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

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Secure Skyline Groups Queries on Encrypted Data on Cloud Platform 23

Secure Skyline Groups Queries on Encrypted Data on Cloud Pla...

引用

23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Teng, Yiping Sun, Yue Shi, Zhan Jiang, Dongyue Zhao, Liang Fan, Chunlong School of Computer Shenyang Aerospace University Liaoning Large-scale Distributed System Laboratory Shenyang China

ISBN: (纸本)9781665494571

As an important category of skyline queries, the skyline groups query has drawn growing interest from the academic communities. For taking the benefit of cost savings, data owners are motivated to outsource the data storage and query processing to the public cloud to offload the massive data management. However, direct outsourcing may raise severe privacy issues. In this paper, we define and study the secure skyline groups query problem, and propose the secure skyline groups query methods. To address this problem, we first propose the Basic Secure Skyline Groups Query (BSSGQ) method to find the skyline groups on encrypted data. In BSSGQ method, candidate groups and their aggregate tuples are generated under encryption. To calculate group dominance relations, we propose a secure group dominance protocol to facilitate the dominance computation between groups. With the dominance relations, the skyline groups w.r.t the query group can be obtained, and finally the query results of the skyline groups can be securely returned without being learnt by the cloud servers. To address the efficiency problem in BSSGQ method, we further propose a Dynamic-programming-based Secure Skyline Groups Query (DSSGQ) method to effectively avoid generating the candidate groups. In DSSGQ method, the encrypted data are equivalently mapped based on the query group as the preprocessing to achieve a dynamic skyline groups query. Then, DSSGQ method dynamically constructs and calculates the skyline sub-groups in ciphertext, and the final skyline groups can be combined with the obtained skyline sub-groups. Thorough analysis shows the security and complexity of the proposed methods, and extensive experimental results on real datasets and synthetic datasets illustrate the performance of our proposed methods. © 2021 ieee.

关键词： Cloud computing Privacy Protocols Smart cities Query processing Memory Complexity theory

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Privacy-Preserving AI: Leveraging Federated Reinforcement Learning in distributed systems

Privacy-Preserving AI: Leveraging Federated Reinforcement Le...

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2024 international conference on Electrical, Electronics and computing Technologies, ICEECT 2024

作者： Mehta, Shiva Aneja, Aseem Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact & Outcome Punjab India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India

ISBN: (纸本)9798350378092

Organizing computing distributed resources in conjunction with machine learning algorithms in the age of big data is critical. This paper presents the FRL approach that combines Federated Learning and Reinforcement Learning to address problems in scale, speed, and data privacy. The overall framework of the Federated Reinforcement Learning (FRL) model bestows the use of distributed computing at different agents to train a standard RL model. This framework guarantees data privacy utilizing differential privacy and secure multi-party computation (SMPC). Quantitative analysis proves the proposed FRL framework retrieves a better result than a standard RL strategy implemented in the central controller. In the 100th episode of the study, the authors' FRL framework had better results than the centralized RL approach in autonomous navigation, resource management and game-playing. Thus, the FRL framework gained a total benefit of 95 cumulative. 6, 98. 4, and 98. 3, and the rewards obtained for the centralized RL approach were 90. 5, 92. 0, and 93. 8, respectively. Also, there was lower communication overhead about the generic FRL framework, where the assessment was recorded at 33. At the same time, 100 parameter exchanges were performed;the decentralized RL method was measured at 6 units, while the centralized RL method was measured at 41. 3 units. The joint plot analysis established that the traditional FRL framework training strategy offers quicker convergence and heightened model robustness, as the collaborative training approach provides. The heatmap visualization confirms the enhancement of the capability to control the communication overhead. © 2024 ieee.

关键词： Federated learning

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Dynamic Uploading Scheduling in mmWave-Based sensor Networks via Mobile Blocker Detection 29

Dynamic Uploading Scheduling in mmWave-Based Sensor Networks...

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29th ieee international conference on Parallel and distributed systems, ICPADS 2023

作者： Sun, Yifei Lv, Bojie Wang, Rui Tan, Haisheng Lau, Francis C. M. Southern University of Science and Technology Shenzhen China The University of Hong Kong Hong Kong University of Science and Technology of China Hefei China

ISBN: (纸本)9798350330717

The freshness of information, measured as Age of Information (AoI), is critical for many applications in next-generation wireless sensor networks (WSNs). Due to its high bandwidth, millimeter wave (mmWave) communication is seen to be frequently exploited in WSNs to facilitate the deployment of bandwidth-demanding applications. However, the vulnerability of mmWave to user mobility typically results in link blockage and thus postponed real-time communications. In this paper, joint sampling and uploading scheduling in an AoI-oriented WSN working in mmWave band is considered, where a single human blocker is moving randomly and signal propagation paths may be blocked. The locations of signal reflectors and the real-time position of the blocker can be detected via wireless sensing technologies. With the knowledge of blocker motion pattern, the statistics of future wireless channels can be predicted. As a result, the AoI degradation arising from link blockage can be forecast and mitigated. Specifically, we formulate the long-term sampling, uplink transmission time and power allocation as an infinite-horizon Markov decision process (MDP) with discounted cost. Due to the curse of dimensionality, the optimal solution is infeasible. A novel low-complexity solution framework with guaranteed performance in the worst case is proposed where the forecast of link blockage is exploited in a value function approximation. Simulations show that compared with several heuristic benchmarks, our proposed policy, benefiting from the awareness of link blockage, can reduce average cost up to 49.6%. © 2023 ieee.

关键词： age of information Markov decision process millimeter wave wireless sensor networks

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Evaluation of Wireless sensor Networks Module using IoT Approach 3

Evaluation of Wireless Sensor Networks Module using IoT Appr...

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3rd international conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Anand, L. Padmalal, S. Seetha, J. Juliana, R. Naveen Kumar, P.S. Parasa, Gayatri Srm Institute of Science and Technology School of Computing Department of Networking and Communications Kattanguluthur India Mangalam College of Engg Department of Computer Science and Engineering Kerala India Panimalar Engineering College Department of Computer Science and Business Systems Chennai India Loyola-ICAM College of Engineering and Technology Department of Information Technology Chennai India St. Ann's College of Engineering and Technology Department of CSE-DATA Science AP Chirala India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Guntur India

ISBN: (纸本)9781665462167

Microcomputers and medical devices with signal transceivers that operate on a specific radio display constitute the backbone of wireless sensor networks (WS Ns) that monitor environmental conditions (temperature, pressure, light, vibration levels, location). It is widely used in WAN sensor networks because of its flexible design and low setup fees. The u200b touch network allows for the connection of up to 65,000 devices, while the Intelligent sensors on other wireless networks are used to transfer data ports and assign wireless networks. Since the price of wireless solutions has been decreasing, and their functional capabilities have been growing, they are gradually replacing wired ones in telemetry data gathering systems and long- distance detecting communication. A deep learning model was used in this investigation to prevent the sensor nodes from manipulating data. sensor nodes include a lot of parameters and estimations. If these projected data values are altered, network performance will suffer, and the node's lifetime will be reduced. Data security became a priority when the sensor nodes were distributed. This new method is 98.82% more efficient than the previous one. © 2023 ieee.

关键词： sensor nodes

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Investigation into the Applicability of Software Requirements from Legal Metrology to sensor Networks

Investigation into the Applicability of Software Requirement...

引用

ieee international Instrumentation and Measurement Technology conference (I2MTC)

作者： Esche, Marko Nischwitz, Martin Toro, Federico Grasso Phys Tech Bundesanstalt Dept 8 5 Metrol IT Berlin Germany Fed Inst Metrol METAS Res & Dev Bern Switzerland

ISBN: (纸本)9781665483605

Technological progress has opened the door for the development of measurements performed by interconnected distributed components. Legal requirements to put such measuring instruments on the market, such as the Measuring Instruments Directive (MID) in Europe, do not yet address this new kind of instruments and therefore might require revisions. To identify necessary modifications, a general list of components is derived, forming the proposed baseline of any type of distributed measuring systems. Based on the MID, assets to be protected and associated security properties are formulated for each of the described general components. By utilizing the recently revised general requirements for software-controlled measuring instruments of the international Organization of Legal Metrology (OIML), the necessary interpretations and changes to fully protect all assets of a generalized distributed measuring system are shown and analysed. Finally, a summary of this investigation presents the current and potential future state of sensor networks under a legal metrology framework.

关键词： sensor networks legal metrology software examination components

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distributed online extraction of a fluid model for microservice applications using local tracing data 15

Distributed online extraction of a fluid model for microserv...

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15th ieee international conference on Cloud computing (ieee CLOUD) / ieee World Congress on Services (ieee SERVICES)

作者： Ruuskanen, Johan Cervin, Anton Lund Univ Dept Automat Control Lund Sweden

ISBN: (数字)9781665481373

ISBN: (纸本)9781665481373

Dynamic resource management is a difficult problem in modern microservice applications. Many proposed methods rely on the availability of an analytical performance model, often based on queueing theory. Such models can always be hand-crafted, but this takes time and requires expert knowledge. Various methods have been proposed that can automatically extract models from logs or tracing data. However, they are often intricate, requiring off-line stages and advanced algorithms for retrieving the service-time distributions. Furthermore, the resulting models can be complex and unsuitable for online evaluation. Aiming for simplicity, we in this paper introduce a general queuing network model for microservice applications that can be (i) quickly and accurately solved using a refined mean-field fluid model and (ii) completely extracted at runtime in a distributed fashion from common local tracing data at each service. The fit of the model and the prediction accuracies under system perturbations are evaluated in a cloud-based microservice application and are found to be accurate.

关键词： microservice runtime management performance modeling model extraction queuing networks fluid model

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Parallel computing Techniques for Accelerating Machine Learning Algorithms on Big Data

Parallel Computing Techniques for Accelerating Machine Learn...

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2023 international conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Mishra, Rahul Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350357769

In the era of Big Data, the computational demands of machine learning (ML) algorithms have grown exponentially, necessitating the development of efficient parallel computing techniques. This research paper delves into the exploration and evaluation of advanced parallel computing methodologies tailored for accelerating ML algorithms when applied to vast datasets. We commence by providing a comprehensive overview of the existing parallelization paradigms, highlighting their strengths and limitations in the context of ML. Subsequently, we introduce novel techniques that harness the combined power of distributed systems, multicore processors, and graphics processing units (GPUs) to achieve significant speed-ups. Experimental results, derived from processing multi-terabyte datasets, demonstrate that our proposed methods can achieve up to a tenfold increase in computational efficiency compared to traditional approaches. Furthermore, we present a detailed analysis of the scalability, fault-tolerance, and resource utilization of our techniques, providing insights for practitioners aiming to deploy ML algorithms on large-scale data infrastructures. This work not only paves the way for faster ML computations but also offers a blueprint for the next generation of scalable, parallel ML systems. © 2023 ieee.

关键词： Big Data distributed systems Machine Learning Acceleration Parallel computing Scalability

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Towards Asynchronously Triggered Spiking Neural Network on FPGA for Event-based Vision 22

Towards Asynchronously Triggered Spiking Neural Network on F...

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22nd international conference on Field Programmable Technology (ICFPT)

作者： Wu, Zhenyu Song, Mo So, Hayden Kwok-Hay Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China

ISBN: (纸本)9798350359114

In this paper, the design and implementation of an asynchronously-triggered spiking neuron tailored for FPGA implementations is presented. The asynchronous triggering mechanism is designed to effectively preserve the spatial-temporal information captured by event-based vision sensors. Neurons of the target network model are implemented using the configurable logic blocks of an FPGA spatially and communicate through an asynchronous handshaking protocol. Without using a global clock to synchronize operations of the neurons, energy consumption and inference latency are minimized. The proposed design is composable and scalable for applications with different spiking neural network (SNN) configurations. Experimental results show that the proposed design is able to achieve 95.76% accuracy on the N-MNIST dataset while consuming less than 1 mW dynamic power on an Xilinx ZCU102 board.

关键词： Spiking neural network asynchronous circuit FPGA dynamic vision sensor neuromorphic computing

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A Comprehensive Overview on IoT-Based Smart Stroke Rehabilitation Using the Advances of Wearable Technology 23

A Comprehensive Overview on IoT-Based Smart Stroke Rehabilit...

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作者： Razfar, Najmeh Kashef, Rasha Mohammadi, Farah Ryerson University Electrical and Computer Engineering Toronto Canada

ISBN: (纸本)9781665494571

The Internet of Things (IoT) is growing fast, and with the advancement of wearable devices and sensors, a wide range of research opportunities is now available. Several machine learning and deep learning techniques were deployed to provide smart stroke rehabilitation in remote stroke treatment and assessments. Reviewing and understanding existing studies in IoT-based stroke rehabilitation and finding the gap in this field can improve rehabilitation strategy. This paper summarizes the development of smart stroke rehabilitation knowledge for remote rehabilitation and assessments of stroke survivors. We have summarised the datasets and the state-of-the-art machine learning and deep learning methods in the IoT-based smart stroke rehabilitation using wearable devices. Supervised learning is the most common technique reported for stroke rehabilitation, and the optimum model is also reported in this paper. This survey provides a novel roadmap for future research in IoT-based stroke rehabilitation and treatment. © 2021 ieee.

关键词： Deep learning Smart cities Wearable computers Supervised learning Stroke (medical condition) sensor systems Internet of Things

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Efficient Power Generation System Using Single Axis Solar Tracking with Weather Monitor

Efficient Power Generation System Using Single Axis Solar Tr...

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2023 international conference on Innovative computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Ananthajothi, K. Santhosh, S. Shreyas, S. M., Santhosh Rajalakshmi Engineering College Computer Science and Engineering Chennai India

ISBN: (纸本)9798350319200

Growing at the fastest rate among renewable energy sources is solar energy. Using a basic dual-axis solar tracker system, the project is conceived and executed. Solar tracking devices are a must for solar power plants in order to optimize solar energy production. Utilizing a switching solar panel, a dual-axis tracker tracks the sun's beams in many directions to maximize energy *** 360-degree rotation of this solar panel is possible. The light intensity was sensed at 30 degrees per degree, or 180 degrees overall, using an LDR (Light Dependent Resistor), which subsequently sent data to the microcontroller. Also, this dual-axis solar tracker project has an LCD display, humidity and temperature sensors, and a raindrop detector. © 2023 ieee.

关键词： Dual axis solar tracker LDR sensor Renewable energy Solar power

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