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

共 30763 条记录，以下是41-50 订阅

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AI-Integrated sensor Data Analytics for Real-Time Decision-Making in Wireless sensor Networks 2

AI-Integrated Sensor Data Analytics for Real-Time Decision-M...

引用

2nd international conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Wasim Haidar, S.K. Wilfred Blessing, N.R. Chaubey, Sudhakar Kumar Mehmood, Zahid Kavitha, S.J. Sutherlin Subitha, G. College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Oman Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Tamil Nadu Chennai India Stella Mary's College of Engineering Department of Computer Science and Engineering Aruthenganvilai India

ISBN: (纸本)9798331505745

The study compares the performance of Wireless sensor Networks (WSNs) with 20, 30, 40, and 50 nodes in real-time AI-enhanced sensor analytics using the AODV routing protocol. All configurations showed a consistent Packet Delivery Ratio (PDR) of 100%. However, the end-to-end delay increased slightly from 0.2 sec (20 nodes) to 0.3 sec (30, 40, 50 nodes), indicating that larger networks result in longer paths. Throughput decreased from 2560 bps at 20 nodes to 1706.67 bps in larger configurations, probable due to network congestion. Energy efficiency also decreased as the number of nodes increased, suggesting higher energy consumption per transmission. © 2025 ieee.

关键词： sensor nodes

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Enabling Intelligent Observability Volume Management 17

Enabling Intelligent Observability Volume Management

引用

17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Naik, Priyanka Goel, Seep Raichstein, Eran Meth, Kalman Govindarajan, Kavya Chakraborty, Aishwariya Govindarajan, Chander IBM Research Bangalore India IBM Research Haifa Israel

ISBN: (纸本)9798331531195

In the era of centralized clouds, multi-cloud, and edge computing, adaptable observability is essential to efficiently manage the growing volume of metrics data. Observability Volume Manager (OVM) addresses the complexities of dynamic observability data management by offering tailored processing capabilities that ensures efficient and effective observability across diverse infrastructures. This demo highlights OVM's ability to perform dynamic transformations for fine-grained control over observability data collection, while significantly reducing the volume of data collected, processed, and stored. These optimizations drive substantial cost savings and position OVM as an essential solution for cost-efficient observability. © 2025 ieee.

关键词： distributed cloud

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Enhancing Tactile sensor Technology with Neuromorphic Models and Machine Learning 6

Enhancing Tactile Sensor Technology with Neuromorphic Models...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Lenka, Komali Jyothi, Pulaparthi Lakshmi Asha Brahma Ramesh, Kallakuri N.V.P.S. Lanka, Dasaradha Ramayya Srikanth, M. Rajesh, Jonnapalli Tulasi Dept of IT S.R.K.R.Engineering College India India AP Bhimavaram India Dept of Artificial intelligence and Machine learning Aditya University India Dept of IT SRKR Engineering College Bhimavaram India

ISBN: (纸本)9798331522667

This study presents a novel approach to enhancing touch sensor technology by utilizing machine learning techniques and neuromorphic models. Tactile sensing has struggled to accurately understand complex physical interactions, despite its significance for artificial touch and robotic dexterity. Our approach improves the classification of tactile data by using neuromorphic computing—models inspired by brain processing—to identify changes in the environment, variations in force, and textures. We evaluate our model on benchmark tactile datasets and demonstrate its superior sensory resolution and increased adaptability. For robotics, prosthetics, and human-machine interfaces, the results are very important because they show that neuromorphic tactile sensors improve the accuracy and speed of data classification. This study showcases the potential of neuromorphic models to improve tactile perception, paving the way for more advanced and adaptable sensory systems. © 2025 ieee.

关键词： Prosthetics

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Design and Implementation of Real-Time Wireless sensor Network Protocols with Relay Nodes and Localization Methods for Efficient System Performance

Design and Implementation of Real-Time Wireless Sensor Netwo...

引用

2025 international conference on Intelligent Control, computing and Communications, IC3 2025

作者： Balan, Gunapriya Pandey, Garima Sirisha, N. Ziara, Sajjad Thethi, H. Pal Alekhya, Juttiga New Horizon College of Engineering Department of Electrical and Electronics Engineering Bangalore India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Lovely Professional University Phagwara India Griet Department of Information Technology Telangana Hyderabad India

ISBN: (纸本)9798331527495

In this research paper we focus on the design and implementation of reliable real time wireless sensor network (WSN) protocols that make use of relay node and proper localization techniques to enhance the performance of the system in real time applications. However, Wireless sensor Networks (WSNs) offer a very important application in environmental monitoring, industrial control, and smart cities. Maintaining efficient communication protocols and accurate real time localization of sensor nodes, especially in environments with dynamic topologies, is one of the key challenges. This paper presents a robust WSN protocol with relay nodes which achieve both energy efficiency and communication efficiency. Additionally, it examines specialized localization algorithms for use in real time systems that offer enhanced localization precision without sacrificing system performance. Results show the reliability, scalability and energy efficiency of WSNs if utilized in real time applications can be highly improved using the optimized protocols that are coupled with localization techniques. © 2025 ieee.

关键词： Wireless sensor networks

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distributed Photovoltaic Power Forecasting Considering Perceived Data Quality

Distributed Photovoltaic Power Forecasting Considering Perce...

引用

2025 international conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

作者： Liu, Xiaodan Hou, Chunlei Du, Lishi Beijing FibrLINK Communications Co. Ltd. Beijing China

ISBN: (纸本)9798331506797

In distributed photovoltaic (PV) power generation systems, data quality plays a critical role in the accuracy of predictive models. However, the complexity of distributed PV sensor data, including issues such as missing values, noise and anomalous bias, often leads to data quality degradation, which seriously affects the reliability of the prediction. To address these challenges, this study proposes a novel forecasting method that integrates sensor data quality into the forecasting process to improve the reliability and robustness of forecasts. The method starts with a detailed analysis of distributed PV sensor data characteristics to identify patterns of data quality degradation and their impact on forecast accuracy. Data recovery algorithm based on adaptive mean drift clustering with multi-paradigm optimisation is presented to effectively deal with data loss and reduce noise. In addition, an adversarial graphical neural network (GNN) is used for knowledge migration and spatio-temporal correlation modelling to make accurate predictions even in the presence of perceived data quality degradation. The GNN framework exploits spatial dependence and temporal dynamics to create robust prediction models. Simulation results show that the proposed method significantly improves the data quality and prediction accuracy of distributed PV power generation, providing a reliable basis for decision making in energy management systems. © 2025 ieee.

关键词： adaptive mean drift clustering component distributed photovoltaic generation perceived data quality spatio-temporal correlation modeling style

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Analyzing Data Traffic in IoT Networks: A Novel Graph-Based Architecture 5th

Analyzing Data Traffic in IoT Networks: A Novel Graph-Based ...

引用

5th international conference on computing and Network Communications, CoCoNet 2023

作者： George, Gemini Department of Computer Applications St. George’s College Aruvithura Erattupetta Kerala Kottayam686122 India

ISBN: (纸本)9789819745395

The rapid deployment of IoT networks in different industrial services has caused the emanation of a huge volume of data from sensors and monitors. The efficient analysis and compact representation of the big data generated are critical to managing its transfer, storage, and latency. In this work, we propose a novel graphical model that has the flexibility to adapt to different architectural features of distributed IoT systems with low-power sensors. Further, we consider the traffic load minimization problem in the network and map the problems of network coverage and clustering onto the graph to find an optimal distributed network structure that minimizes the traffic load. The proposed approaches are tested under different network conditions, and the simulation results emphasize the improved performance of the method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph based architecture IoT Network construction sensor network

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Intrusion Detection System To Counter Sybil Attacks In Underwater Wireless sensor Networks Using Isolation Forest 5

Intrusion Detection System To Counter Sybil Attacks In Under...

引用

5th international conference on Emerging systems and Intelligent computing, ESIC 2025

作者： Mandal, Anindita Chatterjee, Pinaki Sankar Kalinga Institute of Industrial Technology School of Computer Engineering Bhubaneswar India

ISBN: (纸本)9798331522100

Underwater Wireless sensor Networks (UWSNs) are increasingly deployed in maritime and environmental monitoring, data gathering, and underwater communication. However, their unique characteristics - limited bandwidth, high latency, and energy constraints - make UWSNs highly susceptible to security threats, particularly the Sybil attack. In a Sybil attack, a malicious node forges multiple identities, compromising network integrity and leading to false data propagation and resource exhaustion. This paper proposes an Intrusion Detection System (IDS) that leverages the Isolation Forest algorithm to counter Sybil attacks in UWSNs. By analyzing node behavior, the proposed IDS identifies anomalies that correspond to Sybil nodes. The Isolation Forest algorithm is well-suited for this purpose due to its unsupervised nature and efficiency in detecting outliers, making it ideal for the constrained environment of UWSNs. Experimental results show that the proposed IDS effectively identifies Sybil nodes with high accuracy and low computational overhead, enhancing network security without compromising performance. This approach represents a significant advancement in safeguarding UWSNs against malicious intrusions, enabling more secure and reliable underwater operations. © 2025 ieee.

关键词： Network intrusion

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Chernobyl-Inspired Optimization for Efficient Wireless sensor Network Routing 5

Chernobyl-Inspired Optimization for Efficient Wireless Senso...

引用

5th international conference on Emerging systems and Intelligent computing, ESIC 2025

作者： Garima Rani, Amita Kumar, Sanjay Dcrust Computer Science and Engineering Department Murthal Sonepat India Sgt University Computer Science and Engineering Department Gurugram India

ISBN: (纸本)9798331522100

Optimising routing in Wireless sensor Networks (WSNs) is crucial for enhancing their performance, with a focus on energy conservation, reliable data transmission, and network stability. This research presents a unique approach to WSN routing optimization using Chernobyl Disaster Optimization (CDO), a nature-inspired algorithm modeled on the rehabilitation and ecological restoration efforts following the Chernobyl incident. CDO simulates the process of resource redistribution and recovery after a catastrophic event to identify optimal routing paths in WSNs. The study assesses the CDO algorithm's effectiveness against the traditional Gravitational Search Algorithm (GSA) using key performance indicators such as energy usage, jitter, average end-to-end delay (EED), packet loss, and packet delivery fraction (PFD). Simulation results show that the CDO-based routing optimisation method consistently surpasses GSA, delivering improved end-to-end delay, decreased jitter, reduced packet loss, and enhanced energy efficiency. This investigation highlights CDO's potential as a viable alternative to conventional optimisation techniques, offering a more efficient and adaptable solution for WSN routing optimisation, particularly in dynamic, large-scale scenarios. © 2025 ieee.

关键词： Energy efficiency

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Developing Scalable and Fault Tolerant distributed Architecture for Big Unstructured Data systems 6

Developing Scalable and Fault Tolerant Distributed Architect...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Saranya, G. Kumaran, K. Pratheep, V. Dhanush, S.R. School of Computer Science and Engineering Vellore Institue of Technology Chennai India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522667

In the era of big data, efficiently processing and retrieving insights from unstructured data presents a critical challenge. This paper introduces a scalable leader-worker distributed data pipeline designed to handle large sets of unstructured data blobs. Leveraging data parallelism, the system distributes workload across worker nodes, ensuring high performance for embarrassingly parallel tasks with minimal inter-process communication. Fault tolerance is achieved through an optimized next-in-line leader re-election strategy, addressing cascading failures and mitigating the thundering herd effect. The use of Apache Zookeeper for service discovery ensures seamless coordination within the cluster while maintaining a loosely coupled architecture for enhanced scalability. Google Protocol Buffers are employed for secure data transmission, offering tamper resistance against eavesdropping and man-in-the-middle attacks. The system also integrates the TF-IDF algorithm for efficient information retrieval, demonstrating the ability to achieve data parallelism while preserving task uniformity across nodes. Performance evaluation highlights significant reductions in response times with increasing cluster size, validating the system’s scalability, efficiency, and robustness. The proposed architecture is well-suited for real-world applications requiring secure, fault-tolerant, and scalable solutions for unstructured data analysis. © 2025 ieee.

关键词： Big data

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Design of a Scaled-Vehicle Research Platform for Software-Defined Vehicles

Design of a Scaled-Vehicle Research Platform for Software-De...

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11th international conference on Mechatronics and Robotics Engineering, ICMRE 2025

作者： Oh, Sung Bhin Do, Young Soo Lim, Se Jeong Choi, Hyeok Jun Cha, Sung Keun Hong, Hyeong Keun Lim, Seong Hyeon Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798331509293

Modern vehicles are integrated systems of complex software that support advanced features such as autonomous driving and over-the-air updates. Software-defined vehicles (SDVs) are emerging as a future automotive paradigm for managing increasing software complexity by centralizing computing resources and enabling flexible software updates and feature deployment. However, most SDV research is conducted in simulation environments because using real vehicles presents many challenges, including high cost, safety concerns, and implementation difficulties. In this paper, we present the design of an SDV research platform using a 1/5-scale vehicle model to overcome these limitations of SDV research. The platform implements a zone architecture and integrates various embedded systems to replicate the distributed computing environment of a modern vehicle. The platform allows researchers to experiment with different SDV concepts such as distributed computing, OTA updates, middleware, and vehicle software management without the constraints of full-scale vehicle testing. Our design demonstrates the feasibility of using extended vehicles for SDV research and provides insights into platform design for SDV research. © 2025 ieee.

关键词： distributed cloud

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