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IEEE Symposium on Computers and Communications (ISCC)

作者： Ghofrane Fersi Research Laboratory of Development and Control of Distributed Applications (ReDCAD) National School of Engineers of Sfax BP 1173-3038 University of Sfax Tunisia

ISBN: (数字)9798350354232

ISBN: (纸本)9798350354249

The great breakthrough in the Mobile Internet of Things (IoT) has led to a wide range of application domains but has also raised new challenges, especially for routing protocols. In fact, the IoT devices’ mobility leads to routes instability which increases the packet error rate. Additionally, the energy shortage of IoT devices accentuates the routing protocol problems since routing is one of the most important sources of energy whereas the IoT devices suffer from the energy shortage. In this paper, we propose FOLLOWER: Fog-based routing protocol for mobile IoT devices. FOLLOWER exploits the proximity of fog nodes to mobile IoT devices to offer a robust routing protocol that can ensure energy and time-efficient routing while handling IoT objects’ mobility. FOLLOWER divides the IoT network into clusters. Each cluster is led by a fog node. The main routing tasks are done using the fog nodes that are using the Chord protocol for efficient lookup. The performance evaluation has proved that FOLLOWER managed to save time and energy and to handle efficiently IoT nodes mobility.

关键词： Performance evaluation Computers Codes Error analysis Computer architecture Routing Routing protocols Peer-to-peer computing Internet of Things

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Utilizing metabolite connectivity and G-CNN to detect gallbladder cancer

Utilizing metabolite connectivity and G-CNN to detect gallbl...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Ahmed Mahdi Obaid Mohamed Ksantini Amina Turki Abdullah Safaaldin Hatem Bellaaj Control and Energy Management Laboratory (CEMLab) ENIS University of Sfax Sfax Tunisia Croydon university hospital London UK Research laboratory on Development and Control of Distributed Applications. (ReDCAD) ENIS University of Sfax Sfax Tunisia

The hallmark of cancer is metabolic remodelling, which offers a unique insight into the biology of the disease revealing an opportunity for gallbladder cancer identification. By conceptualising the diagnosis of gallbladder cancer as a classification problem, it is possible to assess the capacity of several Machine Learning (ML) models to distinguish between gallbladder cancer patients and healthy individuals. Some of the models that are widely used in metabolomics literature include Support Vector Machines (SVM), Random Forest (RF) classifiers, Artificial Neural Networks (ANN), and Partial Least Squares-Discriminant Analysis (PLS-DA). The use of these models with metabolomic data has been successful. However, whether using them for classification tasks is preferable to using other or more complicated ML models has not been explored. We investigate a novel strategy for classifying people with gallbladder cancer by applying a Graph-Convolutional Neural Network (G-CNN) model to a dataset of patients. The methodical biological model of metabolite interactions and pathways as links is the foundation for this approach. Our findings show that the G-CNN significantly outperforms the most commonly used techniques, in contrast to the RF, whose effectiveness is marginally less but still equivalent to our model. Our findings suggest that using G-CNNs in metabolomics research is promising, and the adoption of non-invasive methods of metabolomic data extraction may help identify gallbladder cancer. Our suggested method achieves an accuracy of 93.6%, a specificity of 97%, and an AUC of 99.2%.

关键词： Support vector machines Radio frequency Metabolomics Technological innovation Smart cities Biological system modeling Artificial neural networks

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Chord-based distributed middleware architecture for Internet of Things

Chord-based distributed middleware architecture for Internet...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Ghofrane Fersi Amine Ben Hammouda Faouzi Derbel Research Laboratory of Development and Control of Distributed Applications (ReDCAD) National School of Engineers of Sfax BP 1173-3038 University of Sfax Tunisia Smart Diagnostic and Online Monitoring Leipzig University of Applied Sciences Leipzig Germany

The outstanding progress in the smart devices as well as the noticeable reduction in their cost has led to the invasion of the Internet of Things (IoT) in our real lives. The multiplicity of the IoT applications and the diversity and heterogeneity of the IoT devices present a real challenge in the IoT development. There is hence a need to have an intermediate layer between the physical layer including the smart devices and the application layer to facilitate the integration and the usage of the IoT devices in the IoT applications. This layer is the middleware layer. Most of the existing middleware are suitable for small-scale IoT networks including limited number of smart things. The performance of these middleware is reduced when the number of IoT devices increases. The main reason of the performance deterioration is the unsuitable middleware architecture that is unable to bear the increasing number of IoT devices. We present in this paper a distributed middleware architecture based on Chord protocol. Our architecture transforms any centralized middleware to a distributed one which improves its performance and makes it scalable. The performance evaluation have shown that our proposed approach has the ability to cope successfully with the increasing number of IoT devices and requests.

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Wake-Up Receiver Based Routing Protocols in Internet of Things: A Survey

Wake-Up Receiver Based Routing Protocols in Internet of Thin...

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ACS/IEEE International Conference on Computer Systems and applications

作者： Ghofrane Fersi Robert Fromm Maximilian Weber Faouzi Derbel Research Laboratory of Development and Control of Distributed Applications (ReDCAD) National School of Engineers of Sfax BP 1173-3038 University of Sfax Tunisia Smart Diagnostic and Online Monitoring Leipzig University of Applied Sciences Leipzig Germany

We are currently living in the era of the Internet of Things (IoT) where numerous smart objects are surrounding us and reporting various information about our environment. The main challenge of these IoT devices is energy consumption since the lifetime of each device is tightly related to its limited battery capacity. For this reason, it is beneficial to keep the IoT nodes in sleeping mode and to wake them up only when they are required. Wake-up-based wireless sensors present nowadays a leading technology that shapes well this requirement. However, despite their important impact on extending the network lifetime, these sensors present a real obstacle for IoT routing protocols. Effectively, routing in IoT networks should be time efficient, whereas these sensors require additional time to wake up and to be prepared for data reception and forwarding. In this paper, we give a general overview of the wake-up-based sensors and detail the most important challenges facing these sensors in the scope of the routing protocols. We also survey and propose a taxonomy of the most important and recent routing protocols that have used these sensors.

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Wake-up Receiver based routing protocol for indoor Wireless Sensor Networks

Wake-up Receiver based routing protocol for indoor Wireless ...

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International Conference on Network and Service Management

作者： Maximilian Weber Ghofrane Fersi Faouzi Derbel Smart Diagnostic and Online Monitoring Leipzig University of Applied Sciences Leipzig Germany Department of Computer Science and Applied Mathematics National School of Engineers of Sfax BP 1173-3038 Sfax Research Laboratory of Development and Control of Distributed Applications (ReDCAD) University of Sfax Tunisia

ISBN: (数字)9783903176515

ISBN: (纸本)9781665489928

Wake-up Receiver (WuRx) is one of the most trivial and effective solutions for energy-constrained networks and a promising solution for monitoring various phenomena in the sense of the Internet of Things (IoT). The most important and challenging issue in WuRx-based networks is the time efficient routing process in an energy efficient manner. Effectively, awaking each node needed in the routing process recursively requires a lot of time which is not suitable for time-critical applications. In this paper, we propose a novel Wake-up Receiver based routing protocol called Time Efficient WuRx-based Routing (TEW) that ensures energy optimised and time efficient routing in indoor scenarios. In our proposed approach, the network is divided into clusters at which each Fog Node manages the routes for data transmission in an asymmetric manner. When the Sink requires data from a specific set of nodes of a particular cluster, the Sink transmits a DataPts request to the corresponding Fog Node. In addition, the Fog Node sends instructions by means of a single Request (REQ) packet informing the corresponding nodes how often they should act as relays before switching to the sleeping mode. The measurement results show that our proposed approach has higher energy efficiency and achieves significant performance improvements in data delivery delay.

关键词： Wireless sensor networks Receivers Switches Routing Routing protocols Energy efficiency Internet of Things

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Block belief propagation algorithm for two-dimensional tensor networks

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Physical Review B 2023年第12期108卷 125111-125111页

作者： Chu Guo Dario Poletti Itai Arad Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha 410081 China Science Mathematics and Technology Cluster Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Faculty of Physics Technion Haifa 3200003 Israel

Belief propagation is a well-studied algorithm for approximating local marginals of multivariate probability distribution over complex networks, while tensor network states are powerful tools for quantum and classical many-body problems. Building on a recent connection between the belief propagation algorithm and the problem of tensor network contraction, we propose a block belief propagation algorithm for contracting two-dimensional (2D) tensor networks and approximating the ground state of 2D systems. The advantages of our method are threefold: (1) the same algorithm works for both finite and infinite systems; (2) it allows natural and efficient parallelization; and (3) given its flexibility, it would allow us to deal with different unit cells. As applications, we use our algorithm to study the 2D Heisenberg and transverse Ising models, and show that the accuracy of the method is on par with state-of-the-art results.

关键词： Quantum spin models Tensor network methods

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Block belief propagation algorithm for two-dimensional tensor networks

arXiv

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arXiv 2023年

作者： Guo, Chu Poletti, Dario Arad, Itai Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Faculty of Physics Technion Haifa3200003 Israel

Belief propagation is a well-studied algorithm for approximating local marginals of multivariate probability distribution over complex networks, while tensor network states are powerful tools for quantum and classical many-body problems. Building on a recent connection between the belief propagation algorithm and the problem of tensor network contraction, we propose a block belief propagation algorithm for contracting two-dimensional tensor networks and approximating the ground state of 2D systems. The advantages of our method are three-fold: 1) the same algorithm works for both finite and infinite systems;2) it allows natural and efficient parallelization;3) given its flexibility it would allow to deal with different unit cells. As applications, we use our algorithm to study the 2D Heisenberg and transverse Ising models, and show that the accuracy of the method is on par with state-of-the-art results. Copyright © 2023, The Authors. All rights reserved.

关键词： Tensors

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An optimal power supervising strategy for a smart home assessed based on BPMN Framework

An optimal power supervising strategy for a smart home asses...

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International Conference on Sciences and Techniques of Automatic control and Computer Engineering (STA)

作者： Leila Lanouar Mouna Rekik Olfa Bouchaala Lotfi Krichen Multimédia & Web Department University of Gabes Higher Institute of Computer Science and Multimedia of Gabes (ISIMG) Gabes Tunis Electrical Engineering Department Electrical systems and renewable energies Laboratory (LSEER) University of Sfax University of Gabes National Engineering School of Sfax (ENIS) Higher Institute of Computer Science and Multimedia of Gabes (ISIMG) Sfax Gabes Tunis Department of Computer Engineering and Applied Mathematics Research Laboratory on Development and Control and Distributed Applications (ReDCAD) University of Sfax National Engineering School of Sfax (ENIS) Sfax Tunis Electrical Engineering Department Electrical systems and renewable energies Laboratory (LSEER) University of Sfax National Engineering School of Sfax (ENIS) Sfax Tunis

ISBN: (纸本)9781665482622

For each smart home, the need of energy consumption supervision is necessary, which plays an important role to ensure the highest power quality and to enhance the stability of the whole grid. The current document implements a smart home supply strategy based on endless resources to reduce the electricity bill and confirm the energy balance. In this context, a proposed supervision algorithm operates in eight cases to reach optimal energy flow between renewable generators, home battery and grid in a smart home concept is presented. The system is evaluated using the framework “Business Process Model and Notation” (BPMN) Camunda basing on information stored in Firebase Cloud and results are presented in order to manifest the efficiency of this control strategy.

关键词： Renewable energy sources Energy consumption Power quality Process control Smart homes Power system stability Stability analysis

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Randomised benchmarking for characterizing and forecasting correlated processes

arXiv

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arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Impacts of Temperature and Humidity variations on RSSI in indoor Wireless Sensor Networks

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Procedia Computer Science 2018年 126卷 1072-1081页

作者： Amir Guidara Ghofrane Fersi Faouzi Derbel Maher Ben Jemaa Faculty of Electrical Engineering and Information Technology Leipzig University of Applied Sciences Germany Research on Development and Control of Distributed Applications ReDCAD National Engineering School of Sfax University of Sfax Tunisia

Many Wireless Sensor Networks (WSN) protocols such as lot of localization protocols rely on the accuracy of the Received Signal Strength Indicator (RSSI). This RSSI metric is sensitive to different factors which lead to its disturbance. Other works have already proved that temperature and humidity have important impact on RSSI in outdoor environment. It is evident that temperature and humidity vary more importantly on outdoor than on indoor. In this paper, we aim to answer at this question: Does the slight modification of temperature and humidity in indoor environment have a significant impact on RSSI value? We have conducted various experiments to study this impact.

关键词： RSSI Temperature Humidity LQI Indoor WSN

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