Qingmin Jia - Academia.edu (original) (raw)

Papers by Qingmin Jia

IEEE transactions on big data, 2024

IEEE internet of things journal, 2024

IEEE access, 2024

Scalable Video Coding (SVC) and edge caching are two techniques that hold the potential to improv... more Scalable Video Coding (SVC) and edge caching are two techniques that hold the potential to improve user-perceived video viewing experience. Moreover, video recommendation can further enhance the caching gain by reshaping users' video preferences. In this paper, we investigate the video caching, recommendation and transmission for layered SVC streaming in cache-enabled cellular networks. Considering the dynamic characteristics of video popularity distribution and wireless network environment, to improve energy efficiency by minimizing system energy consumption and ensure the average user preference deviation tolerance, we begin by formulating a long-term optimization problem that focuses on video caching, recommendation and user association (UA). The problem is then transformed into a Markov decision process (MDP), which is solved by designing a dueling deep Q-learning network (DDQN)based algorithm. Using this algorithm, we can obtain the optimal video caching, recommendation and UA solutions. Since the action space of the MDP is huge, to cope with the "curse of dimensionality", linear approximation is integrated into the designed algorithm. Finally, the proposed algorithm's convergence and effectiveness in reducing long-term system energy consumption are demonstrated through extensive simulations. INDEX TERMS Scalable video coding; edge caching; recommendation; user association; energy efficiency; dueling deep Q-learning.

arXiv (Cornell University), Feb 4, 2024

The emergence of intelligent applications and recent advances in the fields of computing and netw... more The emergence of intelligent applications and recent advances in the fields of computing and networks are driving the development of computing and networks convergence (CNC) system. However, existing researches failed to achieve comprehensive scheduling optimization of computing and network resources. This shortfall results in some requirements of computing requests unable to be guaranteed in an end-to-end service pattern, negatively impacting the development of CNC systems. In this article, we propose a distributed cooperative routing framework for the CNC system to ensure the deadline requirements and minimize the computation cost of requests. The framework includes trading plane, management plane, control plane and forwarding plane. The cross-plane cooperative end-to-end routing schemes consider both computation efficiency of heterogeneous servers and the network congestion degrees while making routing plan, thereby determining where to execute requests and corresponding routing paths. Simulations results substantiates the performance of our routing schemes in scheduling computing requests in the CNC system.

arXiv (Cornell University), Jan 31, 2024

With the development of new Internet services such as computation-intensive and delay-sensitive t... more With the development of new Internet services such as computation-intensive and delay-sensitive tasks, the traditional "Best Effort" network transmission mode has been greatly challenged. The network system is urgently required to provide endto-end transmission determinacy and computing determinacy for new applications to ensure the safe and efficient operation of services. Based on the research of the convergence of computing and networking, a new network paradigm named deterministic computing power networking (Det-CPN) is proposed. In this article, we firstly introduce the research advance of computing power networking. And then the motivations and scenarios of Det-CPN are analyzed. Following that, we present the system architecture, technological capabilities, workflow as well as key technologies for Det-CPN. Finally, the challenges and future trends of Det-CPN are analyzed and discussed.

arXiv (Cornell University), Dec 1, 2023

The fiercely competitive business environment and increasingly personalized customization needs a... more The fiercely competitive business environment and increasingly personalized customization needs are driving the digital transformation and upgrading of the manufacturing industry. IIoT intelligence, which can provide innovative and efficient solutions for various aspects of the manufacturing value chain, illuminates the path of transformation for the manufacturing industry. It's time to provide a systematic vision of IIoT intelligence. However, existing surveys often focus on specific areas of IIoT intelligence, leading researchers and readers to have biases in their understanding of IIoT intelligence, that is, believing that research in one direction is the most important for the development of IIoT intelligence, while ignoring contributions from other directions. Therefore, this paper provides a comprehensive overview of IIoT intelligence. We first conduct an in-depth analysis of the inevitability of manufacturing transformation and study the successful experiences from the practices of Chinese enterprises. Then we give our definition of IIoT intelligence and demonstrate the value of IIoT intelligence for industries in fucntions, operations, deployments, and application. Afterwards, we propose a hierarchical development architecture for IIoT intelligence, which consists of five layers. The practical values of technical upgrades at each layer are illustrated by a close look on lighthouse factories. Following that, we identify seven kinds of technologies that accelerate the transformation of manufacturing, and clarify their contributions. The ethical implications and environmental impacts of adopting IIoT intelligence in manufacturing are analyzed as well. Finally, we explore the open challenges and development trends from four aspects to inspire future researches.

IEEE Transactions on Vehicular Technology

IEEE Access, 2017

With the explosive growth of Internet traffic and the rapid development of network technology, co... more With the explosive growth of Internet traffic and the rapid development of network technology, content delivery has become a significant service in the current Internet. However, the existing content delivery solutions, such as peer-to-peer and content delivery network, have many insufficient aspects. Meanwhile, the collaboration between content delivery and network infrastructures has been considered as a promising technique in network field. From the perspective of collaboration, content delivery systems can make full use of the network characteristics and the effective information provided by the network operators, so as to improve the efficiency of the content distribution and optimize the overall performance of the network. In this paper, we present a comprehensive survey on the collaboration for content delivery and network infrastructures. First, we provide some of the works, which have been done on collaboration solutions from two perspectives: evolutionary and revolutionary. And then, the advantages and disadvantages of these solutions are compared and analyzed from three aspects of technology, business, and standardization. Finally, we outline some challenges and research directions in the future.

Proceedings of the 28th Annual International Conference on Mobile Computing And Networking, Oct 14, 2022

In this paper, we present NestFL, a learning-efficient FL framework for edge computing, which can... more In this paper, we present NestFL, a learning-efficient FL framework for edge computing, which can jointly improve the training efficiency and achieve personalization. Specifically, NestFL takes the runtime resources of the edge devices into consideration and assigns each device a sparsestructured subnetwork by progressively performing the structured pruning. During training, only the updates of these subnetworks are transmitted to the central server. Additionally, these generated subnetworks adopt a structure-and parameter-sharing mechanism, making themselves nested inside a multi-capacity global model. In doing so, the overall communication and computation costs can be significantly reduced, and each device can learn a personalized model without introducing extra parameters. Furthermore, a weighted aggregation mechanism is designed to improve the training performance and maximally preserve personalization.

China Communications, Jul 1, 2019

With the new promising technique of mobile edge computing (MEC) emerging, by utilizing the edge c... more With the new promising technique of mobile edge computing (MEC) emerging, by utilizing the edge computing and cloud computing capabilities to realize the HTTP adaptive video streaming transmission in MEC-based 5G networks has been widely studied. Although many works have been done, most of the existing works focus on the issues of network resource utilization or the quality of experience (QoE) promotion, while the energy efficiency is largely ignored. In this paper, different from previous works, in order to realize the energy efficiency for video transmission in MEC-enhanced 5G networks, we propose a joint caching and transcoding schedule strategy for HTTP adaptive video streaming transmission by taking the caching and transcoding into consideration. We formulate the problem of energy-efficient joint caching and transcoding as an integer programming problem to minimize the system energy consumption. Due to solving the optimization problem brings huge computation complexity, therefore, to make the optimization problem tractable, a heuristic algorithm based on simulated annealing algorithm is proposed to iteratively reach the global optimum solution with a lower complexity and higher accuracy. Finally, numerical simulation results are illustrated to demonstrated that our proposed scheme brings an excellent performance.

Coded caching and cooperative caching have been considered as two promising technologies in heter... more Coded caching and cooperative caching have been considered as two promising technologies in heterogeneous small cell networks. Although some works have been done for coded caching and cooperative caching in heterogeneous small cell networks, to the best of our knowledge, these two important issues have traditionally been addressed separately. However, it is necessary to jointly consider these two significant issues to reduce the backhaul rate and improve content delivery as well as the Quality of Experience (QoE) of end-users. Moreover, the energy efficiency issue for content caching and content delivery is also extremely significant but excessively negligent. In this paper, we jointly consider the coded caching and cooperative caching issues, and propose a cooperative coded caching scheme to improve the content delivery efficiency and enhance the QoE for end-users. And then, based on the proposed scheme, we establish an energy consumption model from the perspective of content caching and content delivery to optimize the energy efficiency. In addition, we propose a greedy-based algorithm to solve this energy efficiency issue by optimizing the caching placement. Finally, simulation results show the performance of the proposed scheme.

2021 3rd International Conference on Applied Machine Learning (ICAML), Jul 1, 2021

The problem of efficient content distribution in mobile network has attracted wide attentions fro... more The problem of efficient content distribution in mobile network has attracted wide attentions from industry and academia. One of the significant approaches is to deploy in-network caching in mobile network. And a lot of methods have been proposed to enhance the content delivery in mobile network by deploying in-network caching. At the same time, some important research challenges remain to be solved. In this article, we present a brief survey on in-network caching of mobile network and discuss some research issues as well as challenges. We identify several significant aspects of mobile network caching, such as where to cache, how to cache, enabling technologies, and challenges. Finally, a brief summary and our conclusion are presented.

Iet Communications, May 1, 2019

Computation offloading has been considered as one of the key research issues in edge computing fi... more Computation offloading has been considered as one of the key research issues in edge computing fields. In order to reduce the energy consumption of the mobile terminal, the energy efficiency issue of computation offloading has attracted a lot of attention from academia and industry. In this study, the authors propose an energy-efficient computation offloading scheme in 5G cellular networks with edge computing and device-to-device (D2D) communications. They consider the computation offloading to fog computing devices via D2D communications and mobile edge computing (MEC) servers via cellular networks. And thus the computation task execution model can be composed of local execution, fog computing device execution and MEC server execution. Then, they formulate the computation offloading issue as stochastic optimisation problem, and use the Lyapunov optimisation technology framework to solve this problem. Finally, extensive simulation results are presented to illustrate the effectiveness of the proposed scheme.

IGI Global eBooks, 2021

Networkslicinghasbeenconsideredapromisingtechnologyinnextgenerationmobilenetworks(5G), whichcancr... more Networkslicinghasbeenconsideredapromisingtechnologyinnextgenerationmobilenetworks(5G), whichcancreatevirtualnetworksandprovidecustomizedserviceondemand.Mostexistingworks onnetworkslicingmainlyfocusonvirtualizationtechnology,andhavenotconsideredin-network caching well. However, in-network caching, as the one of the key technologies for informationcentricnetworking(ICN),hasbeenconsideredasasignificantapproachin5Gnetworktocopewith thetrafficexplosionandnetworkchallenges.Inthisarticle,theauthorsjointlyconsiderin-network cachingcombiningwithnetworkslicing.Theyproposeanefficientcachingresourcesharingscheme fornetworkslicingin5Gcorenetwork,aimingatsolvingtheproblemofhowtoefficientlysharethe limitedphysicalcachingresourceofInfrastructureProvider(InP)amongmultiplenetworkslices. Inaddition,fromtheperspectiveofnetworkslicing,theauthorsformulatecachingresourcesharing problemasanon-cooperativegame,andproposeaniterationalgorithmbasedoncachingresource updatingtoobtaintheNashEquilibriumsolution.Simulationresultsshowthattheproposedalgorithm hasgoodconvergenceperformance,andillustratetheeffectivenessoftheproposedscheme.

2022 5th International Conference on Hot Information-Centric Networking (HotICN)

IEEE transactions on big data, 2024

IEEE internet of things journal, 2024

IEEE access, 2024

Scalable Video Coding (SVC) and edge caching are two techniques that hold the potential to improv... more Scalable Video Coding (SVC) and edge caching are two techniques that hold the potential to improve user-perceived video viewing experience. Moreover, video recommendation can further enhance the caching gain by reshaping users' video preferences. In this paper, we investigate the video caching, recommendation and transmission for layered SVC streaming in cache-enabled cellular networks. Considering the dynamic characteristics of video popularity distribution and wireless network environment, to improve energy efficiency by minimizing system energy consumption and ensure the average user preference deviation tolerance, we begin by formulating a long-term optimization problem that focuses on video caching, recommendation and user association (UA). The problem is then transformed into a Markov decision process (MDP), which is solved by designing a dueling deep Q-learning network (DDQN)based algorithm. Using this algorithm, we can obtain the optimal video caching, recommendation and UA solutions. Since the action space of the MDP is huge, to cope with the "curse of dimensionality", linear approximation is integrated into the designed algorithm. Finally, the proposed algorithm's convergence and effectiveness in reducing long-term system energy consumption are demonstrated through extensive simulations. INDEX TERMS Scalable video coding; edge caching; recommendation; user association; energy efficiency; dueling deep Q-learning.

arXiv (Cornell University), Feb 4, 2024

The emergence of intelligent applications and recent advances in the fields of computing and netw... more The emergence of intelligent applications and recent advances in the fields of computing and networks are driving the development of computing and networks convergence (CNC) system. However, existing researches failed to achieve comprehensive scheduling optimization of computing and network resources. This shortfall results in some requirements of computing requests unable to be guaranteed in an end-to-end service pattern, negatively impacting the development of CNC systems. In this article, we propose a distributed cooperative routing framework for the CNC system to ensure the deadline requirements and minimize the computation cost of requests. The framework includes trading plane, management plane, control plane and forwarding plane. The cross-plane cooperative end-to-end routing schemes consider both computation efficiency of heterogeneous servers and the network congestion degrees while making routing plan, thereby determining where to execute requests and corresponding routing paths. Simulations results substantiates the performance of our routing schemes in scheduling computing requests in the CNC system.

arXiv (Cornell University), Jan 31, 2024

With the development of new Internet services such as computation-intensive and delay-sensitive t... more With the development of new Internet services such as computation-intensive and delay-sensitive tasks, the traditional "Best Effort" network transmission mode has been greatly challenged. The network system is urgently required to provide endto-end transmission determinacy and computing determinacy for new applications to ensure the safe and efficient operation of services. Based on the research of the convergence of computing and networking, a new network paradigm named deterministic computing power networking (Det-CPN) is proposed. In this article, we firstly introduce the research advance of computing power networking. And then the motivations and scenarios of Det-CPN are analyzed. Following that, we present the system architecture, technological capabilities, workflow as well as key technologies for Det-CPN. Finally, the challenges and future trends of Det-CPN are analyzed and discussed.

arXiv (Cornell University), Dec 1, 2023

The fiercely competitive business environment and increasingly personalized customization needs a... more The fiercely competitive business environment and increasingly personalized customization needs are driving the digital transformation and upgrading of the manufacturing industry. IIoT intelligence, which can provide innovative and efficient solutions for various aspects of the manufacturing value chain, illuminates the path of transformation for the manufacturing industry. It's time to provide a systematic vision of IIoT intelligence. However, existing surveys often focus on specific areas of IIoT intelligence, leading researchers and readers to have biases in their understanding of IIoT intelligence, that is, believing that research in one direction is the most important for the development of IIoT intelligence, while ignoring contributions from other directions. Therefore, this paper provides a comprehensive overview of IIoT intelligence. We first conduct an in-depth analysis of the inevitability of manufacturing transformation and study the successful experiences from the practices of Chinese enterprises. Then we give our definition of IIoT intelligence and demonstrate the value of IIoT intelligence for industries in fucntions, operations, deployments, and application. Afterwards, we propose a hierarchical development architecture for IIoT intelligence, which consists of five layers. The practical values of technical upgrades at each layer are illustrated by a close look on lighthouse factories. Following that, we identify seven kinds of technologies that accelerate the transformation of manufacturing, and clarify their contributions. The ethical implications and environmental impacts of adopting IIoT intelligence in manufacturing are analyzed as well. Finally, we explore the open challenges and development trends from four aspects to inspire future researches.

IEEE Transactions on Vehicular Technology

IEEE Access, 2017

With the explosive growth of Internet traffic and the rapid development of network technology, co... more With the explosive growth of Internet traffic and the rapid development of network technology, content delivery has become a significant service in the current Internet. However, the existing content delivery solutions, such as peer-to-peer and content delivery network, have many insufficient aspects. Meanwhile, the collaboration between content delivery and network infrastructures has been considered as a promising technique in network field. From the perspective of collaboration, content delivery systems can make full use of the network characteristics and the effective information provided by the network operators, so as to improve the efficiency of the content distribution and optimize the overall performance of the network. In this paper, we present a comprehensive survey on the collaboration for content delivery and network infrastructures. First, we provide some of the works, which have been done on collaboration solutions from two perspectives: evolutionary and revolutionary. And then, the advantages and disadvantages of these solutions are compared and analyzed from three aspects of technology, business, and standardization. Finally, we outline some challenges and research directions in the future.

Proceedings of the 28th Annual International Conference on Mobile Computing And Networking, Oct 14, 2022

In this paper, we present NestFL, a learning-efficient FL framework for edge computing, which can... more In this paper, we present NestFL, a learning-efficient FL framework for edge computing, which can jointly improve the training efficiency and achieve personalization. Specifically, NestFL takes the runtime resources of the edge devices into consideration and assigns each device a sparsestructured subnetwork by progressively performing the structured pruning. During training, only the updates of these subnetworks are transmitted to the central server. Additionally, these generated subnetworks adopt a structure-and parameter-sharing mechanism, making themselves nested inside a multi-capacity global model. In doing so, the overall communication and computation costs can be significantly reduced, and each device can learn a personalized model without introducing extra parameters. Furthermore, a weighted aggregation mechanism is designed to improve the training performance and maximally preserve personalization.

China Communications, Jul 1, 2019

With the new promising technique of mobile edge computing (MEC) emerging, by utilizing the edge c... more With the new promising technique of mobile edge computing (MEC) emerging, by utilizing the edge computing and cloud computing capabilities to realize the HTTP adaptive video streaming transmission in MEC-based 5G networks has been widely studied. Although many works have been done, most of the existing works focus on the issues of network resource utilization or the quality of experience (QoE) promotion, while the energy efficiency is largely ignored. In this paper, different from previous works, in order to realize the energy efficiency for video transmission in MEC-enhanced 5G networks, we propose a joint caching and transcoding schedule strategy for HTTP adaptive video streaming transmission by taking the caching and transcoding into consideration. We formulate the problem of energy-efficient joint caching and transcoding as an integer programming problem to minimize the system energy consumption. Due to solving the optimization problem brings huge computation complexity, therefore, to make the optimization problem tractable, a heuristic algorithm based on simulated annealing algorithm is proposed to iteratively reach the global optimum solution with a lower complexity and higher accuracy. Finally, numerical simulation results are illustrated to demonstrated that our proposed scheme brings an excellent performance.

Coded caching and cooperative caching have been considered as two promising technologies in heter... more Coded caching and cooperative caching have been considered as two promising technologies in heterogeneous small cell networks. Although some works have been done for coded caching and cooperative caching in heterogeneous small cell networks, to the best of our knowledge, these two important issues have traditionally been addressed separately. However, it is necessary to jointly consider these two significant issues to reduce the backhaul rate and improve content delivery as well as the Quality of Experience (QoE) of end-users. Moreover, the energy efficiency issue for content caching and content delivery is also extremely significant but excessively negligent. In this paper, we jointly consider the coded caching and cooperative caching issues, and propose a cooperative coded caching scheme to improve the content delivery efficiency and enhance the QoE for end-users. And then, based on the proposed scheme, we establish an energy consumption model from the perspective of content caching and content delivery to optimize the energy efficiency. In addition, we propose a greedy-based algorithm to solve this energy efficiency issue by optimizing the caching placement. Finally, simulation results show the performance of the proposed scheme.

2021 3rd International Conference on Applied Machine Learning (ICAML), Jul 1, 2021

The problem of efficient content distribution in mobile network has attracted wide attentions fro... more The problem of efficient content distribution in mobile network has attracted wide attentions from industry and academia. One of the significant approaches is to deploy in-network caching in mobile network. And a lot of methods have been proposed to enhance the content delivery in mobile network by deploying in-network caching. At the same time, some important research challenges remain to be solved. In this article, we present a brief survey on in-network caching of mobile network and discuss some research issues as well as challenges. We identify several significant aspects of mobile network caching, such as where to cache, how to cache, enabling technologies, and challenges. Finally, a brief summary and our conclusion are presented.

Iet Communications, May 1, 2019

Computation offloading has been considered as one of the key research issues in edge computing fi... more Computation offloading has been considered as one of the key research issues in edge computing fields. In order to reduce the energy consumption of the mobile terminal, the energy efficiency issue of computation offloading has attracted a lot of attention from academia and industry. In this study, the authors propose an energy-efficient computation offloading scheme in 5G cellular networks with edge computing and device-to-device (D2D) communications. They consider the computation offloading to fog computing devices via D2D communications and mobile edge computing (MEC) servers via cellular networks. And thus the computation task execution model can be composed of local execution, fog computing device execution and MEC server execution. Then, they formulate the computation offloading issue as stochastic optimisation problem, and use the Lyapunov optimisation technology framework to solve this problem. Finally, extensive simulation results are presented to illustrate the effectiveness of the proposed scheme.

IGI Global eBooks, 2021

Networkslicinghasbeenconsideredapromisingtechnologyinnextgenerationmobilenetworks(5G), whichcancr... more Networkslicinghasbeenconsideredapromisingtechnologyinnextgenerationmobilenetworks(5G), whichcancreatevirtualnetworksandprovidecustomizedserviceondemand.Mostexistingworks onnetworkslicingmainlyfocusonvirtualizationtechnology,andhavenotconsideredin-network caching well. However, in-network caching, as the one of the key technologies for informationcentricnetworking(ICN),hasbeenconsideredasasignificantapproachin5Gnetworktocopewith thetrafficexplosionandnetworkchallenges.Inthisarticle,theauthorsjointlyconsiderin-network cachingcombiningwithnetworkslicing.Theyproposeanefficientcachingresourcesharingscheme fornetworkslicingin5Gcorenetwork,aimingatsolvingtheproblemofhowtoefficientlysharethe limitedphysicalcachingresourceofInfrastructureProvider(InP)amongmultiplenetworkslices. Inaddition,fromtheperspectiveofnetworkslicing,theauthorsformulatecachingresourcesharing problemasanon-cooperativegame,andproposeaniterationalgorithmbasedoncachingresource updatingtoobtaintheNashEquilibriumsolution.Simulationresultsshowthattheproposedalgorithm hasgoodconvergenceperformance,andillustratetheeffectivenessoftheproposedscheme.

2022 5th International Conference on Hot Information-Centric Networking (HotICN)