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GIRP: Energy-Efficient QoS-Oriented Microservice Resource Provisioning via Multi-Objective Multi-Task Reinforcement Learning

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IEEE Transactions on Mobile computing 2025年

作者： Yuan, Honggang Wang, Ting Fu, Min Shi, Yuanming East China Normal University MoE Engineering Research Center of Software/Hardware Co-design Technology and Application Shanghai Key Laboratory of Trustworthy Computing Shanghai200062 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore ShanghaiTech University School of Information Science and Technology Shanghai201210 China

Microservice architecture has revolutionized web service development by facilitating loosely coupled and independently developable components distributed as containers or virtual machines. While existing studies emphasize end-to-end latency, this paper investigates energy-efficient quality-of-service (QoS)-oriented microservice provisioning, focusing on both QoS satisfaction and power consumption (PC) conservation. We propose the Green and Intelligent Resource Provision (GIRP) architecture, integrating a data-driven energy-latency-aware resource allocation and scheduling manager to balance latency and PC. To reconcile the trade-offs involved, a dual-objective optimization problem is formulated to minimize latency and energy use by selecting proper servers, allocating CPU cores, and determining service replicas. To address challenges with discrete variables, dual objectives, and implicit mappings, we leverage a model-free deep deterministic policy gradient-based reinforcement learning algorithm. Specifically, we develop a multi-task agent via the Multi-gate Mixture-of-Experts model to simultaneously make two separate actions regarding CPU core numbers and service replica numbers, followed by a single-task agent to determine service scheduling. Extensive experiments on the DeathStarBenchmark testbed validate GIRP's effectiveness, demonstrating approximately 52% resource savings and a 43% reduction in PC compared to leading methods like Sinan, Firm, and heuristic-based algorithms. These results highlight GIRP's capability to optimize microservice orchestration by balancing end-to-end latency and power efficiency. © 2025 IEEE. All rights reserved.

关键词： Quality of service

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CRFs for Digital Signature and NIZK Proof System in Web Services 1

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22nd International conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Kang, Burong Zhang, Lei Yang, Yafang Meng, Xinyu Engineering Research Center of Software/Hardware Co-design Technology and Application Ministry of Education East China Normal University Shanghai200062 China Science and Technology on Communication Security Laboratory Sichuan610041 China Research Institute of China Telecom Corporation Limited Shanghai200062 China School of Computer Science Fudan University Shanghai200433 China

ISBN: (数字)9783031226779

ISBN: (纸本)9783031226762

Web services are service-oriented computing technology which allows computers running different operating domains to access and share each other’s databases. Each web service is an application (like online business) which may require the private information of users. Thus, it will be important to preserve these web users’ individual privacy. The traditional approaches to achieve this goal in web security is to use the cryptographic technologies, such as digital signature, NIZK proof system. Whereas, some recent research results indicate that these cryptographic technologies may suffer from the algorithm substitution attack (ASA). ASA means that the cryptographic technology would be embedded some backdoor in the process of its implementation by the attacker, and with the backdoor information the attacker can steal the user’s private information. To address this problem, the concept of cryptographic reverse firewall (CRF) has been introduced, which could sanitize the messages inputting and outputting the user’s computer. In this paper, we construct the CRFs for the efficient Pointcheval-Sanders (PS) signature as well as the NIZK proof system. © 2023, Springer Nature Switzerland AG.

关键词： Web services

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HierarchyFL: Heterogeneous Federated Learning via Hierarchical Self-Distillation

arXiv

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arXiv 2022年

作者： Xia, Jun Zhang, Yi Yue, Zhihao Hu, Ming Wei, Xian Chen, Mingsong The MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application East China Normal University Shanghai200062 China

Federated learning (FL) has been recognized as a privacy-preserving distributed machine learning paradigm that enables knowledge sharing among various heterogeneous artificial intelligence (AIoT) devices through centralized global model aggregation. FL suffers from model inaccuracy and slow convergence due to the model heterogeneity of the AIoT devices involved. Although various existing methods try to solve the bottleneck of the model heterogeneity problem, most of them improve the accuracy of heterogeneous models in a coarse-grained manner, which makes it still a great challenge to deploy large-scale AIoT devices. To alleviate the negative impact of this problem and take full advantage of the diversity of each heterogeneous model, we propose an efficient framework named HierarchyFL, which uses a small amount of public data for efficient and scalable knowledge across a variety of differently structured models. By using self-distillation and our proposed ensemble library, each hierarchical model can intelligently learn from each other on cloud servers. Experimental results on various well-known datasets show that HierarchyFL can not only maximize the knowledge sharing among various heterogeneous models in large-scale AIoT systems, but also greatly improve the model performance of each involved heterogeneous AIoT device. copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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New constructions of asymptotically optimal periodic and aperiodic quasi-complementary sequence sets

arXiv

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arXiv 2025年

作者： Wang, Peng Heng, Ziling Li, Chengju School of Science Chang’an University Xi’an710064 China National Mobile Communications Research Laboratory Southeast University Nanjing211111 China MoE Engineering Research Center of Software/Hardware Co-design Technology and Application East China Normal University Shanghai200062 China

Quasi-complementary sequence sets (QCSSs) play an important role in multi-carrier code division multiple access (MC-CDMA) systems as they can support more users than perfect complementary sequence sets (PCSSs). The objective of this paper is to present new constructions of asymptotically optimal periodic and aperiodic QCSSs with large set sizes. Firstly, we construct a family of asymptotically optimal periodic (p2n, pn − 1, pn − 1, pn + 1) QCSSs with small alphabet size p, which has larger set size than the known family of periodic (pn(pn−1), pn−1, pn−1, pn+1) QCSSs. Secondly, we construct five new families of asymptotically optimal aperiodic QCSSs with large set sizes and low aperiodic tolerances. Each family of these aperiodic QCSSs has set size Θ(K2) for some flock size K. compared with known asymptotically optimal aperiodic QCSSs in the literature, the proposed aperiodic QCSSs by us have better parameters or new lengths of their constituent sequences. copyright © 2025, The Authors. All rights reserved.

关键词： code division multiple access

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FedPerturb: covert Poisoning Attack on Federated Learning via Partial Perturbation 26

FedPerturb: Covert Poisoning Attack on Federated Learning vi...

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26th European conference on Artificial Intelligence, ECAI 2023

作者： Jin, Tongsai Fu, Zhihui Meng, Dan Wang, Jun Qi, Yue Cao, Guitao MoE Engineering Research Center of SW/HW Co-design Technology and Application East China Normal University Shanghai China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Oppo Research Institute China

ISBN: (纸本)9781643684369

Federated learning breaks through the barrier of data owners by allowing them to collaboratively train a federated machine learning model without compromising the privacy of their own data. However, Federation Learning also faces the threat of poisoning attacks, especially from the client model updates, which may impair the accuracy of the global model. To defend against the poisoning attacks, previous work aims to identify the malicious updates in high dimensional spaces. However, we find that the distances in high dimensional spaces cannot identify the changes in a small subset of dimensions, and the small changes may affect the global models severely. Based on this finding, we propose an untargeted poisoning attack under the federated learning setting via the partial perturbations on a small subset of the carefully selected model parameters, and present two attack object selection strategies. We experimentally demonstrate that the proposed attack scheme achieves high attack success rate on five state-of-the-art defense schemes. Furthermore, the proposed attack scheme remains effective at low malicious client ratios and still circumvents three defense schemes with a malicious client ratio as low as 2%. © 2023 The Authors.

关键词： Learning systems

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Shape-aware Multi-task Learning for Semi-supervised 3D Medical Image Segmentation

Shape-aware Multi-task Learning for Semi-supervised 3D Medic...

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2021 IEEE International conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Liu, Shasha Li, Yan Li, Xiaohu Cao, Guitao East China Normal University MOE Research Center for Software/Hardware Co-Design Engineering Shanghai200062 China

ISBN: (纸本)9781665401265

Semi-supervised learning has achieved many successes in medical image segmentation since it reduces the costs of manually annotating by leveraging abundant unlabeled data. However, these semi-supervised methods lack attention to ambiguous regions (e.g., some edges or corners around the targets), which may lead to meaningless and unreliable guidance. In this paper, we propose a novel semi-supervised segmentation method called Shape-aware Multi-task Learning (SMTL) to address the above issue. Our multi-task framework includes three tasks namely i) the main task for segmentation ii) one auxiliary task for signed distance regression iii) another auxiliary task for contour detection. The multi-task framework jointly predicts probabilistic segmentation maps, signed distance maps (SDMs) and edge maps to collect complementary information in the existing target label. Specifically, these two auxiliary tasks explicitly enforce shape-priors on the segmentation output to generate more accurate masks. Moreover, we design a region-attention-based adversarial learning strategy that enforces the consistency of two auxiliary tasks prediction distributions on the unlabeled and labeled data to make a meaningful and reliable guidance. We evaluate our SMTL on the datasets of the 2018 Atrial Segmentation Challenge and the 2017 Liver Tumor Segmentation Challenge. The results demonstrate that our SMTL achieves improvements and outperforms the state-of-the-art semi-supervised methods. © 2021 IEEE.

关键词： Image segmentation

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connection models for the Internet-of-Things

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Frontiers of computer Science 2020年第3期14卷 65-85页

作者： Kangli HE Holger HERMANNS Hengyang WU Yixiang CHEN MoE Engineering Research Center for Software/Hardware Co-design Technology and Application East China Normal UniversityShanghai 200062China Saarland University Saarland Informatics CampusSaarbrücken 66123Germany

The Internet-of-Things(IoT)is expected to swamp the *** order to study and understand the emergent behaviour of connected things,effective support for their modelling is *** the heart of IoT are flexible and adaptive connection patterns between things,which can naturally be modelled by channel-based coordination primitives,and characteristics of connection failure probabilities,execution and waiting times,as well as resource *** latter is especially important in light of severely limited power and computation budgets inside the *** this paper,we tackle the IoT modelling challenge,based on a conservative extension of channel-based Reo *** introduce a model called priced probabilistic timed constraint automaton,which combines models of probabilistic and timed aspects,and integrates pricing *** expressive logic called priced probabilistic timed scheduled data stream logic is presented,so as to enable the specification and verification of properties,which characterize data-flow streams and prices.A small but illustrative IoT case demonstrates the principal benefits of the proposed approach.

关键词： IoT Reo cost time probability automaton

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conZone: A Zoned Flash Storage Emulator for consumer Devices

ConZone: A Zoned Flash Storage Emulator for Consumer Devices

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design, Automation and Test in Europe conference and Exhibition

作者： Dingcui Yu Jialin Liu Yumiao Zhao Wentong Li Ziang Huang Zonghuan Yan Mengyang Ma Liang Shi MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application East China Normal University Shanghai China College of Computer Science and Technology East China Normal University Shanghai China Software Engineering Institute East China Normal University Shanghai China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

considering the potential benefits to lifespan and performance, zoned flash storage is expected to be incorporated into the next generation of consumer devices. However, due to the limited volatile cache and heterogeneous flash cells of consumer-grade flash storage, adopting a zone abstraction requires additional internal hardware design to maximize its benefits. To understand and efficiently improve the hardware design on consumer-grade zoned flash storage, we present conZone—the first emulator tailored to the characteristics of consumer-grade zoned flash storage. Users can explore the internal architecture and management strategies of consumer-grade zoned flash storage and integrate the optimization with software. We validate the accuracy of conZone by realizing a hardware architecture for consumer-grade zoned flash storage and comparing it with the state-of-the-art. We also make a case study for read performance research with conZone to explore the design of mapping mechanisms and cache management strategies.

关键词： Performance evaluation Accuracy Europe computer architecture hardware software Planning Optimization Next generation networking

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RAID45: Hybrid Parity-Based RAID for Reducing Parity Write Wear on High-Density SSDs

RAID45: Hybrid Parity-Based RAID for Reducing Parity Write W...

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IEEE International conference on computer design: VLSI in computers and Processors, (ICCD)

作者： Jialin Liu Yujiong Liang Yunpeng Song Liang Shi MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350380408

ISBN: (纸本)9798350380415

High-densitysolid-state drives (SSDs), such as triple-level cell (TLC) or quad-level cell (QLC) flash, are adopted in parity-based RAID systems to achieve high reliability with low redundancy. However, the parity writes cause high write wear, which is unfriendly to such high-density SSDs with low write endurance. conversely, high-performance SSDs, such as ZNAND, XL-Flash, have high write endurance but their high cost per bit hinders their deployment in RAID. This paper proposed a novel hybrid RAID structure, RAID45, to reduce parity writes for highdensity SSDs. Specifically, RAID45 uses high-performance SSD to store the parity of write-intensive stripes to absorb as much of the wear of parity writes on high-density SSDs as possible. Experimental results on real platform show that RAID45 achieves encouraging parity write reduction on the high-density SSDs.

关键词： costs Redundancy Reliability

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Satellite Federated Fine-Tuning for Foundation Models: Architecture design and System Optimization

Satellite Federated Fine-Tuning for Foundation Models: Archi...

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IEEE conference on Global communications (GLOBEcoM)

作者： Yan Zhu Peng Yang Jingyang Zhu Dingzhu Wen Ting Wang Yong Zhou Yuanming Shi Chunxiao Jiang MoE Engineering Research Center of Software/Hardware Co-Design Technology and Application Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China School of Information Science and Technology ShanghaiTech University Shanghai China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

With the surge in the number of low earth orbit (LEO) satellites, continuous research has emerged on using satellite data to train artificial intelligence models. On one hand, traditional centralized training on the ground is not feasible due to privacy concerns and limited bandwidth for downloading raw satellite data. On the other hand, due to the limited energy and computational capability of satellites, training directly on satellites suffers from prolonged latency, especially for large models. To alleviate these issues, we propose a novel satellite-ground collaborative federated fine-tuning architecture, where ground stations (GSs) and satellites collaboratively train a global model without the need for data downloads. In this proposed architecture, satellites serve as edge devices and the ground server serves as a coordinator. However, the short satellite-ground communication windows caused by the high mobility of satellites and the substantial intra-orbit data transmission bring special challenges to the transmission process of federated edge learning. To tackle these challenges, we carefully design the satellite-ground collaborative fine-tuning architecture and utilize an optimized ring all-reduce algorithm and network flow algorithm to enhance the intra-orbit and ground-satellite transmissions, respectively. Experimental results demonstrate that our proposed architecture significantly reduces the training time by 40% compared to training solely on satellite.

关键词： Training Hands Satellites computational modeling collaboration Low earth orbit satellites computer architecture Data models Surges Optimization

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