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检索条件"任意字段=IEEE International Conference on Distributed Computing in Sensor Systems"

共 30762 条记录，以下是81-90 订阅

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Assessing distributed Consensus Performance on Mobile Cyber-Physical System Swarms 19

Assessing Distributed Consensus Performance on Mobile Cyber-...

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Chen, Jiayi Vacheron, Maxime Ferreira, Bruno Chianca Silvestre, Guthemberg Univ Toulouse ENAC Toulouse France

ISBN: (纸本)9798350333398

Mobile Cyber-Physical System (CPS) Swarms are likely to change our daily lives significantly in several application domains, including smart cities, space exploration, environmental monitoring, and transporting systems. Yet, industrial projects fundamentally rely on centralized communication infrastructures which in turn lead to suboptimal performance and limited autonomy for both sensing and actuating. To enhance communication and distributed coordination within the swarm, reliable distributed computing through consensus protocols constitutes a promising approach. Nonetheless, only a handful of studies has considered evaluating reliable distributed computing in Mobile CPS Swarms. The goal of this work is to evaluate the performance of consensus protocols on CPS swarms with processing units deployed on mobile nodes. Running on top of an emulation framework for mobile CPS, our preliminary evaluation focuses on evaluating three key deployment aspects of Mobile CPS Swarms executing a consensus protocol: the effective cost of mobility;the impact of the connectivity of nodes and the eventual network partitions;and the price of continuous routing updates in the mobile environment. Our experimental results indicate the transient network partition in mobile environments are common. They also suggest that the sparsity of dynamic communication network and continuous routing updates have a major impact on the performance of distributed consensus protocols.

关键词： Fault-tolerant mobile computing distributed consensus Paxos Cyber-physical systems Swarm intelligence

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A Hybrid Machine Learning Intrusion Detection System for Wireless sensor Networks 20

A Hybrid Machine Learning Intrusion Detection System for Wir...

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20th ieee international Wireless Communications and Mobile computing (ieee IWCMC) - Green and Intelligent Communications

作者： Zhang, Hongwei Zaman, Marzia Jain, Achin Sampalli, Srinivas Dalhousie Univ Fac Comp Sci Halifax NS B3H 4R2 Canada Cistel Technol Res & Dev Ottawa ON K2E 7V7 Canada Norleaf Networks Res & Dev Gatineau PQ J8Y 2V5 Canada

ISBN: (纸本)9798350361261;9798350361278

Federated Learning (FL) has emerged as a novel distributed Machine Learning (ML) approach, to tackle the challenges associated with data privacy and overload in ML-based intrusion detection systems (IDSs). Drawing inspiration from the FL architecture, we have introduced a hybrid ML IDS tailored for Wireless sensor Networks (WSNs). This system is crafted to leverage ML for achieving a two-layer intrusion detection mechanism in WSNs free from constraints posed by specific attack types. The architecture follows a server-client model compatible with the configuration of sensor nodes, sink nodes, and gateways in WSNs. In this setup, client models located at sink nodes undergo training using sensing data while the server model at the gateway is trained using network traffic data. This two-layer training approach amplifies the efficiency of intrusion detection and ensures comprehensive network coverage. The results derived from our simulation experiments corroborate the effectiveness of the proposed hybrid ML IDS. It generates precise aggregation predictions and leads to a substantial reduction in redundant data transmissions. Furthermore, the system exhibits efficacy in detecting intrusions through a dual validation process.

关键词： Wireless sensor Networks Intrusion Detection System Network Security Hybrid Machine Learning Aggregation Prediction Algorithm Federated Learning Ensemble Learning

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Access Control based on CRDTs for Collaborative distributed Applications 22

Access Control based on CRDTs for Collaborative Distributed ...

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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： Rault, Pierre-Antoine Ignat, Claudia-Lavinia Perrin, Olivier Univ Lorraine CNRS INRIA LORIA F-54000 Nancy France

ISBN: (纸本)9798350381993;9798350382006

A key feature for most collaborative applications is their ability to distinguish access rights to shared documents in a dynamic group of collaborators. To achieve high availability and avoid single points of failure, systems can replicate this access control policy across sites. Increasingly, Conflict-free Replicated Data Types (CRDTs) are used to this end. They embed conflict resolution strategies that take into account concurrent modifications to the policy but also to the document that it manages. However, few systems in the literature support multiple administrators, and those which do fall short of considering distributed applications where no node or group of nodes is central to its operation. To allow multiple concurrent edits of the policy in massively collaborative settings with no central server, we devise a specialized causal model that minimizes concurrency. Crucially our model allows to correct the document state in case operations have become unauthorized following a policy change. We apply our model to a CRDT replicating an access control policy with read and write rights on a collaborative document and admin rights on the policy. We end by studying flexible conflict resolution strategies, providing our underlying algorithms.

关键词： distributed algorithms access control CRDT (Conflict-free Replicated Data Type) eventual consistency real-time collaborative editing

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Hierarchical Caching for Digital Twins Communications Over mURLLC-Based 6G distributed-computing Mobile Networks Using FBC 44

Hierarchical Caching for Digital Twins Communications Over m...

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

作者： Zhang, Xi Zhu, Qixuan Texas A&M Univ Networking & Informat Syst Lab Dept Elect & Comp Engn College Stn TX 77843 USA

ISBN: (纸本)9798350354720;9798350354713

The massive ultra-reliable and low-latency communications (mURLLC) services are emerging as a new traffic type to support massive numbers of mobile users (MUs) demanding the stringent delay and error-rate bounded quality-of-services (QoS) requirements over 6G. Among multiple 6G mURLLC services, digital twins (DT) has been widely envisioned as a major intelligent application to support efficient interactions between physical and virtual objects. Moreover, multi-tier caching, which is one of the key distributed computing techniques, stores the frequently-demanded data items at different wireless network tiers to efficiently reduce mURLLC streaming delay and data move. However, how to efficiently cache mURLLC-based DT data items at different caching tiers of wireless networks and how to statistically upper-bound both delay and error-rate for DT communications remain challenging problems. To overcome these difficulties, in this paper we propose a multi-tier caching mechanism to support DT communications over 6G mobile networks. First, we propose the DT data adaptive collection scheme applying finite blocklength coding (FBC) to dynamically encode a physical object into its virtual representation according to the current network and wireless channel statuses. Second, we develop inter-tier and intra-tier collaborative caching mechanisms, where DT data items are selectively cached at different wireless network caching tiers according to their popularities including: router tier, massive-multiple-input-multiple-output (MIMO) basestation tier, and mobile device tier. Third, our proposed intertier collaborative caching mechanisms maximize the aggregate epsilon-effective capacity across all three caching tiers, and our proposed intra-tier collaborative caching mechanisms minimize the sum of data transmission delay for all DT data items cached in each caching tier. Finally, we numerically validate and evaluate our developed multi-tier hierarchical caching schemes over 6G DT-enab

关键词： 6G mURLLC DT statistical delay and error-rate QoS bounded provisioning epsilon-effective capacity multi-tier caching distributed computing FBC

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Vehicle Routing Model to Avoid Street Congestions Using distributed systems 19

Vehicle Routing Model to Avoid Street Congestions Using Dist...

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Khorchani, Besma Sethom, Kaouthar Bouallegue, Ridha Univ Carthage SUP COM Innov COM Lab Ariana Tunisia Univ Tunis El Manar ENIT Tunis Tunisia

ISBN: (纸本)9798350333398

In large cities, road traffic congestion is a big concern especially with its negative effects on the economy and the environment. Hence, with the advance of the IoT and AI many smart solutions are proposed to deal with this problem. Yet, those solutions enclosed traffic congestion detection and light street manipulation. However, road jams still occur far away from street lights especially in rush hours and in unexpected situations such as accidents and extreme weather conditions. The aim of this study is to propose a solution that helps vehicles avoid traffic jams and congestions based on data analysis gathered from traffic sensors and from a publish-subscribe application integrated with a distributed system to give vehicle driver a real-time updates about the situation of his road traffic.

关键词： Traffic congestion smart city distributed systems IoT Machine Learning

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Energy performance of Internet of Things (IoT) networks for pipeline monitoring 20

Energy performance of Internet of Things (IoT) networks for ...

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20th ieee international Wireless Communications and Mobile computing (ieee IWCMC) - Green and Intelligent Communications

作者： Kuaban, Godlove Suila Czachorski, Tadeusz Gelenbe, Erol Pecka, Piotr Nkemeni, Valery Czekalski, Piotr Polish Acad Sci IITiS PAN Inst Theoret & Appl Informat Gliwice Poland Univ Buea Fac Engn & Technol Lab Elect Engn & Comp Buea Cameroon Silesian Tech Univ Fac Automat Control Elect & Informat Gliwice Poland

ISBN: (纸本)9798350361261;9798350361278

Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of Things (IoT), Wireless sensor Networks (WSNs), Artificial Intelligence (AI), distributed computing, and cloud computing enable continuous monitoring of pipelines to detect leakages and corrosion on the pipeline. The main challenge with using battery-powered sensor nodes to monitor pipelines is the energy constraint, necessitating frequent battery replacement. Thus, there is a need to develop energy-saving mechanisms to prolong the lifetime of these sensor nodes. In this paper, we use the diffusion approximation modelling framework in which the data from the experimental testbed are used to model the dynamics of the battery's energy content and to estimate the mean and variance of the device's lifetime. The novelty in the proposed diffusion model of the battery of an IoT node is the introduction of multiple energy thresholds that split the energy state-space of the battery into multiple energysaving regimes. As the battery discharges, the node gradually transitions into energy-saving regimes by reconfiguring some of its parameters to reduce energy consumption (sometimes at the cost of trading off some performance metrics). We investigate the impact of energy-saving regimes or the number of thresholds on the node's lifetime.

关键词： Green Internet of Things (IoT) energy performance diffusion models adaptive sensing distributed computing duty cycling

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Federated Deep Reinforcement Learning Approach for Real-Time Target Coverage in Wireless sensor Networks 21

Federated Deep Reinforcement Learning Approach for Real-Time...

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21st ieee international conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Glodek, Corey Thomas Siasi, Nazli Depaul Univ Coll Comp & Digital Media Chicago IL 60604 USA

ISBN: (纸本)9798350363999;9798350364002

Maximizing target coverage is crucial in wireless sensor networks (WSN), where sensor nodes collect data to monitor events or targets in specific areas. Efficient coverage optimization involves deploying sensors to cover the entire monitored region, addressing the NP-hard nature of the problem. Various algorithms, including learning-based automata, genetic algorithms, and probabilistic approaches, have been employed. Specifically, deep reinforcement learning (DRL), using deep neural network (DNN) as a predictor, has shown promise. However, the DRL models require a large amount of data for training, which may limit their adaptability to the ever-evolving statistics of the underlying environment. Moreover, wireless networks are inherently distributed systems, where centralized DRL approaches would require excessive data exchange, while fully distributed approaches may result in slower convergence rates and performance degradation. To overcome these challenges, we propose a novel federated learning (FL) approach to Deep Q-Network (DQN), called Federated Reinforcement Deep Q-Network (FEDQN), which allows sensors to collaboratively train the DQN by sharing only model weights, not training data. This paper demonstrates how FEDQN maximizes target coverage in a continuous, partially observable visual sensor network environment, simulating traffic flow with mobile targets.

关键词： Deep learning Federated Learning Reinforcement Learning Target coverage Wireless sensor networks

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Sensing Together: Cooperative Task Adaptation and Scheduling for IoT-Nets using Renewable Energy 21

Sensing Together: Cooperative Task Adaptation and Scheduling...

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21st ieee international conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Liri, Elizabeth Ramakrishnan, K. K. Kar, Koushik Esposito, Flavio Univ Calif Riverside Dept Comp Sci & Engn Riverside CA 92521 USA Rensselaer Polytech Inst Elect Comp & Syst Engn Dept Troy NY USA St Louis Univ Comp Sci Dept St Louis MO 63103 USA

ISBN: (纸本)9798350363999;9798350364002

IoT devices used in various applications, such as monitoring agricultural soil moisture, or urban air quality assessment, are typically battery-operated and energy-constrained. We develop a lightweight and distributed cooperative sensing scheme that provides energy-efficient sensing of an area by reducing spatio-temporal overlaps in the coverage using a multi-sensor IoT network. Our "Sensing Together" solution includes two algorithms: distributed Task Adaptation (DTA) and distributed Block Scheduler (DBS), which coordinate the sensing operations of the IoT network through information shared using a distributed "token passing" protocol. DTA adapts the sensing rates from their "raw" values (optimized for each IoT device independently) to minimize spatial redundancy in coverage, while ensuring that a desired coverage threshold is met at all points in the covered area. DBS then schedules task execution times across all IoT devices in a distributed manner to minimize temporal overlap. On-device evaluation shows a small token size and execution times of less than 0.6s on average while simulations show average energy savings of 5% per IoT device under various weather conditions. Moreover, when devices had more significant coverage overlaps, energy savings exceeded 30% thanks to cooperative sensing. In simulations of larger networks, energy savings range on average between 3.34% and 38.53%, depending on weather conditions. Our solutions consistently demonstrate near-optimal performance under various scenarios, showcasing their capability to efficiently reduce temporal overlap during sensing task scheduling.

关键词： multi-sensor IoT distributed scheduler energy efficiency task adaptation cooperative sensing comb placement problem

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Impedance Sensing-Centered Pervasive and Wearable Activity Recognition on Edge Devices

Impedance Sensing-Centered Pervasive and Wearable Activity R...

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ieee international conference on Pervasive computing and Communications (PerCom)

作者： Liu, Mengxi German Res Ctr Artificial Intelligence DFKI D-67663 Kaiserslautern Germany RPTU Kaiserslautern Landau Dept Comp Sci D-67663 Kaiserslautern Germany

ISBN: (纸本)9798350304367;9798350304374

Recent years have seen significant advancements in sensor-based pervasive and wearable activity recognition, primarily through the development of novel sensing modalities and the application of advanced machine learning algorithms. Despite this progress, the potential of impedance sensing in daily-life scenarios for pervasive and wearable activity recognition remains underexplored, particularly in contrast to its successful application in industrial and labor areas. Additionally, there is a lack of comprehensive studies on end-to-end optimization strategies from sensor to model, aimed at reducing both input and computational complexity of the neural network model, enabling it to not only run but also update efficiently on edge devices. This research project aims to bridge these gaps by investigating impedance sensing as a core technology for pervasive and wearable activity recognition in everyday environments and studying sensor-data-model co-optimization pipeline to enhance the performance and efficiency of these systems on edge devices.

关键词： impedance sensing activity recognition sensor fusion edge-computing

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AirDnD - Asynchronous In-Range Dynamic and distributed Network Orchestration Framework 43

AirDnD - Asynchronous In-Range Dynamic and Distributed Netwo...

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43rd ieee international conference on distributed computing systems (ICDCS)

作者： Dona, Malsha Ashani Mahawatta Berger, Christian Yu, Yinan Univ Gothenburg Gothenburg Sweden Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9798350339864

The increasing usage of IoT devices has generated an extensive volume of data which resulted in the establishment of data centers with well-structured computing infrastructure. Reducing underutilized resources of such data centers can be achieved by monitoring the tasks and offloading them across various compute units. This approach can also be used in mini mobile data ponds generated by edge devices and smart vehicles. This research aims to improve and utilize the usage of computing resources in distributed edge devices by forming a dynamic mesh network. The nodes in the mesh network shall share their computing tasks with another node that possesses unused computing resources. This proposed method ensures the minimization of data transfer between entities. The proposed AirDnD vision will be applied to a practical scenario relevant to an autonomous vehicle that approaches an intersection commonly known as "looking around the corner" in related literature, collecting essential computational results from nearby vehicles to enhance its perception. The proposed solution consists of three models that transform growing amounts of geographically distributed edge devices into a living organism.

关键词： Data transfer

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