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

共 30780 条记录，以下是1231-1240 订阅

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distributed Explicit State Space Exploration with State Reconstruction for RDMA Networks 26

Distributed Explicit State Space Exploration with State Reco...

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26th international conference on Engineering of Complex Computer systems (ICECCS)

作者： Evangelista, Sami Petrucci, Laure Kristensen, Lars Michael Univ Sorbonne Paris Nord LIPN CNRS UMR 7030 99 Av JB Clement F-93430 Villetaneuse France Western Norway Univ Appl Sci Fac Engn & Sci Inndalsveien 28 N-5020 Bergen Norway

ISBN: (纸本)9781665401623

The inherent computational complexity of validating and verifying concurrent systems implies a need to be able to exploit parallel and distributed computing architectures. We present a new distributed algorithm for state space exploration of concurrent systems on computing clusters. Our algorithm relies on Remote Direct Memory Access (RDMA) for low-latency transfer of states between computing elements, and on state reconstruction trees for compact representation of states on the computing elements themselves. For the distribution of states between computing elements, we propose a concept of state stealing. We have implemented our proposed algorithm using the OpenSHMEM API for RDMA and experimentally evaluated it on the Grid'5000 testbed with a set of benchmark models. The experimental results show that our algorithm scales well with the number of available computing elements, and that our state stealing mechanism generally provides a balanced workload distribution.

关键词： Computational modeling Clustering algorithms Computer architecture Benchmark testing Explosions Space exploration Low latency communication

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A Novel distributed Context-Aware Radio Access Technology Selection Scheme For C-ITS Networks 18

A Novel Distributed Context-Aware Radio Access Technology Se...

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18th ieee international Wireless Communications and Mobile computing conference (IWCMC)

作者： Karoui, Mouna Mamadou, Ali Mamadou Chalhoub, Gerard Univ Clermont Auvergne CNRS LIMOS Clermont Ferrand France

ISBN: (纸本)9781665467490

Improving network performances to better support Cooperative Intelligent Transport systems (C-ITS) services has been the subject of renewed efforts by academia and industry. To this end, the availability of multiple in-vehicle radio access technologies (RATs) has been exploited. In this paper, we propose a distributed and Context Aware Radio access Technology selection (DICART) framework for vehicular networks, formulated as Multi-Criteria Decision-Making (MCDM) problem. A validation methodology is then conducted based on OMNET++ full-stack network simulator to prove the effectiveness of DI CART. Results show the benefits of our proposal under low and high density network configurations, in enhancing network performance perceived by end-users while considering the needs and constraints of used services.

关键词： C-ITS RAT selection LTE-V2X (mode 4) ITS-GS MCDM

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Integral AI-based planning for management of WSNs in military operations 35

Integral AI-based planning for management of WSNs in militar...

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35th ieee international conference on Tools with Artificial Intelligence (ICTAI)

作者： Caballero, J. Perez-Mon, Olaya R-Moreno, Maria D. de Oliveira Filho, Julio Univ Alcala ISG Alcala De Henares Spain TNO The Hague Netherlands Univ Alcala Alcala De Henares Spain TNO IAS The Hague Netherlands

ISBN: (纸本)9798350342734

Military tactical scenarios have been shifting to more often consider combat situations in urban environments. Threats in these environments are generally more dynamic in nature, imposing new requirements on sensors and communications systems that support military operations. Wireless sensor networks (WSNs) with a large number of small and mobile computing nodes became the typical solution. However, WSNs demand additional complexity to dynamically manage their tasks, resource allocation, mobility, power consumption, and communication. This paper illustrates the integration of AI techniques into a Battle Management System (BMS) to support military operations in urban environments. The BMS is enhanced with an AI-based planner able to plan tasks, allocate resources, and monitor the WSN operation. The planner takes into consideration energy harvesting capabilities, secure data transfer, and authorization procedures. It generates plans using the information received from the sensors. In case new situations emerge, based on data fusion information, it automatically replans to adapt to the uncertainty in the environment. Finally, it takes into account the coverage between the different components to optimize the communications and better support WSN's operator(s) and their activities.

关键词： AI planning Replanning Goal Reasoning Data Fusion WSN sensor Data

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FedMC: Federated Learning with Mode Connectivity Against distributed Backdoor Attacks

FedMC: Federated Learning with Mode Connectivity Against Dis...

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ieee international conference on Communications (ieee ICC)

作者： Wang, Weiqi Zhang, Chenhan Liu, Shushu Tang, Mingjian Liu, An Yu, Shui Univ Technol Sydney Sch Comp Sci Sydney NSW Australia Nokia Bell Labs Espoo Finland Soochow Univ Sch Comp Sci Suzhou Peoples R China

ISBN: (纸本)9781538674628

Federated learning (FL) has become a hot research domain due to its privacy protection for model collaboratively training in edge computing systems. However, recent studies indicated that most FL algorithms have desperately suffered from backdoor attacks. Although many backdoor defence FL algorithms were proposed, their effects were highly related to the ratio of malicious clients (RMC) of all participated edge nodes. To be more specific, most of them only set RMC around 10% to 30% in their experiments, and their results also showed that the rate of successful backdoor defence seriously drops when RMC increases. In the paper, we propose a novel federated learning scheme with mode connectivity (FedMC) to defend against backdoor attacks, mitigating the sharp defence effect degradation as RMC increases. Conventional mode connectivity mainly focuses on training a connecting curve between two end models, which is inapplicable in distributed multiple clients FL situations. We extend the two-ends mode connectivity to multi-ends by introducing a scalable regularization term consisting of the edge clients' models to involve their knowledge in the connective model training. In each communication round, the FL-Server aggregates and absorbs the contribution of clients by training a connective model based on a small set of clean samples, which builds a pathway to accurately connect all edge clients' models and mitigates the backdoor triggers of models. Extensive experiments and results demonstrate that FedMC can effectively defend against backdoor attacks while maintaining the accuracy on untampered test data.

关键词： Federated Learning Poinson attacks Backdoor Mode Connectivity

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On the Security of Privacy-preserving Data Aggregation Scheme Based on CRT in Mobile Crowdsensing System 15

On the Security of Privacy-preserving Data Aggregation Schem...

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15th international conference on Cyber-Enabled distributed computing and Knowledge Discovery, CyberC 2023

作者： Zhang, Jianhong Zhang, Jianan Lv, Zongyi Zhang, Ruxuan North China University of Technology School of Information Science and Technology Beijing China

ISBN: (纸本)9798350308693

Mobile Crowd Sensing (MCS) is an innovative technology that ensuring data security and privacy is critical to encouraging user participation and maintaining system reliability. Zhu et al. proposed a privacy-preserving data aggregation scheme based on the Chinese Remainder Theorem, claiming that the scheme can ensure data integrity and tamper resistance. However, our analysis shows that their scheme does not achieve the expected level of security because attackers can forge signatures and tamper with data. We elaborate on possible attacks on the scheme and propose an improved solution to provide stronger security measures for sensor networks, including integrity, authentication, non-repudiation and privacy protection. Our scheme effectively prevents signature forgery, data tampering and replay attacks, and provides higher security and reliability than previous schemes. With our efficient, scalable and flexible solution, we can significantly improve the data security of mobile crowd sensing technology and encourage users to actively participate in data collection tasks. © 2023 ieee.

关键词： sensor networks

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Performance Analysis of Leach and Pegasis Routing Protocols in a Wireless sensor Networks for Smart Water Quality Monitoring 15

Performance Analysis of Leach and Pegasis Routing Protocols ...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Anjali, S.V. Paul, Binu Dhanya, S. Pradeep, Anju Cochin University of Science and Technology Division of Electronics Engineering School of Engineering Kerala Kochi22 India Muthoot Institute of Technology and Science Department of Electronics and Communication Engineering Kerala Kochi India

ISBN: (纸本)9798350370249

In the aquaculture industry, maintaining optimal water quality is imperative for the health and productivity of aquatic species such as prawns and pearl spot fish. Wireless sensor Networks (WSNs) have emerged as a promising technology for real-time water quality monitoring in aquaculture settings due to their cost-effectiveness, scalability, and ability to provide continuous data collection. In this paper we present a comprehensive comparison between two prominent routing protocols, Low Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient GAthering in sensor Information systems (PEGASIS) for water quality monitoring. The primary focus is on evaluating their performance in terms of energy efficiency and network lifetime. The performance analysis is conducted through simulations using the MATLAB, considering parameters relevant to the aquaculture environment such as energy efficiency, data aggregation and network lifetime. Our findings reveal the distinct advantages and limitations of both LEACH and PEGASIS in the context of smart aquaculture. LEACH demonstrates superior energy efficiency and scalability through its clustering mechanism, making it suitable for large-scale deployments. © 2024 ieee.

关键词： aquaculture industry energy efficiency LEACH network life time PEGASIS

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A sensor-Based Smart Urban Flood Warning and Management System 4

A Sensor-Based Smart Urban Flood Warning and Management Syst...

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4th international conference on Information Science, Parallel and distributed systems, ISPDS 2023

作者： Song, Sunyang Deng, Xue Gao, Chao College of Engineering China Agricultural University Beijing China

ISBN: (纸本)9798350337181

In recent years, the rapid global climate change has resulted in frequent urban flooding disasters. The phenomenon of blocked drain covers in urban areas directly affects the passage of vehicles and pedestrians, causing inconvenience to citizens' travel. In severe cases, it can even submerge vehicles, leading to casualties and posing a serious threat to public safety and property. To address this issue, we propose a smart urban flood warning and management system. The system installs terminal devices on rainwater grates along the roadsides. When the water level on the road reaches a certain depth, pressure sensors are used to acquire the water level information, which is then uploaded to the server. The system provides realtime and accurate feedback on urban flooding conditions, demonstrating broad prospects for the prediction and control of urban flooding disasters. © 2023 ieee.

关键词： Water levels

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Congestion-aware Optimal Data rate Selection for Efficient Routing in Wireless Rechargeable sensor Network 3

Congestion-aware Optimal Data rate Selection for Efficient R...

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3rd international conference on Advances in computing, Communication, Embedded and Secure systems, ACCESS 2023

作者： Susan T, Siron Anita Nithya, B. Ameen, Abdulla Rajkumar, Sarvesh National Institute of Technology Computer Science and Engineering Tiruchirappalli India

ISBN: (纸本)9798350346169

Wireless Rechargeable sensor Nodes (WRSNs) are widely used to sense, collect, and process data or signals transmitted among people, the environment, and computer systems. However, it faces severe threats such as congestion, resource deprivation, security risk, limited communication speed, high cost, limited bandwidth, and so on. To address some of these issues and to improve the QoS, this paper proposes an Adaptive Rate Determined Congestion Management (ARDCM) approach. It adopts a feedback-based system in which the incoming data rate is managed to increase when congestion is low and decrease when congestion is high. It guarantees congestion free data flow between upstream and downstream in data communication by controlling the data rate and buffer occupancy. The proposed approach is simulated on NS2 with varying numbers of active nodes in a simulated environment. The proposed model's performance is evaluated by comparing the Packet Delivery Ratio(PDR), Packet Loss Ratio(PLR), delay, and throughput to the existing algorithms. © 2023 ieee.

关键词： sensor nodes

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Towards Smart distributed Robotics Solution using Digital Twin 14

Towards Smart Distributed Robotics Solution using Digital Tw...

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14th ieee international conference on Power Electronics and Drive systems, PEDS 2023

作者： Melancon, Cedric Kaur, Kuljeet Gascon-Samson, Julien Saad, Maarouf École de Technologie Supérieure Montréal Canada

ISBN: (纸本)9798350399967

The global COVID-19 pandemic has put a strain on the healthcare system, further compounded by the aging population and the staffing shortage. As a result, the demand for healthcare exceeds the available offer, and health professionals are forced to compensate the best they can. On the other hand, some tasks can easily be offloaded to robots. Some solutions already exist, but they are not necessarily scalable, and exhibit a very high price point. This paper outlines our vision of a new distributed robotics approach to mitigate these constraints. We propose a prototype of an autonomous robot to assist healthcare professionals (e.g., nurses) in their work - for instance, by gathering equipment and delivering water and food to give them more time for human-centric tasks. The solution incorporates the ideas of cloud-fog-edge robotics to enable AI-based control with digital twin notions to help with the training. Preliminary work is introduced on the robot platform and the framework to facilitate communication at every infrastructure layer. © 2023 ieee.

关键词： Fog computing

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Framework of Occupant-Centric Measuring System for Personalized Micro-environment via Online Modeling 12th

Framework of Occupant-Centric Measuring System for Personali...

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12th international conference on distributed, Ambient and Pervasive Interactions (DAPI)

作者： Tak, Mohammad Saleh Nikoopayan Feng, Yanxiao New Jersey Inst Technol Hillier Coll Architecture & Design Newark NJ 07102 USA New Jersey Inst Technol Sch Appl Engn & Technol Newark NJ 07102 USA

ISBN: (纸本)9783031600111;9783031600128

Indoor environmental comfort has become increasingly important, necessitating occupant-centric systems that provide personalized comfort. This trend is particularly notable in light of the increasing frequency of extreme weather events associated with global climate change. This paper proposes a novel framework integrating real-time occupant feedback, multi-sensor data fusion, online modeling, and intelligent sensor technologies to dynamically tailor indoor microenvironments. The framework collects diverse data on built environment and personal health using environmental sensors and wearable devices. It employs online machine learning algorithms to analyze the database and automatically adjust environmental conditions in real-time to match occupants' preferences. In implementing this framework, advanced encryption are utilized to enable swift, localized data processing while preserving privacy. Multi-sensor fusion techniques are leveraged to integrate heterogeneous sensor data into an accurate assessment of occupant comfort. The user interface facilitates occupant feedback to continuously refine the system's reinforcement learning model. By personalizing comfort in a responsive, privacy-aware manner, this framework is expected to enhance occupant well-being and satisfaction, potentially enabling significant energy savings by avoiding overcooling and overheating. The framework represents an innovative application of smart and computing technologies, including deep learning and data fusion, to advance beyond static environmental setpoints. In anticipation of testing, it shows promise in revolutionizing occupant-centric comfort, fostering the creation of more adaptive and resilient indoor spaces.

关键词： Real-time modeling Multi-sensor fusion Adaptive adjustment

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