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Intrusion Detection in Wireless sensor Networks using Hybrid Deep Belief Networks and Harris Hawks Optimizer 4

Intrusion Detection in Wireless Sensor Networks using Hybrid...

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

作者： Vikas Daund, Ramesh Pandharinath Kumar, Davinder Charan, Piyush Ingilela, Ravi Shireesh Kumar Rastogi, Ravi Iimt University School of Computer Science and Applications Uttar Pradesh O-Pocket Ganganagar Meerut India Snd College of Engineering and Research Centre Yeola Department of Computer Engineering Maharashtra India Micron Technology Telangana Hyderabad India Manav Rachna University Department of Electronics and Communication Engineering Haryana Faridabad India Audisankara College of Engineering and Technology Department of CSE Andhra Pradesh India Nielit Uttar Pradesh Gorakhpur India

ISBN: (纸本)9798350300093

A substantial amount of nodes equipped with sensors make up a wireless sensor network that collects and sends data to a base station. the wireless sensor networks, subsequently, face a number of security vulnerabilities as a result of shortages of resources, installation methods, and routes of communication. therefore, detecting illegal entry is crucial to enhancing the security aspects of wireless sensor networks. systems for detection of network breaches offer these functions, making them necessary for every communication network. Although machine learning (ML) techniques are often utilized in intrusion detection systems, their effectiveness when managing unbalanced assaults is unsatisfactory. this research work developed an attack identification system based on deep belief networks to address this issue and boost performance. the best characteristics from the dataset are chosen using a Harris Hawk optimization technique, and the parameters that were chosen are then employed as the building blocks of a deep belief network's structure to look for breaches. the experimental findings shown that the suggested DBN effectively detects assaults and outperforms conventional deep learning models like the Convolutional Neural Networks, Long Short Term Memory Networks, Generative Adversarial Networks and Radial Basis Function Networks. © 2023 ieee.

关键词： Radial basis function networks

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Socially Fair Coverage Control

Socially Fair Coverage Control

引用

ieee international conference on Robotics and Automation (ICRA)

作者： Malencia, Matthew Pappas, George Kumar, Vijay Univ Penn GRASP Lab Levine Hall 4th Floor3330 Walnut St Philadelphia PA 19104 USA

ISBN: (纸本)9798350323658

We investigate and develop algorithms for social fairness in coverage control problems. Existing coverage control methods are efficient, optimizing the average expected distance from any event to the nearest robot. However, in societal applications like disaster response or transportation, these conventional objectives lead to disparate coverage costs with respect to different groups within a population. We formulate social fairness for coverage control as the minimization of the maximum coverage cost among a set of groups within a population. Our approach uses Voronoi iteration to solve this novel problem by approximating the non-differentiable objective with the log-sum-exp and defining a gradient based controller that prioritizes fairness while also optimizing average performance when disparities between groups are low. We show convergence properties of this proposed control law and demonstrate the approach in simulations of randomly generated population densities as well as environments generated from U.S. census data on population rates and demographics. Our approach provides greater fairness than existing methods while maintaining similar computational time and convergence properties.

关键词： Fairness distributed Robot systems Multi Robot systems Robustness Ethics and philosophy

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Telco Market Dynamics under Strategic Pricing and Multi-Attribute QoS Within Cloud Facilities 19

Telco Market Dynamics under Strategic Pricing and Multi-Attr...

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Habli, Samira Datar, Mandar El-Azouzi, Rachid Sabir, Essaid Univ Avignon CERI LIA Avignon France INRIA Sophia Antipolis Mediterranee Valbonne France Hassan II Univ Casablanca LRI Lab NEST Res Grp ENSEM Casablanca Morocco Univ Quebec Montreal Dept Comp Sci Montreal PQ H2L 2C4 Canada

ISBN: (纸本)9798350333398

We present a game theoretic model that describes the competition between non-cooperating Service Providers (SPs) to purchase resources from the Infrastructure Provider (InP), and to offer paid services to their end-users. In the proposed model, the demand of a SP depends not only on its price and its quality of service (QoS), but also on the prices charged and QoS offered by its competitors. We consider that the InP owns the cloud facility to support the resources required by SPs to run the services of their end-users. When SPs access resources through virtually unlimited cloud capacity, resulting in competition to attract end-users with price required and QoS offered. We establish the existence and uniqueness of Nash equilibrium of the induced game. In addition, we design an online learning algorithm to allow SPs to reach the Nash equilibrium in a fully distributed fashion. Finally, we run simulations using Amazon EC2 instances to validate the proposed model's consistency, investigate the impact of some parameters on the market price, and analyze the convergence of the equilibrium price learning algorithm.

关键词： Resource allocation Nash equilibrium MultiAttribute QoS Gradient-Descent

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A Robust Framework for Fixing the Vulnerability of Compressed distributed Learning 26

A Robust Framework for Fixing The Vulnerability of Compresse...

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26th international conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Chen, Yueyao Wang, Beilun Zhang, Yan Kuang, Jingyu Southeast University School of Computer Science and Engineering Nanjing211102 China

ISBN: (纸本)9798350331684

Nowadays, as a prevailing paradigm for large-scale machine learning, distributed learning has been faced with two challenges, communication bottleneck and limited robustness. For the communication challenge, compression is widely-used as a solution. For the robustness challenge, some robust defence methods have been proposed. However, previous works that simultaneously consider these two challenges are limited. through an experiment on the w8a dataset, we found that compressed distributed learning with rand-K is vulnerable to poisoning attacks. therefore, in this paper, we propose a robust compressed distributed framework for distributed learning settings. Experimental evaluations on a9a and w8a datasets have shown the effectiveness of our proposed framework, which markedly decreases the average optimality gap from 1.47E -2 and 2.15E -2 to 3.98E -4 and 4.33E -4 respectively. © 2023 ieee.

关键词： Machine learning

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

2021 IEEE 23rd International Conference on High Performance ...

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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

ISBN: (纸本)9781665494571

the proceedings contain 343 papers. the topics discussed include: three-level compact caching for search engines based on solid state drives;a fine-grained volley gesture recognition method with direction independence;universal adversarial attack against 3d object tracking;efficient hardware redo logging for secure persistent memory;a cost-efficient metadata scheme for high-performance deduplication systems;high speed true random number generator controlled by logistic map;characterization and implication of edge WebAssembly runtimes;frend for edge servers: reduce server number! keeping service quality!;on-the-fly servers placement for online multiplayer games in the fog;advanced architecture design of high-radix router based on chiplet integration and IP reusability;embrace the conflicts: exploring the integration of single port memory in systolic array-based accelerators;visual sensitivity aware rate adaptation for video streaming via deep reinforcement learning;semi-supervised federated learning with non-IID data: algorithm and system design;on-demand intelligent routing algorithms for the deterministic networks;and distributed service placement in ultra-dense edge computing: a game-theoretical approach.

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A distributed SLAM with UWB-VIO Fusion Framework for Enhanced Relative Localization of Multi-UAVs System 4

A Distributed SLAM with UWB-VIO Fusion Framework for Enhance...

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4th international conference on Computer Vision, Image and Deep Learning, CVIDL 2023

作者： Cai, Qiuji Jiang, Bo Wu, Yutao Xu, Hong The 32nd Research Institute of China Electronics Technology Group Corporation Shanghai China

ISBN: (纸本)9798350326444

the most critical challenge of multi-UAV (unmanned aerial vehicles) systems accomplishing a common mission is to maintain relative localization among UAVs. However, it remains an open and challenging research topic in infrastructure-less environments. In this paper, we propose a novel distributed visual-inertial ultra-wideband (UWB) fusion framework for global localization that overcomes the problem of state estimation in GPS-denied areas, which reduces computational issues confronted by centralized Simultaneous Localization and Mapping (SLAM). Firstly, our solution integrates a UWB ranging front-end on each UAV for ranging and uses Visual-Inertial Odometry (VIO) to estimate the self-motion of each UAV. Using a front-end that fuses UWB measurements with VIO, we correct potential drift issues caused by VIO and perform distributed loop closure detection among multiple UAV s to achieve relative pose estimation. Additionally, we propose a consistency measurement filtering method with the adaptive threshold in three-dimensional space to improve the accuracy of state estimation under continuous non-line-of-sight (NLOS) conditions. Lastly, by using distributed outlier rejection to remove erroneous estimates and fusing measurements from both front-end and back-end pose graph optimization modules, we employ a sliding window method to recover the complete trajectory and guarantee global consistency of pose estimates. We believe our method provides a comprehensive solution for the global localization in multi-UAV systems, eliminating the environmental constraints of previous positioning methods and providing opportunities for other researchers to apply UAV cluster motion planning techniques in complex environments. © 2023 ieee.

关键词： Unmanned aerial vehicles (UAV)

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Proceedings - 2023 ieee international conference on Cloud Engineering, IC2E 2023

Proceedings - 2023 IEEE International Conference on Cloud En...

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11th ieee international conference on Cloud Engineering, IC2E 2023

ISBN: (纸本)9798350343946

the proceedings contain 31 papers. the topics discussed include: cost-effective scheduling for Kubernetes in the edge-to-cloud continuum;energy-efficient OECT sensor data analysis on constrained edge devices;CLOUDFACTORY: an open toolkit to generate production-like workloads for cloud infrastructures;a reinforcement learning approach for performance-aware reduction in power consumption of data center compute nodes;protocol-independent context propagation for sharing microservices in multiple environments;towards serverless sky computing: an investigation on global workload distribution to mitigate carbon intensity, network latency, and cost;evaluation of data enrichment methods for distributed stream processing systems;and breaking the vicious circle: self-adaptive microservice circuit breaking and retry.

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Quantum sensor Network Algorithms for Transmitter Localization 4

Quantum Sensor Network Algorithms for Transmitter Localizati...

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

作者： Zhan, Caitao Gupta, Himanshu Stony Brook University Department of Computer Science United States

ISBN: (纸本)9798350343236

A quantum sensor (QS) is able to measure various physical phenomena with extreme sensitivity. QSs have been used in several applications such as atomic interferometers, but few applications of a quantum sensor network (QSN) have been proposed or developed. We look at a natural application of QSN-localization of an event (in particular, of a wireless signal transmitter). In this paper, we develop effective quantum-based techniques for the localization of a transmitter using a QSN. Our approaches pose the localization problem as a well-studied quantum state discrimination (QSD) problem and address the challenges in its application to the localization problem. In particular, a quantum state discrimination solution can suffer from a high probability of error, especially when the number of states (i.e., the number of potential transmitter locations in our case) can be high. We address this challenge by developing a two-level localization approach, which localizes the transmitter at a coarser granularity in the first level, and then, in a finer granularity in the second level. We address the additional challenge of the impracticality of general measurements by developing new schemes that replace the QSD's measurement operator with a trained parameterized hybrid quantum-classical circuit. Our evaluation results using a custom-built simulator show that our best scheme is able to achieve meter-level (1-5m) localization accuracy;in the case of discrete locations, it achieves near-nerfect (99-100%) classification accuracy. © 2023 ieee.

关键词： Transmitters

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Routing Drones Being Aware of Wind Conditions: a Case Study 17

Routing Drones Being Aware of Wind Conditions: a Case Study

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

作者： Palazzetti, Lorenzo Univ Florence Dept Comp Sci Florence Italy

ISBN: (纸本)9781665439299

In this paper, we investigate the manner in which energy consumption in drone deliveries is affected by windy environmental conditions. We know in fact that the energy consumption of the drone will depend on the static and dynamic parameters of the scenario where it moves and according to these it decides, during the mission, to detour from the originally planned path to take advantage of the wind changes. In order to validate this, we simulate possible deliveries among fixed destinations relying on a real data-set of recorded winds obtained from different weather stations in Corsica, France. For our analysis, we will mainly concentrate on the evaluation of the delivery scheme proposed in the literature, where completing a delivery means finding a cycle for the drone that is feasible, i.e., that can be completed with the available energy autonomy of the drone.

关键词： Wind Energy consumption Routing sensor systems Batteries distributed computing Drones

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Research on Distribution Network Planning with distributed Generation Considering Line Margin 4

Research on Distribution Network Planning with Distributed G...

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4th international conference on Advanced Electrical and Energy systems, AEES 2023

作者： Gao, Liping She, Yanjie Zhu, Lili Zhang, Jiangtao Wang, Jing Xu, Wentao Cai, Pengcheng Mi, Yang State Grid Luoyang Power Supply Company Henan China Shanghai Ocean University School of Information Shanghai China Shanghai University of Electric Power College of Electrical Engineering Shanghai China

ISBN: (纸本)9798350342659

the current planning for large-scale photovoltaic integration into the distribution network needs to balance electricity and transmission capacity, and the strategy of energy storage distribution network joint planning has emerged. Firstly, a line margin index is established as the evaluation basis for the transmission capacity of distribution network lines. Furthermore, a bi-level programming model was constructed that comprehensively considers economic costs and line transmission capacity. Collaborative planning was carried out for energy storage systems and distribution network lines, and the model was transformed from a two-layer model to a single-level model to solve the problem, reducing the difficulty of solving the model. Finally, a numerical example was compared between the collaborative planning strategy and other methods. From the simulation results, it can be seen that the proposed strategy not only has certain economic benefits in planning the expansion direction of the grid line and determining the energy storage capacity, but also has higher grid line margin and higher security in the proposed planning scheme. © 2023 ieee.

关键词： distributed power generation

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