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Service Localization and User Satisfaction Enabled Multi-Tier computing IoT System 44

Service Localization and User Satisfaction Enabled Multi-Tie...

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44th ieee international conference on distributed computing systems (ICDCS)

作者： Gong, Chenyu Ma, Mulei Zeng, Liekang Yang, Yang Wu, Liantao Liu, Zening HKUST Guangzhou IoT Thrust & Res Ctr Digital World Intelligent Th Guangzhou Peoples R China Peng Cheng Lab Shenzhen Peoples R China Terminus Grp Beijing Peoples R China East China Normal Univ Software Engn Inst Shanghai Peoples R China Purple Mt Labs Nanjing Peoples R China

ISBN: (纸本)9798350354720;9798350354713

the rapid expansion of the Internet of things (IoT) poses challenges to certain applications, such as Digital Twin (DT). While data from user devices can be filtered by human intelligence, this is not feasible for IoT devices. Owing to the voluminous data generated by IoT devices that require transmission and computing, traditional cloud computing architectures may no longer guarantee the Quality of Experience (QoE), even causing network congestion. To address this issue, we propose a novel Cloud-Network-Edge-Terminal (CNET) model, which includes an intelligent edge layer for filtering IoT data. the computing paradigm shift indicates that the network will provide services at the edge rather than in the cloud, which is so-called service localization. To demonstrate the benefits of service localization, we use integrated user requirement descriptions to measure QoE, specifically the concepts of Service Requirement Zone (SRZ) and User Satisfaction Ratio (USR). Additionally, we conduct extensive numerical simulations to evaluate the model's performance under varying Degrees of Localization (DoL). Our results show that service localization can significantly improve USR even in changing network conditions.

关键词： Service Localization Multi-Tier computing IoT System QoE Service Requirement Zone User Satisfaction Ratio Digital Twin

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Group-Centric Scheduling for Industrial Edge computing Networks with Incomplete Information 44

Group-Centric Scheduling for Industrial Edge Computing Netwo...

引用

44th ieee international conference on distributed computing systems (ICDCS)

作者： Zhu, Tongxin Zou, Ouming Fang, Xiaolin Luo, Junzhou Li, Yingshu Cai, Zhipeng Southeast Univ Dhaka Bangladesh Georgia State Univ Atlanta GA 30303 USA

ISBN: (纸本)9798350386066;9798350386059

the Industrial Edge computing (IEC) network has recently received considerable attention, where industrial devices offload their computation-intensive and delay-sensitive tasks to servers located at the network edge. Task offloading scheduling is a fundamental problem in IEC networks to achieve satisfactory quality of service. Many prior efforts have been devoted to scheduling task offloading for networks with complete information, while the complete information is hard or even infeasible to acquire by the scheduler. therefore, their performance degrades in IEC networks with incomplete information. Scheduling task offloading for IEC networks with incomplete information is urgent and presents great technical challenges. this paper proposes a group-centric task offloading framework tailored for IEC networks with incomplete information, and models the minimum delay scheduling problem as a Partially Observable Markov Decision Process. then, the SGOS algorithm integrating the Long Short-Term Memory with Soft Actor-Critic networks in reinforcement learning is proposed to devise online task offloading schedules for IEC networks with incomplete information. Extensive experimental results verify that the SGOS algorithm can achieve the best performance compared with baseline schemes in terms of major metrics, including convergence, delay, and workload balance.

关键词： Industrial Internet of things Mobile Edge computing Incomplete Information Offloading Scheduling

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Mitigating Demographic Bias of Federated Learning Models via Robust-Fair Domain Smoothing: A Domain-Shifting Approach 44

Mitigating Demographic Bias of Federated Learning Models via...

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44th ieee international conference on distributed computing systems (ICDCS)

作者： Zeng, Huimin Yue, Zhenrui Jiang, Qian Zhang, Yang Shang, Lanyu Zong, Ruohan Wang, Dong Univ Illinois Urbana IL 61801 USA

ISBN: (纸本)9798350386066;9798350386059

Federated learning (FL) emerges as a promising solution to train machine learning (ML) models from distributed data sources. In FL, the heterogeneous and imbalanced data distribution of local clients could severely hurt the fairness of the aggregated global model. In this paper, we identify two key obstacles of developing fair FL models w.r.t. the global distribution: the domain shifts from local clients to the global data distribution and the fairness heterogeneity across local clients. therefore, considering these two obstacles, we present a novel fairness-aware FL training framework Robust-Fair Domain Smoothing (RFDS) to address the bias issue of FL models from a unique domain-shifting perspective. In particular, we design two novel components to build RFDS: 1) local robust-fair training, and 2) reference domain smoothing. Local robust-fair training aims to train robust-fair local models whose fairness is robust against the domain shifts from local distributions to the global distribution. Reference domain smoothing reduces the heterogeneity of fairness across clients to improve the fairness of the aggregated global model. We further provide a theoretical analysis to show the connection between the domain discrepancy of local data distributions and the heterogeneity of fairness across clients. Empirical evaluation results on multiple real-world datasets show that RFDS achieves promising performance gains in improving demographic fairness compared to state-of-the-art baselines.

关键词： Federated Learning Group Fairness Domain Shift distributed computing

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three-dimensional Logic in Memory Device for Ultra-low Power Parallel Evolutionary computing 24

Three-dimensional Logic in Memory Device for Ultra-low Power...

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ieee 24th international conference on Nanotechnology (NANO)

作者： Zhang, Zhizhong Lin, Kelian Feng, Xueqiang Wang, Jinkai Zhao, Weisheng Zhang, Yue Beihang Univ Hangzhou Int Innovat Inst Natl Key Lab Spintron Hangzhou 311115 Peoples R China Beihang Univ MIIT Key Lab Spintron Fert Beijing Inst Beijing 100101 Peoples R China Beihang Univ Sch Integrated Circuit Sci & Engn Beijing 100101 Peoples R China

ISBN: (纸本)9798350386257;9798350386240

In this paper, a three-dimensional all-spin parallel evolutionary computing (ASPEC) device is proposed to realize the evolutionary algorithm in a single device instead of a traditional CMOS circuit. A 3D magnetic tunnel junction (MTJ) array is used to store the genetic information of the whole population. Using the spin transfer torque (STT) effect with spin diffusion mechanism, we realize a parallel computing scheme for chromosome replication, proliferation, crossover, gene mutation, and selection. Getting benefit from the logic-in-memory (LIM) architecture consisting of MTJ arrays, the ASPEC device is not only non-volatile but also avoids memory wall. Our results show that the time complexity of evolutionary algorithms is reduced due to the parallel computing design, and the energy consumption is also significantly cut down owing to non-volatility and its avoidance of Joule heating.

关键词： Magnetic Tunnel Junction Logic-in-Memory Evolutionary Algorithm

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A Bi-Layer Joint Training Reinforcement Learning Framework for Post-Disaster Rescue 20

A Bi-Layer Joint Training Reinforcement Learning Framework f...

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20th Annual international conference on distributed computing in Smart Sensor systems and the Internet of things (DCOSS-IoT)

作者： Huang, Songjun Sun, Chuanneng Gong, Jie Pompili, Dario Rutgers Univ New Brunswick Dept Elect & Comp Engn New Brunswick NJ 08901 USA Rutgers Univ New Brunswick Dept Civil & Environm Engn New Brunswick NJ USA

ISBN: (纸本)9798350369458;9798350369441

In modern post-disaster rescue missions, the deployment of Multi-Robot systems (MRSs) plays a key role in minimizing injuries and deaths among rescue personnel and civilians involved in the disaster. Achieving optimal MRS efficiency requires the implementation of a well-suited task allocation mechanism and a highly efficient pathfinding algorithm. However, due to inconsistent communication and low bandwidth, traditional frameworks in the mentioned domains may be impractical or may not work well. To address these problems, a novel Bi-Layer Joint Training Reinforcement (BJoT-RL) framework is proposed where, in the first layer, a Multi-Head Deep Q-Learning (MHDQN) is designed to perform task allocation;whereas, in the second layer, a Condition-Constrained Q-Learning (CCQ) is proposed to perform pathfinding. Noticeably, the output of each layer is used in the training of the other layer to realize a tight coupling, hence the innovative joint training. thorough simulations show that the BJoT-RL framework performs better than state-of-the-art solutions in such applications.

关键词： Multi-Agent Reinforcement Learning distributed Learning and computing Task Allocation Pathfinding

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Towards a lightweight distributed telemetry for microservices 44

Towards a lightweight distributed telemetry for microservice...

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44th ieee international conference on distributed computing systems (ICDCS)

作者： Otero, Manuel Maria Garcia, Jose Fernandez, Pablo Univ Seville Seville Spain Univ Seville Score Lab Seville Spain

ISBN: (纸本)9798350354720;9798350354713

Microservice architectures have become the standard framework for developing scalable distributed systems, offering significant advantages in managing the integration and evolution of complex applications. Despite their benefits, these architectures face challenges, particularly in effectively diagnosing and resolving performance and reliability issues. Traditional centralized telemetry models, such as those implemented by Prometheus, ELK, and various cloud-based platforms like Datadog or NewRelic, often require complex and costly configurations and are not inherently tailored to the unique requirements of RESTful microservices. While the OpenAPI Specification (OAS) has established itself as a key standard for describing microservice APIs, current centralized tools do not leverage this standard to enhance service analysis effectively. this paper introduces a novel, lightweight, and distributed approach to telemetry that capitalizes on the API information provided by the OAS. Our proposed model aims to simplify the diagnostic process by offering an automated, configuration-free system that provides developers and operations teams access to root cause analysis tools. Additionally, it allows for effective management of telemetry without impacting service performance, thanks to the ability to toggle telemetry features on or off as needed;in doing so, our approach is specially suitable to the dynamic nature of distributed computing Continuum (DCC) systems where resources and services may fluctuate and scale. As validation, we provide a first proof of concept consisting of a ready-touse package for the NodeJS ecosystem that has been tested to demonstrate that it can operate with minimal impact on system performance and resource usage.

关键词： telemetry oas api microservices

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HardWhale: A Hardware-isolated Network Security Enforcement System for Cloud Environments 44

HardWhale: A Hardware-isolated Network Security Enforcement ...

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44th ieee international conference on distributed computing systems (ICDCS)

作者： You, Myoungsung Nam, Jaehyun Seo, Hyunmin Seo, Minjae Kim, Jaehan Choi, Dongmin Shin, Seungwon Korea Adv Inst Sci & Technol Daejeon South Korea Dankook Univ Yongin South Korea

ISBN: (纸本)9798350386066;9798350386059

With the increasing popularity of containers for deploying microservices, ensuring the security of container networks has become a vital concern. However, current security solutions rely on a host's operating system (OS) to enforce network policies for container traffic. this design incurs severe overhead and cannot guarantee container network security when attackers gain access to the host's OS. therefore, we propose HardWhale, a hardware-isolated network security enforcement system for containers that delivers high-performance and robust network security without depending on the host's OS. HardWhale leverages a smartNIC, physically isolating the entire container traffic inspection stack from the host and accelerating inspection tasks. Inspection policies securely reside within the smartNIC and are updated in runtime without involving the host, due to our isolated policy management mechanism. this design ensures robust network security for containers, even if the host is exposed to attackers. Evaluations show that HardWhale protects containers against various network attacks in compromised environments and improves HTTP throughput threefold and HTTP latency 2.3fold compared to state-of-the-art solutions.

关键词： Cloud computing Container Network security Programmable data plane

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A Solution for conference Room Cluster Audio System Based on distributed Architecture 27

A Solution for Conference Room Cluster Audio System Based on...

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27th ieee/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and Parallel/distributed computing (SNPD)

作者： Xu, Xiaoyi Zhang, Xin Wei, Zenglai Commun Univ China Sch Mus & Recording Arts Beijing Peoples R China Commun Univ China Sch Comp & Cyber Sci Beijing Peoples R China

ISBN: (纸本)9798350391961;9798350391954

With the rapid development of information technology, people have put forward higher requirements for the audio-visual experience and usage functions of conference spaces. the traditional, single-function conference room configuration can no longer adapt to the diverse needs of modern work and interactive activities. How to achieve efficient management and control, seamless interconnection, and resource sharing of audio systems across spaces, while ensuring the acoustic characteristics and flexibility of each independent space, has become a core issue that needs to be urgently resolved in building a multi-hall, multi-functional conference room cluster. Based on the audio system project of the Academic Center of the Communication University of China, this paper proposes a solution for a conference room cluster audio system based on a distributed architecture. this solution not only overcomes the limitations of traditional systems in terms of scalability, collaborative work, and resource scheduling but also promotes lossless transmission, real-time processing, and adaptive configuration of audio signals. thus, it ensures the consistency and high quality of the audio experience within the entire cluster, providing practical guidance for the design and optimization of future conference room audio systems.

关键词： AoIP distributed architecture conference space cluster audio system

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VKM: A Virtual Keyboard and Mouse Solution Towards a Lightweight computing System 20

VKM: A Virtual Keyboard and Mouse Solution Towards a Lightwe...

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20th Annual international conference on distributed computing in Smart Sensor systems and the Internet of things (DCOSS-IoT)

作者： Bisht, Divyansh Pal, Amitangshu Banerjea, Shashwati Indian Inst Technol Kanpur Comp Sci & Engn Kanpur Uttar Pradesh India Motilal Nehru Natl Inst Technol Allahabad Comp Sci & Engn Prayagraj UP India

ISBN: (纸本)9798350369458;9798350369441

this paper provides a novel solution for developing a virtual keyboard and mouse (VKM) system that is easily manageable and portable. the traditional keyboards and mouse devices take up valuable desk space and are not easily customizable to different languages. On-screen keyboards and 3-D cameras are alternatives, but they also have drawbacks. Our proposed method makes use of computer vision techniques and calls for a mini-projector and a web camera as necessary hardware. the system tracks hand keypoints to detect real-time touch events and uses the Mediapipe tool to detect hands and keystrokes. the mouse functionality is also implemented by monitoring the finger hovering. through experimentation, we show that our VKM solution can provide an accuracy of >90% for detecting the correct keystroke, with a typing speed of similar to 55 letters/min.

关键词： Virtual keyboard user interface computer vision hand gesture touch detection

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Advanced Electromagnetism and Nanoplasmonics in FEniCSx 24

Advanced Electromagnetism and Nanoplasmonics in FEniCSx

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24th international conference on Transparent Optical Networks (ICTON)

作者： Greco, Stefano Castriotta, Michele Ciraci, Cristian Ctr Biomol Nanotechnol Ist Italiano Tecnol Arnesano LE Italy Univ Salento Dipartimento Matemat & Fis E De Giorgi Lecce Italy

ISBN: (纸本)9798350377330;9798350377323

the new approaches for speeding up calculations to allow High Performance computing (HPC) in the field of computational electromagnetism, together with longevity and portability of the code, are a complex but stimulating challenge. the Finite Element Method (FEM) is widely used to solve harmonic Maxwell's equations, that describe every electromagnetic and optical phenomena concerning light-matter interactions at nanoscale, for the simulation of nanophotonic devices. From a computation perspective the FEM resolution of the electromagnetic problem is very interesting as it presents many challenges. In fact, due to the nonlocal nature of Maxwell's equations (in frequency domain), the matrix associated to the differential problem is non-sparse such that the use of traditional hardware to acceleration (i.e., GPUs) is ineffective. Moreover, the most used FEM software require the purchase of a license for their use, and they often don't provide all the details of the underlying code. the research in this field could provide novel computational tools that overcome these issues and that give results to allow the study of both the properties of some fundamental phenomena and the behavior of nanophotonic systems. So, our main goal is to implement and then optimize some new computational ways and paradigms in this context.

关键词： computational electromagnetism High Performance computing Finite Element Method

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