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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： An, Ledong Wang, Chenyang Huang, Shaoyuan Guo, Yang Zhang, Cheng Qiu, Chao Wang, Xiaofei College of Intelligent and Computing Tianjin University Tianjin China College of Computer Science and Software Engineering Shenzhen University Guangdong Shenzhen518060 China Tianjin University of Finance and Economics Tianjin China Software Technology Company Limited Suzhou215163 China

ISBN: (纸本)9789819628292

The rapid advancements in time-series forecasting have led to the emergence of datasets with increasingly diverse characteristics. Researchers typically focus on designing robust algorithms to handle these datasets. However, model performance can vary across different datasets. Existing studies commonly use Mean Absolute Error (MAE) and Mean Squared Error (MSE) to evaluate model performance. These metrics often need to fully account for the impact of dataset quality on forecast accuracy and reliability, leading to insufficient explanations of model forecasts and even dataset dependence. Furthermore, the lack of dataset evaluation makes it difficult to determine whether forecast results are influenced by data characteristics or model architecture, significantly hindering model improvement. To address this problem, this study proposes a new dataset evaluation paradigm-Multiscale Temporal Entropy Evaluation Paradigm. This paradigm aims to tackle the problem of data feature ambiguity affecting model forecast interpretability. By evaluating nine time-series datasets from domains such as weather, economics, transportation, and networks and comparing these evaluations with the forecast results from six different models, this study demonstrates the effectiveness of this method in explaining the relationship between dataset features and model performance. © ifip international Federation for Information Processing 2025.

关键词： Spatio-temporal data

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A Utility-Adjustable Reverse Auction Mechanism for UAV Data Collection Task Allocation 20th

A Utility-Adjustable Reverse Auction Mechanism for UAV Data...

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Chen, Peng Zhang, Jixian School of Information Science and Engineering Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9789819628636

Due to their low cost, easy deployment, and high flexibility, unmanned aerial vehicles(UAV) have become widely utilized for various data collection tasks across different fields. In particular, virtual service providers(VSP) recruit UAVs to collect data in their regions of interest(ROI), and leverage this data to offer a range of services, such as metaverse, traffic management, etc. To attract UAV owners to participate in the recruitment activities, VSP need to provide participating users with payments as rewards to motivate their participation. However, the recruitment demands of different VSPs for UAVs can vary significantly. For instance, time-sensitive tasks require timely recruitment of sufficient UAVs to ensure prompt completion of data collection tasks, necessitating higher payments to increase user enthusiasm. Conversely, in other types of tasks, the VSP’s objective might be to maximize its own utility. However, designing a general incentive mechanism for VSPs with different tasks that satisfies incentive compatibility(IC) and individual rationality(IR) to address the issues of UAV task allocation and payment is challenging. If VSP offer insufficient payments to users, it will be difficult to attract enough users to share their UAVs;conversely, offering excessive payments to users will harm the VSP’ profits. To address this problem, we propose a utility-adjustable reverse auction mechanism based on reverse Vickrey-Clarke-Groves(VCG) auction and affine maximizer auction(AMA) theory to cope with different task scenarios. This incentive mechanism can maximize social welfare while flexibly adjusting the utility allocation between VSP and users, ensuring non-negative utility for both parties. Experimental results show that the mechanism has excellent performance. © ifip international Federation for Information Processing 2025.

关键词： Unmanned aerial vehicles (UAV)

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DaCP: Accelerating Synchronization-Free SpTRSV via GPU-Friendly Data Communication and parallelism Strategies 20th

DaCP: Accelerating Synchronization-Free SpTRSV via GPU-Frie...

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Guo, Mingfeng Deng, Liang Dai, Zhe Li, Ruitian Lin, Gaofeng Liu, Jie Computational Aerodynamics Institute China Aerodynamics Research and Development Center Mianyang China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

ISBN: (纸本)9789819628292

Sparse triangular solve (SpTRSV) is a vital component in various scientific applications, and numerous GPU-based SpTRSV algorithms have been proposed. Synchronization-free SpTRSV is currently the mainstream algorithm on GPU due to its short preprocessing time and outstanding performance. However, we observed that this algorithm still has two performance bottlenecks. Firstly, the thread-level parallel mode can introduce to thread divergence issues within GPU warps during the writing phase. Secondly, the thread-level and warp-level fusion mode may struggles to fully exploit GPU resources due to suboptimal mapping relationships between rows and threads. To address these issues, this paper proposes DaCPSpTRSV, a new synchronization-free algorithm with GPU-friendly data communication and parallelism strategies. Specifically, we first develop a fast-forward thread-level approach, incorporating an efficient global memory access pattern and a light-weight dependency control mechanism, to optimize data communication and alleviate thread divergence. A fine-grained fusion strategy is then proposed to maximize GPU parallelism by adaptively selecting the suitable thread-level or warp-level modes. Moreover, the commonly-used compressed sparse row (CSR) format is employed in our DaCPSpTRSV, enhancing the versatility of our algorithm. We evaluate our approach using 245 matrices from the SuiteSparse Matrix Collection on two NVIDIA GPUs, demonstrating speedup ratios of up to 4.77×, 4.94×, 1.67×, and 1.62× compared to cuSPARSE, Sync-Free, CapelliniSpTRSV, and YuenyeungSpTRSV, respectively. The project is open-sourced at https://***/gmfff12334/DaCP. © ifip international Federation for Information Processing 2025.

关键词： Graphics processing unit

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SC-TSDRL: A Cloud-Edge Collaboration Framework for Diffusion Model Inference Acceleration 20th

SC-TSDRL: A Cloud-Edge Collaboration Framework for Diffusio...

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Wang, Huiyu Liu, Zhicheng Wang, Xiaofei Qiu, Chao Zhang, Cheng Wang, Wenyu Ye, Qianwen College of Intelligent and Computing Tianjin University Tianjin China Tianjin University of Finance and Economics Tianjin China Shanghai Zhuichu Networking Technologies Co. Ltd. Shanghai China Hubei Central China Technology Development of Electric Power Co. Ltd. Wuhan China

ISBN: (纸本)9789819628636

In recent years, the rapid rise of Artificial Intelligence Generated Content (AIGC) has been accompanied by a surge in demand for generative AI application services. This trend has not only driven the diversified deployment of large-scale models but also posed more significant challenges to the efficient inference of these models. Current computing solutions have struggled to solely keep pace with growing user demands, which results in insufferable latency and inefficient performance. Integrating cloud computing and edge computing for the inference process of large models is deemed a promising solution, while related resource scheduling issues are still pending. To address this challenge, we focus our research on diffusion models, a representative model in the field of generative artificial intelligence, and propose a cloud-edge collaborative framework to accelerate the inference pipeline of text-to-image diffusion models. Our optimization goal is to minimize the average completion time of inference tasks while maintaining image quality. Considering that the inference for each image is an iterative process, we propose a step clipping strategy to save and reuse intermediate results to reduce iterations, compressing the calculation amount of inference tasks. Above this, we design a task scheduling strategy using proximal policy optimization, which can make efficient resource decisions. Experiments demonstrate the superiority of our strategy over local execution, greedy task scheduling strategy, and learning-based task scheduling strategies. Compared with the three baselines, the average task completion time under different system configurations is reduced by 1.093 s, 1.024 s, and 0.481 s, respectively. © ifip international Federation for Information Processing 2025.

关键词： Cloud platforms

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LBoDSN: An In-network Load Balancing Mechanism for Lossless Data Center networks Based on Direct Switch Notification 20th

LBoDSN: An In-Network Load Balancing Mechanism for Lossless...

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Shi, Qingyu Jiang, Fangxue Huang, Huang Li, Xiaocui Li, Chuang Cao, Wenzhi Liu, Limei School of Advanced Interdisciplinary Studies Hunan University of Technology and Business Changsha China Xiangjiang Laboratory Changsha China

ISBN: (纸本)9789819628292

With the extensive deployment of Remote Direct Memory Access (RDMA) in lossless data center networks (DCNs), enhancing the RDMA load balancing performance for distributed AI training and HPC applications becomes particularly critical. However, existing load balancing schemes either suffer difficulty in responding to congestion in sub-RTT time, or cannot accurately detect and reroute flows that are on the verge of creating path congestion for Priority-based Flow Control (PFC) enabled lossless DCNs. In this paper, we propose LBoDSN, an in-network load balancing mechanism for lossless DCNs based on direct swtich notification, to address above challenges. LBoDSN monitors ingress queue length evolution at destination switches to predict the triggering time of PFC pause, and accurately identifies congested flows based on the congestion contribution level before PFC pause, then further proactively sends the flow congestion notification (FCN) to source switches for fast rerouting. The FCN contains a flow ID that identifies the congested flow, and a path ID that identifies the target path to which the congested flow will be rerouted. And after rerouting, the Congestion Notification Packet (CNP) of the old path is selectively discarded at source switches to improve transmission performance, while out-of-order packets are reordered at the destination switch. The experimental results show that under realistic workloads, LBoDSN achieves 9–64% and 20–80% better than CONGA for the average and tail Flow Completion Times (FCTs), respectively. Compared with ConWeave, LBoDSN achieves around 8% better performance for the average and tail FCTs while significantly reducing switch queue usage for reordering. © ifip international Federation for Information Processing 2025.

关键词： Time switches

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MiDedup: A Restore-Friendly Deduplication Method on Docker Image Storage Systems 20th

MiDedup: A Restore-Friendly Deduplication Method on Docker ...

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Qin, Lisha Tan, Haoliang Zou, Xiangyu Ou, Wenhao Wei, Yan Huang, Rubing Xia, Wen Harbin Institute of Technology Shenzhen China Peng Cheng Laboratory Shenzhen China Zhongruan International Technology Service Co. Ltd. Shenzhen China Macau University of Science and Technology Macao China

ISBN: (纸本)9789819628292

Docker image storage systems, like Docker registry, often employ deduplication to reduce storage overhead. Existing deduplication methods for these systems detect redundancy at either layer or file level, each with its own advantages and limitations. Layer-level deduplication offers much faster restoration but lower deduplication ratio, as it eliminates duplicate layers while ignoring duplicate files across layers. Conversely, file-level deduplication offers a higher deduplication ratio but slower restoration, as removing duplicate files scatters the files of a layer, leading to multiple disk read I/O during restoration. Our analysis reveals that the slow restoration in file-level deduplication partly stems from ignoring file-layer relationships. In this paper, we propose MiDedup, a new Docker deduplication method. MiDedup detects redundancy at file-level and organizes files into a restore-friendly layout by considering file-layer relationships to enhance restore speed. Our studies also show that duplicated files of one layer are not uniformly distributed across different layers. MiDedup uses this insight to skip deduplicating scattered files to further optimize the file layout for faster restoration. Evaluations indicate that MiDedup achieves restore speeds that are 8–19× faster than file-level deduplication (slightly slower than layer-level one), while maintaining 9–47% higher deduplication ratios than layer-level deduplication. © ifip international Federation for Information Processing 2025.

关键词： Redundancy

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Incentivizing Crowdsensing for DT-Enabled Metaverse 20th

Incentivizing Crowdsensing for DT-Enabled Metaverse

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Ye, Dongdong Huang, Xumin Wu, Yuan Kang, Jiawen Zhong, Weifeng Niyato, Dusit School of Automation Guangdong University of Technology Guangzhou China State Key Laboratory of Internet of Things for Smart City University of Macau Taipa China Department of Computer and Information Science University of Macau Taipa China Collge of Computing and Data Science Nanyang Technological University Singapore Singapore

ISBN: (纸本)9789819628292

Digital Twin (DT) has been proposed as a key enabling technology to produce a digital clone of the physical world and facilitate the convergence of the physical and virtual worlds for building a real-world Metaverse. For physical-virtual synchronization, crowdsensing is applied to employ Internet of Things (IoT) devices to sense physical objects and collect status information for timely updating the associated DTs. However, an incentive mechanism is necessitated to stimulate the devices to perform sensing tasks while meeting task requirements such as Age of Information (AoI) requirements. Thus, we adopt a contract theoretic approach to design an incentive mechanism for the devices that are classified into several types and the type parameters are unknown to others. The contract consists of a set of contract items with each contract item representing a device type, which specifies the required data updating frequency and monetary reward. We formulate an optimal contract design problem subject to feasible constraints including the average AoI requirement for each device type. Furthermore, we solve the problem by transforming it into a convex optimization problem that can be directly tackled by the existing methods. Finally, we provide numerical results to demonstrate the effectiveness and efficiency of our scheme. © ifip international Federation for Information Processing 2025.

关键词： Convex optimization

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A Satellite-Ground Link Handover Strategy in LEO networks Using Advantage Actor-Critic Algorithm 20th

A Satellite-Ground Link Handover Strategy in LEO Networks U...

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20th ifip WG 10.3 international conference on network and parallel computing, npc 2024

作者： Chen, Chen Tong, Chenqiang Cong, Li Wang, Zhiyi Jin, Fan Zhou, Xiaobo Pei, Qingqi School of Telecommunication Engineering Xidian University Xi’an710071 China Xidian Guangzhou Institute of Technology Xidian University Guangzhou China Xidian Hangzhou Institute of Technology Xidian University Hangzhou China The State Grid Jilin Province Electric Power Company Changchun130000 China National Key Laboratory of Science and Technology on Space Microwave CAST Xi’an710100 China College of Intelligence and Computing Tianjin University Tianjin300350 China

ISBN: (纸本)9789819628636

Low Earth Orbit (LEO) satellite network is a crucial component of the Space-Air-Ground Integrated network (SAGIN) architecture and Non-Terrestrial networks (NTN). It can provide global, real-time, and seamless broadband data services to many users, playing a critical role in emergencies such as disaster relief. This paper proposes an LEO satellite networks satellite-ground link handover strategy based on Advantage Actor-Critic (A2C) to tackle challenges associated with high handover frequency among ground users, data transmission blocking, and access selection post-handover due to the high-speed cyclic motion of satellites. The strategy considers three handover factors: signal reception strength, satellite potential service time, and service quality. At first, the handover problem is modeled as a combinatorial optimization problem, subsequently transformed into a Markovian Action-Value Function (MAVF) based Multi-Agent Markov Decision Process (MAMDP), and solved in the framework of the A2C algorithm proposed in this paper. The results of simulations illustrate the superior performance of the proposed handover strategy compared to three alternative strategies, namely, Random Handover (RH), Maximum number of Free Channels (MFC), and Maximum Service Time (MST), in terms of both convergence and practicality. The average number of handover occurrences can be reduced by up to 58%, consequently lowering the probability of blocking data transmission. Moreover, signal quality exhibits more excellent stability and can be enhanced by up to 39%, thereby ensuring user communication quality. © ifip international Federation for Information Processing 2025.

关键词： Markov processes

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network and parallel computing

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international JOURNAL OF parallel PROGRAMMING 2015年第3期43卷 311-315页

作者： Hsu, Ching-Hsien Li, Xiaoming Shi, Xuanhua Chung Hua Univ Dept Comp Sci & Informat Engn Hsinchu Taiwan Univ Delaware Dept Elect & Comp Engn Newark DE USA Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China

It’s our pleasure to bring you this special issue of the international Journal of parallel Programming on the network and parallel computing. Prior to the publication to this special issue, all papers were presented in the 10th ifip international conference on network and parallel computing (npc’13) held from September 19 to September 21 2013 in Guiyang, China. Since 2003, npc has become a valuable venue for engineers and scientists to present their excellent ideas and experiences in system?fields of distributed and parallel computing. The npc 2013 continues this tradition and in particular extends areas of interest to Big data computing and parallel and multicore issues and opportunities. Huazhong University of Science and Technology, China organized this year’s npc conference.

关键词： CLOUD storage SEMANTIC Web parallel algorithms

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Construction and Application of Linux Virtual Server Cluster for Scientific computing

Construction and Application of Linux Virtual Server Cluster...

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ifip international conference on network and parallel computing

作者： Tang, Hong She, Rui He, Chen Dou, Yusheng Chongqing Univ Posts & Telecommun Chongqing 400065 Peoples R China

ISBN: (纸本)9780769533544

In this paper, we describe a cluster server, Linux Virtual Server cluster, formed by various inexpensive personal computers for scientific computing. This cluster has many facorable features, including lower cost, load balancing, and dynamic scalability. Application of this cluster in the simulation of photochemistry reaction is also presented.

关键词： Cluster computing

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