-2025-890)King Saud University,Riyadh,Saudi Arabia and was supported by the Competitive Research Fund of theUniversity of Aizu,Japan.
文摘The exponential expansion of the Internet of Things(IoT),Industrial Internet of Things(IIoT),and Transportation Management of Things(TMoT)produces vast amounts of real-time streaming data.Ensuring system dependability,operational efficiency,and security depends on the identification of anomalies in these dynamic and resource-constrained systems.Due to their high computational requirements and inability to efficiently process continuous data streams,traditional anomaly detection techniques often fail in IoT systems.This work presents a resource-efficient adaptive anomaly detection model for real-time streaming data in IoT systems.Extensive experiments were carried out on multiple real-world datasets,achieving an average accuracy score of 96.06%with an execution time close to 7.5 milliseconds for each individual streaming data point,demonstrating its potential for real-time,resourceconstrained applications.The model uses Principal Component Analysis(PCA)for dimensionality reduction and a Z-score technique for anomaly detection.It maintains a low computational footprint with a sliding window mechanism,enabling incremental data processing and identification of both transient and sustained anomalies without storing historical data.The system uses a Multivariate Linear Regression(MLR)based imputation technique that estimates missing or corrupted sensor values,preserving data integrity prior to anomaly detection.The suggested solution is appropriate for many uses in smart cities,industrial automation,environmental monitoring,IoT security,and intelligent transportation systems,and is particularly well-suited for resource-constrained edge devices.
基金supported by Henan Province Major Science and Technology Project(241100210100).
文摘Over the past few years,video live streaming has gained immense popularity as a leading internet application.In current solutions offered by cloud service providers,the Group of Pictures(GOP)length of the video source often significantly impacts end-to-end(E2E)latency.However,designing an optimized GOP structure to reduce this effect remains a significant challenge.This paper presents two key contributions.First,it explores how the GOP length at the video source influences E2E latency in mainstream cloud streaming services.Experimental results reveal that the mean E2E latency increases linearly with longer GOP lengths.Second,this paper proposes EGOP(an Enhanced GOP structure)that can be implemented in streaming media servers.Experiments demonstrate that EGOP maintains a consistent E2E latency,unaffected by the GOP length of the video source.Specifically,even with a GOP length of 10 s,the E2E latency remains at 1.35 s,achieving a reduction of 6.98 s compared to Volcano-Engine(the live streaming service provider for TikTok).This makes EGOP a promising solution for low-latency live streaming.
基金substantially supported by the National Natural Science Foundation of China under Grant No.62002263in part by Tianjin Municipal Education Commission Research Program Project under 2022KJ012Tianjin Science and Technology Program Projects:24YDTPJC00630.
文摘With technological advancements,high-speed rail has emerged as a prevalent mode of transportation.During travel,passengers exhibit a growing demand for streaming media services.However,the high-speed mobile networks environment poses challenges,including frequent base station handoffs,which significantly degrade wireless network transmission performance.Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers’media experiences are key research priorities.To address these issues,we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness(ACOTM-EA)tailored for high-speed rail streaming media.Within this framework,we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes.Additionally,we introduce a proactive base station handoffstrategy to minimize handoffrelated disruptions and optimize resource distribution across adjacent base stations.Moreover,this study presents a wireless resource allocation approach based on an enhanced genetic algorithm,coupled with an adaptive bitrate selection mechanism,to maximize passenger Quality of Experience(QoE).To evaluate the proposed method,we designed a simulation experiment and compared ACOTM-EA with established algorithms.Results indicate that ACOTM-EA improves throughput by 11%and enhances passengers’media experience by 5%.
基金the financial support received from the National Natural Science Foundation of China(Grant No.62174119)the 111 Project (Grant No.B07014)the Foundation for Talent Scientists of Nanchang Institute for Microtechnology of Tianjin University
文摘No-wash bioassays based on nanoparticles are used widely in biochemical procedures because of their responsive sensing and no need forwashing processes.Essential for no-wash biosensing are the interactions between nanoparticles and biomolecules,but it is challenging toachieve controlled bioconjugation of molecules on nanomaterials.Reported here is a way to actively improve nanoparticle-based no-washbioassays by enhancing the binding between biomolecules and gold nanoparticles via acoustic streaming generated by a gigahertz piezoelectricnanoelectromechanical resonator.Tunable micro-vortices are generated at the device-liquid interface,thereby accelerating the internalcirculating flow of the solution,bypassing the diffusion limitation,and thus improving the binding between the biomolecules and goldnanoparticles.Combined with fluorescence quenching,an enhanced and ultrafast no-wash biosensing assay is realized for specific proteins.The sensing method presented here is a versatile tool for different types of biomolecule detection with high efficiency and simplicity.
文摘In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits.Consumers now frequently rely on external sources to make well-informed purchasing decisions,leading to the emergence of live shopping as a prominent avenue for gathering product information and completing transactions.E-commerce live streaming has experienced rapid growth,leveraging its ability to generate traffic and capture consumer attention.The integration of content and live streaming not only meets users’psychological needs but also facilitates seamless communication between buyers and sellers.From the perspective of content marketing typologies,this paper examines content marketing across three key dimensions:informational content,entertainment content,and emotional content.It further explores the impact of content marketing on consumers’purchase intentions within the context of e-commerce live streaming.
基金supported in part by the National Natural Science Foundation of China(Nos.62271454 and 62171119).
文摘Unmanned aerial vehicles(UAVs)bring more innovation and attraction to outdoor mobile high-definition(HD)live streaming with its unique perspective.Due to the heavy computational requirements of HD live broadcast tasks and the limited hardware performance of UAV equipment,how to reduce the system response delay and improve the energy efficiency of terminal equipment directly affects the secure broadcast of the system.Secure task offloading in this scenario is considered a promising solution and has received academic attention.In this paper,we simulate the UAV-aided outdoor mobile HD live streaming scenarios and optimize the relevant task offloading strategies.First,we design the total cost function of task offloading that jointly optimizes secure time latency and energy consumption.Additionally,we propose a collaborative computing model for multi-UAV task offloading.This model combines the idea of simulated annealing(SA)and introduces the compression factor to enhance the particle swarm optimization(PSO)to realize secure task offloading.The simulation results show that the proposed strategy has better performance in balancing network latency and energy consumption.Compared with the discrete teaching–learning-based optimization(DTLBO)and quantum PSO(QPSO)task offloading strategies,the fitness value of the proposed strategy is decreased by an average of 26.73%and 16.42%,respectively.
基金funded by Korea Environmental Industry&Technology Institute(KEITI)through Wetland Ecosystem Value Evaluation and Carbon Absorption Value Promotion Technology Development Project of Korea Ministry of Environment(MOE)(RS-2022-KE002025).
文摘Urbanization and environmental degradation have led to significant declines in water quality and aquatic ecosystem health,highlighting the urgent need for effective restoration efforts.This study applies an integrated analysis approach to estimate the economic value and benefits of improvements in water quality and aquatic ecosystem services resulting from the Ecological Stream Restoration Project.Using survey data analyzed through the choice experiment(CE)method,we assessed respondents’preferences for various ecosystem services,including water-friendly services,ecological functions,water-level control,and water-quality purification.Three empirical analysis models—the Conditional Logit Model(CLM),Nested Logit Model(NL),and Error Component Logit Model(ECL)—were applied,with the ECL model identified as the most suitable for this study.From the physical impact assessment,we derived compensating variations to estimate the annual economic benefits of the project.The estimated annual economic value of water quality improvement due to the Anyangcheon Ecological Stream Restoration Project ranged from approximately KRW 10.54 billion to KRW 21.44 billion,while the economic value of aquatic ecosystem improvement was estimated to range from KRW 6.05 billion to KRW 12.30 billion annually.This study provides analytic framework that can inform future ecological restoration projects and sustainable water management policies.
文摘To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hydrogen integrated energy system(EHH-IES)optimal scheduling model considering carbon emission stream(CES)and wind-solar accommodation.First,the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate,branch carbon intensity,and node carbon potential,realizing accurate tracking of carbon flow in the process of multi-energy coupling.Second,a stepped carbon pricing mechanism is established to dynamically adjust carbon trading costs based on the deviation between actual carbon emissions and initial quotas,strengthening the emission reduction incentive.Finally,a lowcarbon economic dispatch model is constructed with the objectives of minimizing operation cost,carbon trading cost,wind-solar curtailment penalty cost,and energy loss.Simulation results show that compared with the traditional economic dispatch scheme 3,the proposed schemel reduces carbon emissions by 53.97%and wind-solar curtailment by 68.89%with a 16.10%increase in total cost.This verifies that the model can effectively improve clean energy utilization and reduce carbon emissions,achieving low-carbon economic operation of EHH-IES,with CES theory ensuring precise carbon flow tracking across multi-energy links.
基金supported by National Natural Science Foundationof China(Nos.61174124 and 61233003)Research Fund for DoctoralProgram of Higher Education of China(No.20123402110029)Natural Science Research Program of the Anhui High Education Bureau of China(No.KJ2012A286)
文摘The proliferation of streaming service system in various application areas gains increasing importance and also poses more challenges in the research of streaming service system. In this paper, we propose a novel dynamic model composed of a set of differential equations to describe the evolution of streaming service systems. And in the model, we focus on how the policies for admission control and peer selection influence on the system. We first introduce a flexible abstraction of streaming service systems. The abstraction is generally enough to capture the essences of streaming service systems with different structures, physical characteristics,software protocols and client behaviors. Then, by analyzing the state which is defined as the number of requests, a novel dynamic model is developed in microscopic scale to characterize the behaviors of streaming service systems. The model proposed in this paper demonstrates the interactions between clients and servers and also between different servers. The interactions are primarily influenced by the admission control policy and peer selection policy. Finally, some experiments are designed to verify the validation and reasonability of the model.
文摘Recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,etc.The recent developments of deep learning(DL)models find helpful in the detection and classification of anomalies.This article designs an oversampling with an optimal deep learning-based streaming data classification(OS-ODLSDC)model.The aim of the OSODLSDC model is to recognize and classify the presence of anomalies in the streaming data.The proposed OS-ODLSDC model initially undergoes preprocessing step.Since streaming data is unbalanced,support vector machine(SVM)-Synthetic Minority Over-sampling Technique(SVM-SMOTE)is applied for oversampling process.Besides,the OS-ODLSDC model employs bidirectional long short-term memory(Bi LSTM)for AD and classification.Finally,the root means square propagation(RMSProp)optimizer is applied for optimal hyperparameter tuning of the Bi LSTM model.For ensuring the promising performance of the OS-ODLSDC model,a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDS 2018,KDD-Cup 1999,and NSL-KDD datasets.
文摘With the widespread use of streaming media application on the Internet, a significant change in Internet workload will be provoked. Caching is one of the applied techniques for enhancing the scalability of streaming system and reducing the workload of server/network. Aiming at the characteristics of broadband network in community, we propose a popularity-based server-proxy caching strategy for streaming medias, and implement the prototype of streaming proxy caching based on this strategy, using RTSP as control protocol and RTP for content transport. This system can play a role in decreasing server load, reducing the traffic from streaming server to proxy, and improving the start-up latency of the client. Key words streaming server - proxy - cache - streaming media - real time streaming protocol CLC number TP 302 - TP 333 Foundation item: Supported by the National High Technology Development 863 Program of China (2001AA111011).Biography: Tan Jin (1962-), male, Ph. D candidate, research direction: network communications, multimedia technologies, and web caching.
