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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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Optimization of Economic Load Dispatch for distributed Energy System Using Metaheuristic Method

Optimization of Economic Load Dispatch for Distributed Energ...

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2024 international conference on Engineering and computing, ICECT 2024

作者： Khan, Usama Tariq Zia, Muhammad Fahad Lahore University of Management Sciences Department of Electrical Engineering Lahore Pakistan American University in Dubai Department of Electrical and Computer Engineering Dubai United Arab Emirates

ISBN: (纸本)9798350349719

The increasing demand for electricity has led to the use of multiple energy generation sources. Among these sources, renewable energy is favored due to its environmentally friendly nature. The integration of distributed generation sources with the conventional grid makes the system highly dense and complex. Different heuristic methods are commonly used to determine the optimal or near-optimal operational strategy of a distributed system while maintaining system constraints. To address this issue, a meta-heuristic method based on genetic algorithms (GA) is proposed in this paper to solve the economic load dispatch problem for a distributed energy system that incorporates both thermal and photovoltaic (PV) systems. In addition, the prohibited-operating zones of the thermal generators are considered. The power output of the PV system for each subinterval is calculated by considering the irradiance and temperature values in that interval. The algorithm is tested for a daily load of 700 MW and the optimal share of each generator for different scheduling hours is determined. To validate the proposed algorithm, it is compared with benchmarking methods such as particle swarm optimization, quadratic programming, and lambda iteration. The results indicate that the proposed algorithm is effective in reducing operating costs and has a faster convergence rate than benchmark methods. © 2024 ieee.

关键词： Genetic algorithms

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SRS: Scalable and Robust Snapshot Algorithm for Wireless sensor Networks 3

SRS: Scalable and Robust Snapshot Algorithm for Wireless Sen...

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3rd ieee international conference on Intelligent Technologies, CONIT 2023

作者： Mishra, Raghvendra Sharma, Teek Parval National Institute of Technology Department of Computer Science HP Hamirpur India

ISBN: (纸本)9798350338607

Global state determination of distributed systems gives information that is useful in applications of checkpointing, distributed garbage collection, deadlock detection, distributed algorithm termination detection, event boundary detection, distributed debugging, etc. Determination of the global state in a wireless sensor network needs a different approach than of traditional distributed networks due to unique properties of WSN like a constraint on resources, energy constraints, remote hazardous environments where sensors are deployed, network topology that is dynamic in nature, etc. In this paper, we propose a distributed snapshot algorithm that is scalable, robust, and provides efficient communication among WSN nodes which is based on tree architecture. We designed an algorithm in such a way that it can easily be scaled to any number of nodes without affecting the performance of the underlying system and it can effectively handle packet loss so that the communication cost of the whole system is maintained as minimal. We performed simulations in OMNET++ and did the analysis of results based on the number of messages exchanged, response time, and performance in packet loss situations. © 2023 ieee.

关键词： Fault tolerance

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Thwarting Longitudinal Location Exposure Attacks in Advertising Ecosystem via Edge computing 42

Thwarting Longitudinal Location Exposure Attacks in Advertis...

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42nd ieee international conference on distributed computing systems (ICDCS)

作者： Yu, Le Zhang, Shufan Zhou, Lu Meng, Yan Du, Suguo Zhu, Haojin Shanghai Jiao Tong Univ Shanghai Peoples R China Univ Waterloo Waterloo ON Canada

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

As geo-location data has been increasingly adopted as a high-profile feature in targeted advertising, exposing user real locations to untrusted cloud services or advertisers has raised severe privacy concerns. To protect location privacy with formal guarantee, a wide-stretched line of recent studies focuses on injecting controlled geo-indistinguishability (geo-IND) noise as per each location exposure. However, in advertising, over the course of 2 years, a single user can report and contribute near 1k location data points on average, which allows a longitudinal attacker to infer some statistics from the perturbed locations. In this study, we demonstrate the above-mentioned privacy risk via revealing an inference attack mechanism, coined as a longitudinal location exposure attack. This novel attack illustrates the possibility of recovering 75%similar to 90% of user top-1 locations (within only 200-meter range) among 37k users. In light of this deficiency, we propose a novel edge-assisted location privacy protection system, entitled Edge-PrivLocAd, that is adapted to location-based advertising. The novelty of Edge-PrivLocAd stems from our n-fold Gaussian mechanism, which adds permanent noise to the statistical user location profile and thus can defend against longitudinal attackers while balancing the privacy-utility trade-off. In addition, our system incorporates a posterior-based sampling technique into the location re-mapping process, that boosts location utility without privacy loss. We develop a fully-functioning prototype and empirically evaluate the proposed system. Our experimental results show that Edge-PrivLocAd is practical and scalable in real-world scenarios.

关键词： Privacy Differential privacy Ecosystems Prototypes Advertising distributed computing Edge computing

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Hybrid Quantum-Classical Machine Learning for Near Real-time Space to Ground Communication of ISS Lightning Imaging sensor Data 13

Hybrid Quantum-Classical Machine Learning for Near Real-time...

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ieee 13th Annual computing and Communication Workshop and conference (CCWC)

作者： Fadli, Samih Rawal, Bharat S. Capitol Technol Univ Comp Sci Dept Laurel MD 20708 USA

ISBN: (纸本)9798350332865

Near real-time sensor data is growing exponentially faster than our ability to sense and make sense of it as the current classical computing and supercomputing approaches require an enormous volume of computational resources, storage, and training time. Quantum computing is posed to exponentially outperforms today's high-performance computers and accelerate the evolution of information occurring in classical systems and sensor networks. The Lightning Imaging sensor (LIS) mounted on the international Space Station (ISS) locates, senses, and detects lightning activities from low Earth orbit and measures radiant energy at millisecond timing over a broad regional spectrum. In this paper, we are introducing a space-to-ground hybrid quantum- classical machine learning architecture to demonstrate the application potential and the feasibility of Hybrid Quantum Neural Networks using the ISS LIS lightning dataset and a corresponding background dataset as inputs (1) to train a classical deep neural network model (2) where the feature extraction outputs are encoded as quantum states using multiple calibrated quantum encoding patterns (3) then used as part of a quantum feature mapping process, ( 4) allowing for enhanced hybrid QNN training, optimization, and auto-differentiation, setting the path towards polynomial advantage. The following is how the rest of the paper is structured: The introduction is covered in section I, and the motivation and our contribution are covered in section II. Section III presents related works. Section IV describes the NRT lightning imaging sensor. Section V describes the space-to-ground hybrid quantum architecture. Section VI. Space-to-ground hybrid quantum-classical machine learning architecture. Section VII describes quantum machine learning. Section VIII presents a performance analysis. Finally, section XI concludes the research paper.

关键词： hybrid quantum-classical machine learning architecture quantum neural networks integrated quantum 11earth storm detection lightning-atmosphere interaction

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distributed Predefined-Time Optimization for Basic Source Estimation 20

Distributed Predefined-Time Optimization for Basic Source Es...

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20th international conference on Electrical Engineering, computing Science and Automatic Control, CCE 2023

作者： Devilleros, Pablo Sánchez-Torres, Juan Diego Defoort, Michael Loukianov, Alexander CINVESTAV Dept. Automatic Control Guadalajara Mexico Iteso Dept. Mathematics and Physics Tlaquepaque Mexico Uphf Lamih Umr Cnrs 8201 Valenciennes France

ISBN: (纸本)9798350306767

This paper introduces a distributed optimization algorithm for achieving formation control in multi-agent systems utilizing the zero-gradient sum property and the predefined-time stabilization framework. The distributed optimization scheme offers the flexibility to assign the settling time according to desired requirements, distinguishing it from existing finite and fixed-time schemes. Moreover, the algorithm eliminates the need for agents to exchange local gradients or Hessians of the cost functions. The algorithm's effectiveness is validated through an application to a basic case of distributed source localization. © 2023 ieee.

关键词： Multi agent systems

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BikeCAP: Deep Spatial-temporal Capsule Network for Multi-step Bike Demand Prediction 42

BikeCAP: Deep Spatial-temporal Capsule Network for Multi-ste...

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42nd ieee international conference on distributed computing systems (ICDCS)

作者： Zhong, Shuxin Lyu, Wenjun Zhang, Desheng Yang, Yu Rutgers State Univ New Brunswick NJ 08901 USA Lehigh Univ Bethlehem PA 18015 USA

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Given the recent global development of bike-sharing systems, numerous methods have been proposed to predict their user demand. These methods work fine for single-step prediction (i.e., 10 mins) but are limited to predicting in a multi-step prediction (i.e., more than 60 mins), which is essential for applications such as bike re-balancing that requires long operation time. To address this limitation, we leverage the fact that the demand for upstream transportation, e.g., subways, can assist the future demand prediction of downstream transportation, e.g., bikes. Specifically, we design a deep spatial-temporal capsule network called BikeCAP with three components: (1) a historical capsule that learns the demand characteristics for both the upstream (i.e., subways) and downstream (i.e., bikes) transportation systems, where a pyramid convolutional layer explores the simultaneous spatial-temporal correlations;(2) a future capsule that actively captures the dynamic spatial-temporal propagation correlations from the upstream to the downstream system, in which a spatial-temporal routing technique benefits to reduce the accumulated prediction errors;(3) a 3D-deconvolution decoder that constructs future bike demand considering the similar downstream demand patterns in neighboring grids and adjacent time slots. Experimentally, we conduct comprehensive experiments on the data of 30, 000 bikes and 7 subway lines collected in Shenzhen City, China, The results show that BikeCAP outperforms several state-of-the-art methods, significantly increasing the performance by 38.6% in terms of accuracy in multi-step prediction. We also conduct ablation studies to show the significance of BikeCAP's different designed components.

关键词： distributed Transportation systems Demand Prediction Bike Sharing

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Secure EELB-AOMDV Protocol to Mitigate Blackhole Attack 9

Secure EELB-AOMDV Protocol to Mitigate Blackhole Attack

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9th international conference on Advanced computing and Communication systems, ICACCS 2023

作者： Rani, B. Sandhya Shyamala, Kattula Department of CSE Hyderabad India

ISBN: (纸本)9798350397376

Recent advancements in wireless technologies have gradually increased the application domain of Wireless sensor Networks (WSNs) in hostile and unsupervised environments. The lack of administrator control in such environments leads to security attacks. To mitigate Blackhole attack, "Secure EELBAOMDV"protocol is presented in this paper and the results are compared with AOMDV protocol. An improvement in PDR, throughput, routing overhead and energy consumption is achieved with increase in number of nodes and packets. © 2023 ieee.

关键词： Wireless sensor networks

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Node Coverage and Connectivity Optimization in Heterogeneous Wireless sensor Networks Using Improved Flower Pollination Algorithm 4

Node Coverage and Connectivity Optimization in Heterogeneous...

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4th international conference on Ubiquitous computing and Intelligent Information systems, ICUIS 2024

作者： Mahankali, Saritha Kesavan, R. Kalaiselvan, S.A. Saveetha School of Engineering Simats Department of Computer Science & Engineering Chennai India Vardhaman College of Engineering Department of Computer Science & Engineering Telangana India Rajalakshmi Engineering Department of Artificial Intelligence & Machine Learning Chennai India

ISBN: (纸本)9798331529635

Wireless sensor networks (WSNs) rely on energy-conserving routing protocols due to the limited power and communication capabilities. The LEACH protocol has seen extensive usage despite its homogeneous network foundation, leads inadequate signal coverage. To solve the issue, this research proposes an improved flower pollination algorithm (IFPA) improves flower pollination algorithm (FPA) addresses issues with slow convergence and local optima. This research presents an enhanced clustering technique that may be utilized in heterogeneous sensor networks. Its main feature is the ability to adjust the status of data transmission. Once the observed information intensity above the predefined threshold, the data transmission connection is initiated and data is sent to the sink by the cluster heads, which filter the perceived information. Otherwise, cluster nodes keep track of the data and wait for the next batch of nodes to provide data. The good news is that the simulation results show a network lifespan that is several times longer than the LEACH protocol. The IFPA method stands out because it increases coverage rates while drastically decreasing the cost of deploying networks. As a result, the suggested method might find many uses, helping to lower costs and improve the performance of wireless sensor networks. © 2024 ieee.

关键词： sensor nodes

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Lagrange Coded Federated Learning (L-CoFL) Model for Internet of Vehicles 42

Lagrange Coded Federated Learning (L-CoFL) Model for Interne...

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42nd ieee international conference on distributed computing systems (ICDCS)

作者： Ni, Weiquan Zhu, Shaoliang Karim, Md Monjurul Asheralieva, Alia Kang, Jiawen Xiong, Zehui Maple, Carsten Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China Southern Univ Sci & Technol Res Inst Trustworthy Autonomous Syst Shenzhen Peoples R China Guangdong Univ Technol Sch Automat Guangzhou Peoples R China Singapore Univ Technol & Design Pillar Informat Syst Technol & Design Singapore Singapore Univ Warwick WMG Coventry W Midlands England

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

In Internet-of-Vehicles (IoV), smart vehicles can efficiently process various sensing data through federated learning (FL) - a privacy-preserving distributed machine learning (ML) approach that allows collaborative development of the shared ML model without any data exchange. However, traditional FL approaches suffer from poor security against the system noise, e.g., due to low-quality trained data, wireless channel errors, and malicious vehicles generating erroneous results, which affects the accuracy of the developed ML model. To address this problem, we propose a novel FL model based on the concept of Lagrange coded computing (LCC) - a coded distributed computing (CDC) scheme that enables enhancing the system security. In particular, we design the first L-CoFL (Lagrange coded FL) model to improve the accuracy of FL computations in the presence of low-quality trained data and wireless channel errors, and guarantee the system security against malicious vehicles. We apply the proposed L-CoFL model to predict the traffic slowness in IoV and verify the superior performance of our model through extensive simulations.

关键词： Coded distributed computing (CDC) data privacy federated learning Internet of Vehicles (IoV) machine learning security

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ZombieCoin3.0: On the Looming of a Novel Botnet Fortified by distributed Ledger Technology and Internet of Things 23

ZombieCoin3.0: On the Looming of a Novel Botnet Fortified by...

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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： Gao, Haoyu Li, Leixiao Lin, Hao Chang, Xiangyang Wan, Jianxiong Li, Jie Zhu, Fangyuan College of Data Science and Application Inner Mongolia University of Technology China Inner Mongolia Autonomous Reg. Eng. and Technol. Research Center of Big Data Based Software Service China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665494571

P2P Botnet is famous for the resilience against termination. However, its dependence on Neighbor List (NL) makes it susceptible to infiltration and poison, also leading to a dearth of adequate protection of Botmaster's identity. So as to overcome these weaknesses, the novel botnet infrastructure combined with blockchain emerges. But due to some flaws such like high latency and expensive transactions fees on blockchain, these new schemes can't satisfy the need of constructing hyper large-scale botnet in practice. We propose ZombieCoin3.0, a Botnet underlying overlay leveraging IoT devices to be maintainers and integrated with distributed Ledger Technology (DLT), which is able to deploy bots fully on blockchain. And it is versatile for file transfer, data feedback and other command and control scenarios that many contemporaries are impotent to cope with. Our proposal eliminates the P2P botnets' dependence on NL and the bottlenecks that other blockchain combined botnets have. Experiments' results authenticated that the effectiveness of our proposal as well as low latency of communication and nearly zero overhead of cost other comparatives unable to attain are achieved. © 2021 ieee.

关键词： Costs distributed ledger Botnet Blockchains Proposals Internet of Things Low latency communication

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