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AIEC-RSC: AI and Edge Collaboration Empowered Reliable Service Computing for High-Speed Mobile Businesses

IEEE TRANSACTIONS ON SERVICES COMPUTING 2024年第1期17卷 224-236页

作者： Xu, Siya Chi, Jingye Wang, Shi Guo, Shaoyong Qiu, Xuesong Meng, Luoming Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

With the rapid development of high-speed assistant driving and smart inspections, the edge network is required to provide quick and reliable service to avoid large service response delays and frequent re-transmissions caused by interruption. However, the reasonable service component caching, efficient edge collaboration and reliable cross-domain computation offloading are still key problems to be solved. Thus, we consider an AI and mobile edge computing (MEC) integrated service framework, which is highly reliable for high-speed mobile businesses, and we divide the service process into component caching phase and task offloading phase. In the first phase, we novelly define the edge collaborative service domain (ECSD) which allows multiple edge nodes to collaboratively share resources from a global perspective and design a user behavior aware service component pre-caching method to increase resource utilization. In the second phase, based on the formed ECSDs and cached service components, we present an AI-empowered cross-domain computation task offloading mechanism including task partition and backup to enhance the reliable service capability of edge networks. Simulation results verify that the proposed mechanism can jointly optimize the allocation of caching, computation, and communication resources, while improving the service response speed and resource utility of edge networks.

关键词： High-speed mobile business mobile edge computing service component caching computation task offloading

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Comprehensive Link-Level Simulator for Terahertz MIMO Integrated Sensing and Communication Systems With TDD Framework

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IEEE TRANSACTIONS ON VEHICULAR techNOLOGY 2024年第11期73卷 16932-16947页

作者： Shi, Hanchen Yang, Chuang Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Terahertz (THz) integrated sensing and communication (ISAC) with multiple-input multiple-output (MIMO) architecture is recognized as a promising interdisciplinary technology for ultra-high-rate mobile communications since the systems enable narrow beam tracking which is necessary in the THz band. In this work, a link-level simulator for THz MIMO ISAC in time-division duplex (TDD) operation is proposed to design and analyze mobile systems. Compared to the simulators in the literature, the proposed simulator is more practical and comprehensive, employing two-dimensional position and motion simulation to develop localization capabilities, and considering THz characteristics such as wideband echo, molecular absorption and cluster-based channel. Specifically, the simulator supports the standard orthogonal frequency division multiplexing (OFDM) and discrete Fourier transform spread OFDM (DFT-s-OFDM) waveforms for sensing and communication simultaneously. Trade-offs between communication and sensing metrics required for waveform numerology design are investigated. In particular, by exploiting TDD framework's integration capability, range-velocity-angle estimation with virtual array and sensing-aided downlink spatial multiplexing are co-designed. Additionally, a user interface with elaborate parameter configuration is introduced. Finally, we implement an urban vehicle-to-vehicle (V2V) application case to verify the simulator. The simulation results present the feasibility of the developed integrated architecture.

关键词： Terahertz communications MIMO communication OFDM 6G mobile communication Estimation Location awareness Design methodology THz ISAC MIMO TDD OFDM waveform numerology link-level simulator

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Fast Personalized Federated Learning in Wireless Networks With Heterogeneous Data and Limited Communication Resources

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IEEE INTERNET OF THINGS JOURNAL 2024年第17期11卷 28555-28565页

作者： Fan, Shaoshuai Ni, Jie Tian, Hui Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

In addressing the challenges of heterogeneous data and limited communication resources in wireless networks, which often hinder the performance of federated learning, this article introduces a personalized learning approach. This approach not only addresses data heterogeneity but also optimizes resource management in wireless networks. We construct an optimization model aimed at maximizing the decay of the global loss function in a single iteration. The problem is divided into two subproblems: 1) allocation of device-local fine-tuning learning rates and 2) communication resources, tackled through an iterative method. The solutions involve determining near-optimal fine-tuning learning rates and optimizing device resource block and transmission power allocation. Our simulation results demonstrate that, under the constraints of wireless network resources and data heterogeneity, our algorithm outperforms baseline methods in terms of convergence speed and accuracy in personalized federated learning.

关键词： Data models Federated learning Adaptation models Training Wireless networks Resource management Servers Heterogeneity of device data personalized federated learning (PFL) wireless resource management

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Beam Management in Low Earth Orbit Satellite Networks With Random Traffic Arrival and Time-Varying Topology

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IEEE TRANSACTIONS ON VEHICULAR techNOLOGY 2024年第9期73卷 13352-13367页

作者： Zhu, Jianfeng Sun, Yaohua Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Low earth orbit (LEO) satellite communication networks have been considered as promising solutions to providing high data rate and seamless coverage, where satellite beam management plays a key role. However, due to the limitation of beam resource, dynamic network topology, beam spectrum reuse, time-varying traffic arrival and service continuity requirement, it is challenging to effectively allocate time-frequency resource of satellite beams to multiple cells. In this article, aiming at reducing time-averaged beam revisit time and mitigate inter-satellite handover, a beam management problem is formulated for dynamic LEO satellite communication networks, under inter-cell interference and network stability constraints. Particularly, inter-cell interference constraints are further simplified into off-axis angle based constraints, which provide tractable rules for spectrum sharing between two beam cells. To deal with the long-term performance optimization, the primal problem is transformed into a series of single epoch problems by adopting Lyapunov optimization framework. Since the transformed problem is NP-hard, it is further divided into three subproblems, including serving beam allocation, beam service time allocation and serving satellite allocation. With the help of conflict graphs built with off-axis angle based constraints, serving beam allocation and beam service time allocation algorithms are developed to reduce beam revisit time and cell packet queue length. Then, we further develop a satellite-cell service relationship optimization algorithm to better adapt to dynamic network topology. Compared with baselines, numerical results show that our proposal can reduce average beam revisit time by 20.8% and keep strong network stability with similar inter-satellite handover frequency.

关键词： Satellite broadcasting Resource management Satellites Low earth orbit satellites Handover Interference Heuristic algorithms Low earth orbit satellite communication beam management beam revisit time inter-satellite handover interference mitigation

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Dynamic Cache Placement and Trajectory Design for UAV-Assisted Networks: A Two-Timescale Deep Reinforcement Learning Approach

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IEEE TRANSACTIONS ON VEHICULAR techNOLOGY 2024年第4期73卷 5516-5530页

作者： Liu, Binghong Liu, Chenxi Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Unmanned aerial vehicle (UAV)-assisted edge caching has been attracting significant attention, due to the potential of UAVs in delivering prompt content services to users. One of the key issues in UAV-assisted edge caching networks is the unpredictable user requests, which requires dynamic update of cache placement. Moreover, the timescale difference between cache placement strategy with long updating cycle and UAV trajectory planning strategy with short updating cycle makes them difficult to be optimized simultaneously. Against these backdrops, in this article, we consider a UAV-assisted edge caching network, where the UAVs act as aerial base stations (BSs), together with terrestrial BS to provide edge caching services for the mobile users. The user association, UAV cache placement and trajectory planning strategies are jointly optimized to maximize the throughput, while simultaneously satisfying the cache capacity and kinematics constraints of the UAVs. Specifically, we split the optimization problem into a cache placement subproblem in large timescale and a user association and trajectory planning subproblem in small timescale. A double deep Q-network (DDQN) method is adopted to solve the former subproblem, and an attention-based multi-agent deep deterministic policy gradient (ATMADDPG) algorithm is utilized to deal with the latter, in which the users and UAVs are regarded as heterogeneous agents to learn the accessing and flying policies for mutual benefits, respectively. Finally, a two-timescale deep reinforcement learning (2TDRL) algorithm is proposed to iteratively solve these two subproblems. Through comparisons with the other state-of-art schemes, simulation results verify the effectiveness of our proposed algorithm and demonstrate that a well-designed cache placement strategy can increase the throughput by 18.6%.

关键词： Unmanned aerial vehicle (UAV)-assisted edge caching user association cache placement UAV trajectory planning

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Performance Analysis of Integrated Sensing and Communication Networks With Blockage Effects

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IEEE TRANSACTIONS ON VEHICULAR techNOLOGY 2024年第11期73卷 16876-16891页

作者： Sun, Zezhong Yan, Shi Jiang, Ning Zhou, Jiaen Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Communication-sensing integration represents an up-and-coming area of research, enabling wireless networks to simultaneously perform communication and sensing tasks. However, in urban cellular networks, the blockage of buildings results in a complex signal propagation environment, affecting the performance analysis of integrated sensing and communication (ISAC) networks. To overcome this obstacle, this paper constructs a comprehensive framework considering building blockage and employs a distance-correlated blockage model to analyze interference from line of sight (LoS), non-line of sight (NLoS), and target reflection cascading (TRC) links. Using stochastic geometric theory, expressions for signal-to-interference-plus-noise ratio (SINR) and coverage probability for communication and sensing in the presence of blockage are derived, allowing for a comprehensive comparison under the same parameters. The research findings indicate that blockage can positively impact coverage, especially in enhancing communication performance. The analysis also suggests that there exists an optimal base station (BS) density when blockage is of the same order of magnitude as the BS density, maximizing communication or sensing coverage probability.

关键词： Sensors Interference Radar Wireless sensor networks Analytical models Wireless networks Stochastic processes Blockage effect integrated sensing and communication (ISAC) performance analysis stochastic geometry

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Energy-Efficient Cache Update and Content Delivery for Optimizing Information Freshness of Industrial Applications

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IEEE INTERNET OF THINGS JOURNAL 2024年第3期11卷 4508-4522页

作者： Zhao, Junwei Wang, Ying Qin, Xiaoqi Yan, Yingjie Fei, Zixuan Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

In industrial edge caching networks, to ensure long-term accurate decision making of industrial applications, it is critical to obtain fresh sensing contents with low sensor energy consumption. The acquisition of sensing contents consists of cache update and content delivery, jointly determining the Age of Information (AoI) of applications. However, cache update suffers from the large sensor energy consumption and the mismatch between content offerings and demands. Content delivery suffers from the limited fronthaul capacity. Furthermore, contents from multiple sensors typically need to be aggregated, allowing the AoI of applications to be determined by the co-AoI of all correlated sensors. It is challenging to make the tradeoff between the energy efficiency of each sensor and the co-AoI performance of all correlated sensors. In our work, the weighted sum of application AoI and sensor energy consumption is minimized by jointly optimizing cache update and content delivery, which is formulated as a long-term stochastic optimization problem. Next, two caching schemes, access point centric scheme (APCS) and request adaptive caching scheme (RACS), are presented. In APCS, we fully decouple cache update and content delivery by applying statistical probability of application requests to control update. In RACS, cached contents are updated along with content delivery according to real-time requests. Thus, we introduce the concept of decision reward to transform the stochastic problem into the per-time slot reward maximization problem and propose online algorithms to solve it. Simulation results show that proposed schemes can reduce the sensor energy consumption by 40% while guaranteeing the application AoI.

关键词： Sensors Heuristic algorithms Optimization Industrial Internet of Things Wireless sensor networks Wireless communication Energy consumption Age of Information (AoI) cache decision optimization edge caching networks energy efficient Industrial Internet of Things (IIoT)

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PrivTDSI: A Local Differentially Private Approach for Truth Discovery via Sampling and Inference

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IEEE TRANSACTIONS ON BIG DATA 2023年第2期9卷 471-484页

作者： Zhang, Pengfei Cheng, Xiang Su, Sen Zhu, Binyuan Beijing Univ Posts ands Telecommun State Key Lab Networking & Switching Tech Beijing 100876 Peoples R China

Truth discovery is an effective way to identify the aggregated truth of each task among multiple observed data drawn from different workers of varying reliabilities. However, existing studies are insufficient to protect individuals' privacy, as they either just guarantee the weaker versions of local differential privacy (LDP) or potentially assume that the tasks are independent. In this paper, we, for the first time, investigate the problem of truth discovery while achieving the rigorous LDP for each worker with continuous inputs without the independence assumption. We present a locally differentially private truth discovery approach called PrivTDSI based on sampling and inference with solid privacy and utility guarantees. In PrivTDSI, the server first determines which values of each worker should be sampled according to a sample proportion and sends the indexes of these values to each worker. Then, each worker adds noise into the sampled values for privacy protection and uploads them to the server. After receiving the noisy sampled values from all the workers, the server first infers the unsampled values and then conducts truth discovery based on both the noisy sampled values and the inferred values. In particular, to determine the sample proportion, we formulate a constrained nonlinear programming problem and give a closed-form solution to this problem. Moreover, to determine which values of each worker should be sampled while avoiding the situation where the values of some workers or tasks might not be sampled at all, we develop a two-stage sampling method called TOSS. Furthermore, to infer the unsampled values accurately, we design a quality-aware inference method based on matrix factorization called QualityMF. Experimental results on two real-world datasets and a synthetic dataset demonstrate the effectiveness of PrivTDSI.

关键词： Task analysis Privacy Servers Reliability Crowdsourcing Protocols Noise measurement truth discovery local differential privacy privacy protection sampling and inference

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SMR: Spatial-Guided Model-Based Regression for 3D Hand Pose and Mesh Reconstruction

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO techNOLOGY 2024年第1期34卷 299-314页

作者： Sun, Haifeng Zheng, Xiaozheng Ren, Pengfei Wang, Jingyu Qi, Qi Liao, Jianxin Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

3D hand reconstruction is an important technique for human-computer interaction. Interactive experience depends on the accuracy, efficiency, and robustness of the algorithm. Therefore, in this paper, we first propose a balanced framework called spatial-aware regression (SAR) to achieve precise and fast reconstruction. SAR can bridge convolutional networks and graph-structure networks more effectively than existing frameworks to fully exploit extracted spatial information using a novel spatial-aware initial graph building module. In addition, SAR uses adaptive-GCN to make keypoints interact efficiently and effectively;and regresses 2.5D belief maps to characterize uncertainty. SAR is highly flexible because it can predict an arbitrary number of keypoints and apply pose-guided refinement for coarse to fine regression. To produce more rational results for challenging cases and mitigate 3D label reliance, we also propose a more robust model-based framework called spatial-guided model-based regression (SMR) that is based on SAR. There are two critical designs of SMR: 1) it uses SAR to enhance the features with pose information to help the regression of hand model parameters;and 2) it regresses parameters in a spatially aware manner that is similar to SAR. Experiments demonstrate that the proposed frameworks surpass existing fully-supervised approaches on the FreiHAND, HO-3D, RHD, and STB datasets. Also, the performances of the proposed frameworks under weakly/self-supervised settings outperform other competitors. Meanwhile, the proposed frameworks are accurate and efficient.

关键词： Three-dimensional displays Feature extraction Decoding Predictive models Image reconstruction Computational modeling Solid modeling 3D hand pose estimation 3D hand mesh reconstruction

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Joint Network Function Placement and Routing Optimization in Dynamic Software-Defined Satellite-Terrestrial Integrated Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第5期23卷 5172-5186页

作者： Yuan, Shuo Sun, Yaohua Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Software-defined satellite-terrestrial integrated networks (SDSTNs) are seen as a promising paradigm for achieving high resource flexibility and global communication coverage. However, low latency service provisioning is still challenging due to the fast variation of network topology and limited onboard resource at low earth orbit satellites. To address this issue, we study service provisioning in SDSTNs via joint optimization of virtual network function (VNF) placement and routing planning with network dynamics characterized by a time-evolving graph. Aiming at minimizing average service latency, the corresponding problem is formulated as an integer nonlinear programming under resource, VNF deployment, and time-slotted flow constraints. Since exhaustive search is intractable, we transform the primary problem into an integer linear programming by involving auxiliary variables and then propose a Benders decomposition based branch-and-cut (BDBC) algorithm. Towards practical use, a time expansion-based decoupled greedy (TEDG) algorithm is further designed with rigorous complexity analysis. Extensive experiments demonstrate the optimality of BDBC algorithm and the low complexity of TEDG algorithm. Meanwhile, it is indicated that they can improve the number of completed services within a configuration period by up to 58% and reduce the average service latency by up to 17% compared to baseline schemes.

关键词： Routing Satellites Planning Dynamic scheduling Heuristic algorithms Network topology Topology Satellite-terrestrial integrated networks virtual network function placement routing planning end-to-end latency

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