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检索条件"任意字段=Proceedings of the 22nd International Conference on Distributed Computing and Networking"

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CoEdge: A Cooperative Edge System for distributed Real-Time Deep Learning Tasks 22

CoEdge: A Cooperative Edge System for Distributed Real-Time ...

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22nd ACM/IEEE international conference on Information Processing in Sensor Networks (IPSN)

作者： Jiang, Zhehao Ling, Neiwen Huang, Xuan Shi, Shuyao Wu, Chenhao Zhao, Xiaoguang Yan, Zhenyu Xing, Guoliang Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9798400701184

Recent years have witnessed the emergence of a new class of cooperative edge systems in which a large number of edge nodes can collaborate through local peer-to-peer connectivity. In this paper, we propose CoEdge, a novel cooperative edge system that can support concurrent data/compute-intensive deep learning (DL) models for distributed real-time applications such as city-scale traffic monitoring and autonomous driving. First, CoEdge includes a hierarchical DL task scheduling framework that dispatches DL tasks to edge nodes based on their computational profiles, communication overhead, and real-time requirements. Second, CoEdge can dramatically increase the execution efficiency of DL models by batching sensor data and aggregating the inferences of the same model. Finally, we propose a new edge containerization approach that enables an edge node to execute concurrent DL tasks by partitioning the CPU and GPU workloads into different containers. We extensively evaluate CoEdge on a self-deployed smart lamppost testbed on a university campus. Our results show that CoEdge can achieve up to 82.32% reduction on deadline missing rate compared to baselines.

关键词： Smart City Edge computing distributed Deep Learning System Real-time Scheduling Edge Containerization

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Not Best but Fair: Achieving a Fair Service Deployment Through Sky computing for Latency-Sensitive Applications 22nd

Not Best but Fair: Achieving a Fair Service Deployment Throu...

引用

22nd international conference on Service Oriented computing

作者： Shi, Weijia Zhao, Baokang Zhou, Huan Natl Univ Def Technol Changsha Peoples R China

ISBN: (纸本)9789819608072;9789819608089

Latency-sensitive applications, such as online gaming, require that the conditions of networks from the server to each client are almost the same to achieve fairness. Traditionally, the servers are always set fixedly in certain locations and only the nearby clients can connect, which is not fair to some far-away clients. To tackle the fairness issue, the emerging cloud computing or sky computing is a potential solution, where the server cannot be fixed anymore. Hence, we design LibraCloud, a novel server selection and allocation mechanism for latency-sensitive applications, using globally distributed cloud infrastructure. LibraCloud aims to select the fairest server rather than the best one. By defining a fairness indicator and dynamically utilizing multiple clouds, it overcomes the limitations of traditional fixed servers. To validate LibraCloud, we conduct experiments using 85 probes to simulate clients and 13 data centers for server selection. Assuming 20 distributed clients, 78.8% of the experimental cases show that LibraCloud selects the fairest server, significantly outperforming random selection or fixed three-server mechanisms.

关键词： Fair service deployment Sky computing Latency-sensitive applications Fairness

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DICer: distributed Coordination for In-Network Computations 9

DICer: Distributed Coordination for In-Network Computations

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22nd international conference on Information Centric networking

作者： Ambalavanan, Uthra Grewe, Dennis Nayak, Naresh Liu, Liming Mohan, Nitinder Ott, Joerg Robert Bosch GmbH Bosch Res Stuttgart Germany Tech Univ Munich Munich Germany

ISBN: (纸本)9781450392570

Application domains such as automotive and the Internet of Things may benefit from in-network computing to reduce the distance data travels through the network and the response time. Information Centric networking (ICN) based compute frameworks such as Named Function networking (NFN) are promising options due to their location independence and loosely-coupled communication model. However, unlike current operations, such solutions may benefit from orchestration across the compute nodes to use the available resources in the network better. In this paper, we adopt the State Vector Synchronization (SVS), an application dataset synchronization protocol in ICN, to enhance the neighborhood knowledge of in-network compute nodes in a distributed fashion. As such, we design distributed coordination for in-network computation (DICer) that assists the service deployments by improving the resolution of compute requests. We evaluate the performance of DICer against NFN and observe an increase in the resource utilization at the edge and a reduction in the request completion time.

关键词： distributed Coordination Named Function networking In-Network Compute Synchronization Protocols

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Streamlined Deployment of a distributed and Scalable Co -Simulation Platform for Integrated Finergy Systems 22

Streamlined Deployment of a Distributed and Scalable Co -Sim...

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22nd international conference on Intelligent Systems Applications to Power Systems

作者： Chini, Fabio Canali, Davide Barbierato, Luca Schiera, Daniele Salvatore Bottaccioli, Lorenzo Margara, Alessandro Patti, Edoardo Politecn Milan DEIB Milan Italy Politecn Milan DAUIN Turin Italy Politecn Milan Energy Ctr LAB Turin Italy Politecn Milan DENERG Turin Italy Politecn Milan DIST Turin Italy

ISBN: (纸本)9798331531768;9798331531751

To reach decarbonisation goals, energy systems are becoming increasingly complex and deeply integrated with other sectors and activities through digital technologies such as Big Data analytics and Digital Twins. In recent years, co -simulation has become a powerful technique to study complex cyber-physical integrated energy systems. Indeed, co -simulation enables the coupling of diverse simulators, each specialised in modelling a specific aspect of the system, to provide a comprehensive understanding of its behaviour. As the simulation scenarios grow in scale and complexity, they require more extensive compute infrastructures to scale horizontally. Yet, deploying and operating co -simulation platforms in distributed computing infrastructures remains a difficult task. This paper explores the challenges faced in achieving scalable co-simulation through horizontal distribution using cluster/cloud deployments, both in terms of engineering complexity for deploying and operating co-simulation platforms and in terms of absolute performance and scalability. It proposes a novel framework to streamline the process of deploying and operating complex co -simulation scenarios in cloud environments. The framework adopts established methodologies in engineering software solutions in the cloud to deploy and operate co -simulations. Specifically, it adopts containerisation technologies to decouple the definition of the simulation scenario from the execution infrastructure, automating and abstracting away distribution and deployment concerns and allowing seamless migration to different computing infrastructures. An initial assessment of absolute performance and scalability of realistic co-simulation scenarios within the proposed framework shows the benefits of horizontal scaling but also the performance bottlenecks introduced by current technologies for orchestrating simulators.

关键词： Co-simulation Integrated Energy Systems distributed computing Performance Analysis Cloud Software Engineering

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SLO-Aware Task Offloading Within Collaborative Vehicle Platoons 22nd

SLO-Aware Task Offloading Within Collaborative Vehicle Plato...

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22nd international conference on Service Oriented computing

作者： Sedlak, Boris Morichetta, Andrea Wang, Yuhao Fei, Yang Wang, Liang Dustdar, Schahram Qu, Xiaobo TU Wien Distributed Syst Grp Vienna Austria Tsinghua Univ Emerging Transportat Solut Beijing Peoples R China

ISBN: (纸本)9789819608072;9789819608089

In the context of autonomous vehicles (AVs), offloading is essential for guaranteeing the execution of perception tasks, e.g., mobile mapping or object detection. While existing work on offloading focused extensively on minimizing inter-vehicle networking latency, vehicle platoons (e.g., heavy-duty transport) present numerous other objectives, such as energy efficiency or data quality. To optimize these Service Level Objectives (SLOs) during operation, this work presents a purely Vehicle-to-Vehicle approach (V2V) for collaborative services offloading within a vehicle platoon. By training and using a Bayesian Network (BN), services can proactively decide to offload whenever this promises to improve platoon-wide SLO fulfillment;therefore, vehicles estimate how both sides would be impacted by offloading a service. In particular, this considers resource heterogeneity within the platoon to avoid overloading more restricted devices. We evaluate our approach in a physical setup, where vehicles in a platoon continuously (i.e., every 500 ms) interpret the SLOs of three perception services. Our probabilistic, predictive method shows promising results in handling large AV platoons;within seconds, it detects and resolves SLO violations through offloading.

关键词： Service Level Objectives Edge computing Intelligent Transportation Microservices Offloading Bayesian Networks

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Hydra: Concurrent Coordination for Fault-tolerant networking 22

Hydra: Concurrent Coordination for Fault-tolerant Networking

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22nd ACM/IEEE international conference on Information Processing in Sensor Networks (IPSN)

作者： Biri, Andreas Da Forno, Reto Kuonen, Tobias Mager, Fabian Zimmerling, Marco Thiele, Lothar Swiss Fed Inst Technol Zurich Switzerland Tech Univ Dresden Dresden Germany Univ Freiburg Freiburg Germany

ISBN: (纸本)9798400701184

Low-power wireless networks have the potential to enable applications that are of great importance to industry and society. However, existing network protocols do not meet the dependability requirements of many scenarios as the failure of a single node or link can completely disrupt communication and take significant time and energy to recover. This paper presents Hydra, a low-power wireless protocol that guarantees robust communication despite arbitrary node and link failures. Unlike most existing deterministic protocols, Hydra steers clear of centralized coordination to avoid a single point of failure. Instead, all nodes are equivalent in terms of protocol logic and configuration, performing coordination tasks such as synchronization and scheduling concurrently. This concept of concurrent coordination relies on a novel distributed consensus algorithm that yields provably unique decisions with low delay and energy overhead. In addition to a theoretical analysis, we evaluate Hydra in a multi-hop network of 23 nodes. Our experiments demonstrate that Hydra withstands random node failures without increasing coordination overhead and that it re-establishes efficient and reliable data exchange within seconds after a major disruption.

关键词： Fault tolerance consensus network coordination concurrent transmissions WSN

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Work in Progress: Dynamic Offloading of Soft Real-time Tasks in SDN-based Fog computing Environment 22

Work in Progress: Dynamic Offloading of Soft Real-time Tasks...

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22nd ACM SIGBED international conference on Embedded Software (EMSOFT) as part of the Embedded Systems Week (ESWEEK)

作者： Kumar, Niraj Mondal, Arijit RGIPT Jais Jais India IIT Patna Patna India

ISBN: (数字)9781665472982

ISBN: (纸本)9781665472982

A significant transition in the characteristics of computational workloads coupled with the developments in computing as well as networking concepts and practices has presented various challenges and opportunities. In this work, we study dynamic offloading of soft real-time tasks in SDN based fog computing system. Preliminary results have been presented to highlight the impact of intra/inter-cluster offloading on the penalty due to deadline miss. Finally, the future research directions have been outlined.

关键词： Fog computing SDN Soft Real-time Tasks Offloading

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MPS: A Multiple Poisoned Samples Selection Strategy in Backdoor Attack 22

MPS: A Multiple Poisoned Samples Selection Strategy in Backd...

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IEEE 22nd international conference on Trust, Security and Privacy in computing and Communications (TrustCom) / BigDataSE conference / CSE conference / EUC conference / ISCI conference

作者： Zou, Weihong Zhang, Shigeng Wang, Weiping Zhang, Jian Liu, Xuan Cent South Univ Schoosl Comp Sci & Engn Changsha Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha Peoples R China Sci & Technol Parallel & Distributed Proc Lab PDL Changsha Peoples R China

ISBN: (纸本)9798350381993;9798350382006

Recently there has been many studies on backdoor attacks, which involve injecting poisoned samples into the training set in order to embed backdoors into the model. Existing multiple-poisoned samples attacks usually randomly select a subset from clean samples to generate the poisoned samples. Filtering-and-Updating Strategy (FUS) has shown that the poisoning efficiency of each poisoned sample is inconsistent and random selection is not optimal. However, FUS does not fully considered the selection of multiple poisoned samples, there are still some issues with the selection of multiple poisoned samples. In this paper, we formulate the selection of multiple types of poisoned samples as a multi-objective optimization problem and proposed a Multiple Poisoned Samples Selection Strategy (MPS) to solve the issue. Unlike FUS, we consider the potential of clean samples that are not selected as to become efficient poisoned samples. Specifically, we use a weight-based contribution approach to calculate the contribution of each sample (clean sample and poisoned sample) during the training process from multiple dimensions. Finally, based on the greedy approach, we retain a subset of samples with the largest contribution in each dimension through iterations. We evaluate the effectiveness of MPS on various attack methods, including BadNet, Blended, ISSBA, and WaNet, as well as benchmark datasets. The experimental results on CIFAR-10 and GTSRB show that MPS can increase the attack strength by 1.45% to 18.34% compared to RSS and 0.43% to 10.84% compared to FUS in multiple-poisoned samples attacks, thereby enhancing the stealthiness of the attack. Meanwhile, MPS is suitable for black-box settings, meaning that poisoned samples selected in one setiing can be applied to other settings.

关键词： Backdoor attack Multiple poisoned samples Poisoning efficiency Optimization problem Stealthiness

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Balancing computing and networking in Autonomous Edge Clouds 22

Balancing Computing and Networking in Autonomous Edge Clouds

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22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Masuda, Shinnosuke Hasegawa, Tsuyoshi Shudo, Kazuyuki Cho, Kenjiro Kyoto University Japan Iij Japan

ISBN: (纸本)9798331508050

In the ever-changing environment of edge cloud systems, it is necessary to allocate diverse cloud resources in an efficient manner, at the same time, reducing energy consumption. A simple distributed resource allocation model is proposed in a previous study that utilizes a pseudo cost function of resource load, and it is shown that a convex function allows energy saving by pooling idle edge servers. In this paper, we extend this cost model beyond simple load, and present a method to balance computation and communication by merging multiple constraints into the cost function. We show trade-offs among soft constraints along with energy saving effects by simulation, using specific scenarios with computational and communication constraints. Our simulation results show that the combination of a convex function with a polynomial penalty function works well for balancing energy saving and other soft constraints. © 2025 IEEE.

关键词： Cost functions

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Privacy-Enhanced Content Discovery for Bitswap 22

Privacy-Enhanced Content Discovery for Bitswap

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22nd international-Federation-for-Information-Processing (IFIP) networking conference (IFIP networking)

作者： Daniel, Erik Tschorsch, Florian Techn Univ Berlin Distributed Secur Infrastructures Berlin Germany

ISBN: (纸本)9783903176577

IPFS is a content-addressed peer-to-peer data network, which follows the paradigm of information centric networking. In IPFS, data is exchanged with the Bitswap protocol. For content discovery, Bitswap queries all neighbors for the content, leaking the interest to all neighbors. In our paper, we develop three privacy-enhanced protocols for content discovery, which reduce the interest leak from all neighbors to ideally one content provider. Our protocols use probabilistic data structures like Bloom filter and cryptographic approaches like Private Set Intersection. We implement our protocols as proof of concept and show how they can be integrated into go-bitswap. Furthermore, we provide a performance, security, and privacy evaluation of the three protocols, showing their feasibility trade-offs.

关键词： P2P Overlay Network Information Centric networking IPFS Privacy

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