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8th ieee international conference on Fog and Mobile Edge computing (FMEC)

作者： Alkhabbas, Fahed Alawadi, Sadi Ayyad, Majed Spalazzese, Romina Davidsson, Paul Malmo Univ Internet Things & People Res Ctr Malmo Sweden Malmo Univ Dept Comp Sci & Media Technol Malmo Sweden Halmstad Univ Sch Informat Technol Halmstad Sweden Blekinge Inst Technol Dept Comp Sci Karlskrona Sweden Birzeit Univ Dept Comp Sci Birzeit Israel

ISBN: (纸本)9798350316971

the integration of the Internet of things (IoT) and Machine Learning (ML) technologies has opened up for the development of novel types of systems and services. Federated Learning (FL) has enabled the systems to collaboratively train their ML models while preserving the privacy of the data collected by their IoT devices and objects. Several FL frameworks have been developed, however, they do not enable FL in open, distributed, and heterogeneous IoT environments. Specifically, they do not support systems that collect similar data to dynamically discover each other, communicate, and negotiate about the training terms (e.g., accuracy, communication latency, and cost). Towards bridging this gap, we propose ART4FL, an end-to-end framework that enables FL in open IoT settings. the framework enables systems' users to configure agents that participate in FL on their behalf. those agents negotiate and make commitments (i.e., contractual agreements) to dynamically form federations. To perform FL, the framework deploys the needed services dynamically, monitors the training rounds, and calculates agents' trust scores based on the established commitments. ART4FL exploits a blockchain network to maintain the trust scores, and it provides those scores to negotiating agents' during the federations' formation phase.

关键词： Trustworthy Federated Learning Internet of things Machine Learning Agents

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A live context model for semantic reasoning in IoT applications

A live context model for semantic reasoning in IoT applicati...

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20th ieee international conference on Pervasive computing and Communications (ieee PerCom)

作者： Del Gaudio, Daniel Ariguib, Boshra Bartenbach, Arne Solakis, Georgios Univ Stuttgart Inst Parallel & Distributed Syst Stuttgart Germany

ISBN: (纸本)9781665416474

Nowadays, the rapid increase of IoT devices and the corresponding high volume of produced data leads to a higher complexity of data analysis and context reasoning tasks. In the IoT, monitoring the context of an application, i.e., the involved devices sensors and actuators as well as their surroundings, is of vital importance. Ontologies can be used to model such context, nevertheless, they usually do not consider live information like sensor values and monitoring data. Yet, this is necessary to capture the full context of an IoT application. In this paper, we propose a context model that includes the current state of devices, composing their static information, such as device names, and live information gathered from monitoring systems and sensors. We further propose an extendable architecture to enrich the ontology with static and live data. Our approach can be extended by integrating different data sources and extending the context model.

关键词： Internet of things context modeling ontologies

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Batterfly: Battery-Free Daily Living Activity Recognition System through distributed Execution over Energy Harvesting Analog PIR sensors 17

Batterfly: Battery-Free Daily Living Activity Recognition Sy...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Stirapongsasuti, Sopicha Misaki, Shinya Matsui, Tomokazu Suwa, Hirohiko Yasumoto, Keiichi Nara Inst Sci & Technol Ikoma Nara 6300192 Japan

ISBN: (纸本)9781665439299

In recent years, the use of energy harvesting (EH) sensors has led to the proposal of activity sensing systems that are easy to install and do not require maintenance such as battery replacement. In this study, we aim to construct a system that can not only sense but also recognize activities of daily living (ADLs) using only power generated by EH sensors. To achieve this goal, in this paper, we propose a fully EH-based ADL recognition system called Batterfly, which consists of EH analog PIR sensor nodes that can operate with indoor light, continuously senses human movement, and recognizes daily activities through machine learning. We applied the distributed execution method of the activity recognition model with five sensor nodes to five types of activities by five participants, and found that the system could recognize them with an average accuracy of 63.59%, comparable to the performance of the centralized model running on a gateway.

关键词： wireless sensor network energy harvesting distributed computing

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Fully distributed Containment Control of Nonlinear Multi-agent systems 4

Fully Distributed Containment Control of Nonlinear Multi-age...

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4th international conference on Data-Driven Optimization of Complex systems, DOCS 2022

作者： Liu, Tianqi Lv, Yuezu Wen, Guanghui Southeast University School of Information Science and Engineering Nanjing China Beijing Institute of Technology Advanced Research Institute of Multidisciplinary Sciences Beijing China Southeast University School of Mathematics Department of Systems Science Nanjing China

ISBN: (数字)9781665459822

ISBN: (纸本)9781665459822

In this paper, the containment problem of multi-agent nonlinear dynamic systems under directed topologies is reconsidered, where the exchange of the observer information between neighboring agents is avoided to release the communication burden. In this setting, only the relative output measured by sensor networks can be utilized to generate the observer and the controller. We regard the Lipschitz nonlinearity and relative input of each agent as unknown input and give a reduced-order observer-based protocol. © 2022 ieee.

关键词： Multi agent systems

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distributed Coordinate Descent Algorithm for Variational Quantum Classification 4

Distributed Coordinate Descent Algorithm for Variational Qua...

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4th ieee international conference on Quantum computing and Engineering, QCE 2023

作者： Koyasu, Izuho Raymond, Rudy Imai, Hiroshi The Univ. of Tokyo Dept. of Computer Science Japan Ibm Ibm Quantum Japan Keio University Quantum Computing Center Japan

ISBN: (纸本)9798350343236

Quantum Machine Learning (QML) is one of promising applications for near-term quantum computing. Two popular methods in QML are kernel methods and variational methods. Variational methods, which consist of parametrized quantum circuits (PQCs) to encode data and define classifiers, work faster in theory (i.e., O(N) to learn from N training examples) than kernel methods, which use quantum circuits to compute O(N2) elements of kernel matrices. However, in practice when dealing with large N, it is necessary to speed up variational methods due to the slow quantum gates. In this work, we propose a parallelization of training variational quantum classifiers to utilize the availability of many quantum devices with dozens of qubits. In contrast to existing parallelization of variational methods with gradient-based algorithms, we develop a novel distributed coordinate descent algorithm to optimize parametrized gates of variational quantum circuits. there are several gradient-free methods to optimize PQCs that have been shown to converge faster. Here, by focusing on the so-called Free-axis selection (Fraxis) method, we show how the gradient-free methods can be parallelized, and demonstrate their efficacies by running the algorithm on both simulators and IBM Quantum devices. We confirm the proposed algorithm achieves high classification accuracy and gains almost-linear speedup with the degree of parallelization. © 2023 ieee.

关键词： Classification (of information)

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Survey of distributed File systems: Concepts, Implementations, and Challenges 14

Survey of Distributed File Systems: Concepts, Implementation...

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14th international conference on Information and Communication Technology Convergence, ICTC 2023

作者： Pham, Kiet Tuan Lee, Sangjin Nguyen, Lan Anh Paek, Jeongyeup Son, Yongseok Chung-Ang University Department of Computer Science and Engineering Korea Republic of

ISBN: (纸本)9798350313277

Modern computing now relies heavily on distributed File systems (DFS), which make it possible to store, manage, and retrieve data across remote contexts in an effective manner. therefore, it is essential to comprehend the DFS environment to optimize data management and storage solutions. We explore DFS in this thorough overview work, discussing its foundational ideas, well-known applications, related difficulties, and potential future research avenues. © 2023 ieee.

关键词： cloud computing data-intensive computing distributed File systems

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DG Locational Incremental Contribution to Grid Supply Level

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ieee TRANSACTIONS ON INDUSTRY APPLICATIONS 2022年第1期58卷 5-14页

作者： Hernando-Gil, Ignacio Zhang, Zhipeng Ndawula, Mike Brian Djokic, Sasa Z. Univ Bordeaux ESTIA Inst Technol F-64210 Bidart France Univ Bath Dept Elect & Elect Engn Bath BA2 7AY Avon England Univ Edinburgh Sch Engn Inst Energy Syst Edinburgh EH9 3JL Midlothian Scotland

Due to decarbonisation and decentralisation of energy sectors, the rise of distributed generation (DG) will modify generation and demand patterns at grid supply points (GSPs), where the interface between distribution and transmission systems takes place. With the increasing penetration of such devices, methodologies able to evaluate its contribution to both local distribution network and transmission system become crucial. this article proposes an analytical method to evaluate the DG locational incremental contribution (LIC) to the interface with the transmission grid. Accordingly, the original model of the U.K. engineering recommendation P2 is enhanced by studying the impacts from high-voltage distribution networks (i.e., <= 132 kV) under normal and contingent conditions. this approach enables a more accurate network security assessment, especially when considering contingencies such as distribution system faults. To illustrate the proposed method, the original P2 model is compared against different enhanced approaches on three basic distribution networks, followed by a case study and a sensitivity analysis on a revised ieee 14-bus GSP system. the proposed LIC method produces results that assess a wider range of conditions including DG penetration, concentration, and system reliability. Furthermore, it provides an increased DG visibility for transmission planning and operation.

关键词： Distribution networks Erbium Standards Planning Mathematical models Renewable energy sources distributed power generation distributed generation (DG) network congestion management network state enumeration power system reliability transmission system operator

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sensor Assisted War Field Spying Robot using Internet of things (IoT) 4

Sensor Assisted War Field Spying Robot using Internet of Thi...

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4th international conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Rajeshwaran, K. Rishma, M. Ovia Pavai, V. Nandhini, D. Sri Ramakrishna Engineering College Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350300093

the goal of this research is to lower the number of people who die in terrorist attacks. therefore, this issue can be solved by designing an RF-based surveillance robot that includes a wireless camera, making it possible to investigate issues when necessary. this robot has the ability to silently enter into enemy area and transmit data through a wireless camera. this robot's movement can be wirelessly controlled by transmitting commands to an onboard RF receiver using a handheld RF transmitter. this robot also operates in automatic mode. this spy robot can also be utilized in high-end malls, hotels, jewellery showrooms, and other locations where there may be a threat from terrorists or trespassers. In times of conflict, it can be used to gather intelligence from the enemy's terrain, watch it in a remote, secure location, and securely develop a plan for a counterattack. It can also be used to track terrorist organizations' locations and then organize an attack at an appropriate time. this robot monitors any location where people are not allowed. © 2023 ieee.

关键词： Internet of things

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the Parallelized Cuckoo Filter for Cold Data Representation 23

The Parallelized Cuckoo Filter for Cold Data Representation

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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： Sun, Bowen Luo, Lailong Li, Shangsen Chen, Yingwen Guo, Deke College of Computer National University of Defense Technology China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory China College of Computer National University of Defense Technology National Lab for Parallel and Distributed Processing China

ISBN: (纸本)9781665494571

Cold data contributes a large portion of the big data today and is usually stored in secondary storage. Various sketch data structures are implemented to represent the stored elements and provide constant-time membership queries. Considering the large volume and infrequent access of cold data, we envision three rationales of cold data representation: 1) parallelized insertion, 2) accurate representation, and 3) constant-time query/deletion. the existing sketches, however, fail to achieve these rationales simultaneously. To this end, we propose a novel sketch named Parallelized cuckoo Filter (PCF) in this paper. PCF divides the standard cuckoo filter into multiple homogenous segments. An additional hash function is introduced to assign an element to a segment. the element will be inserted into the selected segment. With such a design, element insertions in PCF can be naturally parallelized. Besides, as a variant of the cuckoo filter, PCF naturally realizes the accurate representation and constant-time query/deletion requirements. Comprehensive experiments further indicate that PCF achieves the three rationales simultaneously. © 2021 ieee.

关键词： Hash functions Smart cities Big Data Data structures Standards

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IoT-Enabled Optimised sensor-based System for Monitoring Grain Storage 4

IoT-Enabled Optimised Sensor-based System for Monitoring Gra...

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4th international conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Shaik, Shafi Leela Ratnasree, M. Mounika, K. Pravalika, M. Kalyan, B. Begum, Humera B v Raju Institute of Technology Ece Telangana Narsapur India

ISBN: (纸本)9798350300093

In the recent past, most of the countries started developing the technologies to improve safety of food storage, as almost one-third of the food grains are wasted due to storage losses worldwide. On the other side, in India nearly 20% of food grains are lost every year and is majorly due to environmental conditions, like floods, heavy rains and lack of well-equipped infrastructure for packing, transportation, storing of grains. So, food is getting wasted from its production to consumption. To overcome this, an IoT (Internet of things) -enabled optimized sensor-based system for monitoring grain storage is proposed. Here, the proposed system is focused to reduce food wastage during storage phase. the proposed model includes smart sensing devices to sense various parameters like humidity, temperature, CO2 (Carbon Dioxide), and fire/smoke. All the values of these sensors are collected from Arduino controller and stored in a cloud server through GSM (Global System for Mobile Communication) module. the parameters are then compared with threshold values for any abnormality in the storage place. If there is a change in any of the parameter then a controlled action will be initiated and an alert message will be sent to linked mobile numbers. In addition, proposed model consists of a fan to control humidity and temperature before necessary action being taken. © 2023 ieee.

关键词： Carbon dioxide

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