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A distributed Energy Trading Framework with secure and effective Consensus Protocol 42

A Distributed Energy Trading Framework with secure and effec...

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

作者： Ye, Jin Liang, Jiahua Li, Xiaohuan Chen, Qian Guangxi Univ Sch Comp & Elect Informat Nanning 530000 Peoples R China Guilin Univ Elect Technol Sch Informat & Commun Guilin 541000 Peoples R China

ISBN: (数字)9781665488792

ISBN: (纸本)9781665488792

With the rapid increase of DER(distributed energy resources), it has become a global trend to establish a distributed energy trading markets to coordinate these DERs. However, the construction of distributed energy trading market faces various challenges, in which trusted transaction among market participants is crisis. Since the existing solutions need numerical calculation and communication resource that lead to large delay, this paper proposes a distributed energy trading framework with secure and effective consensus protocol. Different from the traditional PBFT (Practical Byzantine Fault Tolerance) that is the notable debasement on interaction flow between processes, a threshold signature mechanism is introduced and the consensus process of trading is reconstructed. Theoretical analysis shows that the communication complexity of the proposed framework is optimized from O(n(2)) to O(n), and the computation complexity of the participants is also reduced from O(n) to O(1). Our simulation results also show that the task delay of our consensus protocol begins to be lower than PBFT when the number of participants exceeds a certain threshold. In particular, the trusted transaction delay using our consensus protocol is reduced by 12.14% when the number of participants increases to 100.

关键词： distributed energy trading blockchain consensus protocol threshold signature

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distributed Rendering for Video Games via Object Streaming 42

Distributed Rendering for Video Games via Object Streaming

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

作者： Parolini, Giacomo Maggiorini, Dario Gadia, Davide Ripamonti, Laura Anna Univ Milan Dept Comp Sci Milan Italy

ISBN: (数字)9781665488792

ISBN: (纸本)9781665488792

Propelled by the growing availability of broadband connection in recent years, the gaming industry is now devoting a considerable amount of resources and investments in online and cloud gaming. In legacy online gaming, the gaming experience is usually provided with the support of remote servers, and online players rely on their local PCs or consoles, which hold a local copy of all the content (assets) and must follow some minimum requirements in hardware and software specifications. Whereas, on cloud gaming, intensive computational tasks are almost completely offloaded to dedicated servers: video frames are rendered on the remote machine, encoded and sent to the players as a video stream. This approach soften the need for updated and powerful devices, but it suffers from all the limitations and problems inherent to multimedia real-time streaming. In this paper we explore an hybrid approach between a (video) streaming-based cloud gaming and the traditional approach where all assets are local to the player. We propose a solution where the rendering pipeline is split between server and client. In this distributed architecture, the server manages most of the game scene description, runs the game simulation, performs the first segment of the graphics pipeline's application stage, and finally sends a stream of pre-processed graphical objects to the client, which performs the final rendering steps. The proposed approach reduces the computational burden on the server, which is not required to perform rendering, improving scalabihty when compared with cloud gaming solutions based on video streaming.

关键词： Video Games distributed Rendering Cloud gaming Online gaming Game streaming

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Adaptive Multi-sensor Integrated Navigation System Aided by Continuous Error Map from RSU for Autonomous Vehicles in Urban Areas 26

Adaptive Multi-Sensor Integrated Navigation System Aided by ...

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ieee 26th international conference on Intelligent Transportation systems (ITSC)

作者： Huang, Feng Wen, Weisong Zhang, Guohao Su, Dongzhe Hsu, Li-Ta Hong Kong Polytech Univ Hong Kong Peoples R China Hong Kong Appl Sci & Technol Res Inst ASTRI Hong Kong Peoples R China

ISBN: (纸本)9798350399462

There has been a widespread study on multi-sensor integration to achieve precise and robust odometry for autonomous vehicles (AVs) in urban areas. LiDAR odometry and visual odometry can be affected by structureless scenarios and numerous dynamic objects. GNSS positioning can be degenerated due to the multipath and non-line-of-sight signals by buildings. Therefore, selecting appropriate weighing for heterogeneous sensors is a challenge for multi-sensor fusion. With the advancements in cellular vehicle-to-everything (C-V2X) and intelligent roadside units (RSUs), vehicles and the RSUs can collaborate to deliver reliable service. Inspired by this, this paper investigates continuous error maps for available sensors under different time conditions (noon, sunset, and night) to improve the positioning performance of surrounding AVs in complex urban environments. In particular, this paper presents an error-map-aided multi-sensor integrated system, which benefits from the error information collected by a sensor-rich AV. Then the error information is uploaded to the RSUs which is then distributed to the AVs. A smaller weight is assigned if a larger error is queried from the error map. To validate our approach, experiments were performed using the realistic CARLA simulator and our self-developed GNSS RUMS simulator. To benefit the research community, we open-sourced the implementation on our project page(3).

关键词： Autonomous vehicles

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A Light Waveguide Bending sensor with a High Sensing Range and High Sensitivity

A Light Waveguide Bending Sensor with a High Sensing Range a...

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2024 ieee international conference on Real-Time computing and Robotics, RCAR 2024

作者： Liu, Zeyu Li, Zhengwei Wei, Jiachen Li, Houcheng Zou, Yongxiang Meng, Deyuan Cheng, Long Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China

ISBN: (纸本)9798350372601

The optical waveguide bending sensor offers numerous advantages, including high sensitivity, compact size, immunity to electromagnetic interference, corrosion resistance, and biocompatibility. These attributes have led to its extensive adoption in robotics systems. This study introduces a highly sensitive optical waveguide bending sensor with a wide range. Structural optimizations are implemented in the standard waveguide system to minimize interference from ambient light and unwanted deformation. The responses of four core materials to different curvatures and bending angles are thoroughly examined. The experimental findings confirm the efficacy of the cladding modifications and reveal distinct sensitive ranges for each material. Building on the results from single-core waveguides, a tri-core waveguide is developed to broaden the sensor's sensitive range from less than 60° to 120°, resulting in over a 30% reduction in the error of bending angle sensing compared to single-core waveguides. Additionally, the sensor's ability to monitor joint angles is demonstrated through evaluations performed on the wrist and ankle joints. © 2024 ieee.

关键词： Corrosion resistance

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Optimization and Performance Evaluation of sensor-Based Smart Parking systems: A Case Study Approach 1

Optimization and Performance Evaluation of Sensor-Based Smar...

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1st ieee international conference on Advances in computing, Communication and Networking, ICAC2N 2024

作者： Rathore, Rachna Mohammed, Abbasi Imtiaz Saranraj, G. Kumar, Anil Kumar, Javalkar Dinesh Jaitwal, Vaibhav Shrimant Madhav Rao Scindia University Dept. of Mathematics Gwalior India Madhav University Dept. of Commerce & Management Pindwara India Dhanalakshmi Srinivasan College Dept. of CSE Coimbatore India Mangalayatan University Dept. of EEE Aligarh India Lingayas Vidyapeeth Dept. of ECE Faridabad India Chandigarh University Dept. of CSE Chandigarh India

ISBN: (纸本)9798350356816

The abstract introduces a smart parking system designed to alleviate traffic congestion and save time by employing sensors, data protocols, and a live interface through mobile apps. The initial section of this paper provides an expository overview detailing the system's functionality and operation. Furthermore, the study validates the efficacy of smart parking solutions in enhancing convenience and efficiency through empirical analysis of randomized data. © 2024 ieee.

关键词： Data Communication Protocols Iot Based Smart Parking System Parking Challenges Real-Time Parking Monitoring sensor Networks

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EndGraph: An Efficient distributed Graph Preprocessing System 42

EndGraph: An Efficient Distributed Graph Preprocessing Syste...

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

作者： Liu, Tianfeng Li, Dan Tsinghua Univ Beijing Peoples R China

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Graph processing mainly includes two stages, namely, preprocessing and algorithm execution. Most previous proposals for performance enhancement of graph processing systems focus on the algorithm execution stage, and simple ignore the preprocessing overhead. However, in this work, we argue that the cost of preprocessing can not be ignored since the preprocessing time is much longer than the algorithm execution time in state-of-the-art systems. We propose EndGraph, a distributed graph preprocessing system, to improve preprocessing performance. Firstly, for graph partitioning, we find existing systems either assign imbalanced preprocessing workloads or spend too much time on graph partitioning. Hence, EndGraph proposes a novel chunk-based partition algorithm to balance preprocessing workloads and achieve theoretical lower bound of time complexity. Secondly, for graph construction (converting data layout from edge array to adjacency list), existing systems use counting sort, which is not efficient for computation and communication. EndGraph employs a novel two-level graph construction method by carefully decoupling the graph construction into intra-machine and intermachine construction. Our extensive evaluation results show that, compared with five state-of-the-art systems, LFGraph, PowerLyra, PowerGraph, D-Galois, and Gemini, EndGraph can improve the preprocessing performance up to 35.76x (from 4.72x). To show the generality of EndGraph, we integrate it with D-Galois and Gemini, and it improves the end-to-end (including preprocessing and algorithm execution) graph processing performance up to 7.44 x (from 2.96 x ).

关键词： Graph processing distributed Preprocessing

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High Capacity Multiresonant Chipless RFID sensor Tag For IoT Applications 3

High Capacity Multiresonant Chipless RFID Sensor Tag For IoT...

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3rd international conference on Communication, computing and Digital systems, C-CODE 2023

作者： Jabeen, Iqra Amin, Yasar Tenhunen, Hannu University of Engg and Technology Dept.of Telecommunication Engg Taxila Pakistan University of Turku Dept.of Information Technology Turku Finland

ISBN: (纸本)9798350332391

A novel, high-density, miniature and compact chip- less RFID sensor tag is presented in this article. The proposed work comprises fourteen nested quatrefoil-shaped slot resonators for ID coding with the additional feature of printability and sensitivity. The geometrical configuration consists of several quatrefoil slots of various sizes distributed in a concentric *** unique feature of the presented tag is exhibiting a humidity sensing feature with the deployment of silver nano-ink particle as a radiator by keeping the high code density of 21.8 bits/cm2 in comparison with existing reported works. A bit coding sequence is observed in the frequency spectra from 5 GHz-24 GHz while maintaining a compact size of 8 mm× 8 mm. Further, the performance of the proposed tag is evaluated for numerous substrates, including Rogers RT/Duroid/5880, Taconic (TLX-8), F4BM and Kapton HN, allowing it to be employed in a variety of environments. Additionally, the realized tag structure possesses angular stability at various polarization angles up to 900. This particular tag is deemed to be a suitable choice for future product identification and Internet of Things (IoT) systems. © 2023 ieee.

关键词： Internet of things

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Decentralised Biomedical Signal Classification using Early Exits 21

Decentralised Biomedical Signal Classification using Early E...

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21st ieee Interregional NEWCAS conference (NEWCAS)

作者： Li Xiaolin Vandierendonck, Hans Nikolopoulos, Dimitrios S. Ji, Bo Cardiff, Barry John, Deepu Univ Coll Dublin Dublin Ireland Queens Univ Belfast Belfast Antrim North Ireland Virginia Tech Blacksburg VA USA

ISBN: (纸本)9798350300246

This paper presents a decentralised signal classification approach for data acquired using Internet of Things (IoT) wearable sensors. Traditionally, data from IoT sensors are processed in a centralised fashion, and in a single node. This approach has several limitations, such as high energy consumption on the edge sensor, longer response times, etc. We present a distributed processing approach for convolutional neural network (CNN) based classifiers where a single CNN model can be split into multiple sub-networks using early exits. To reduce the transfer of large feature maps between sub-networks, we introduced an encoder-decoder pair at the exit points. Processing of inputs that can be classified with high confidence at an exit point will be terminated early, without needing to traverse the entire network. The initial sub-networks can be deployed on the edge to reduce sensor energy consumption and overall complexity. We also experimented with multiple exit point locations and show that the point of exit can be adjusted for trade-offs between complexity and performance. The proposed system can achieve a sensitivity of 98.45% and an accuracy of 97.55% for electrocardiogram (ECG) classification and save 60% of the data transmitted wirelessly while reducing 38.45% of the complexity.

关键词： ECG classification Arrhythmia Decentralised Inferencing distributed Network Deep Learning

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Hermes: Memory-Efficient Pipeline Inference for Large Models on Edge Devices 42

Hermes: Memory-Efficient Pipeline Inference for Large Models...

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42nd international conference on Computer Design

作者： Han, Xueyuan Cai, Zinuo Zhang, Yichu Fan, Chongxin Liu, Junhan Ma, Ruhui Buyya, Rajkumar Shanghai Jiao Tong Univ ParisTech Elite Inst Technol Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China Shanghai Jiao Tong Univ UM SJTU Joint Inst Shanghai Peoples R China Shanghai Aerosp Syst Engn Inst Shanghai Peoples R China Univ Melbourne Cloud Comp & Distributed Syst CLOUDS Lab Melbourne Vic Australia

ISBN: (纸本)9798350380415;9798350380408

The application of Transformer-based large models has achieved numerous success in recent years. However, the exponential growth in the parameters of large models introduces formidable memory challenge for edge deployment. Prior works to address this challenge mainly focus on optimizing the model structure and adopting memory swapping methods. However, the former reduces the inference accuracy, and the latter raises the inference latency. This paper introduces PIPELOAD, a novel memory-efficient pipeline execution mechanism. It reduces memory usage by incorporating dynamic memory management and minimizes inference latency by employing parallel model loading. Based on PIPELOAD mechanism, we present Hermes, a framework optimized for large model inference on edge devices. We evaluate Hermes on Transformer-based models of different sizes. Our experiments illustrate that Hermes achieves up to 4.24x increase in inference speed and 86.7% lower memory consumption than the state-of-the-art pipeline mechanism for BERT and ViT models, 2.58x increase in inference speed and 90.3% lower memory consumption for GPT-style models.

关键词： Edge computing Memory optimisation Large model inference Pipeline execution.

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Resiliency Measurement Framework for distributed Energy Resource Integrated Distribution Networks

Resiliency Measurement Framework for Distributed Energy Reso...

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2024 international conference on Advances in computing, Communication, Electrical, and Smart systems, iCACCESS 2024

作者： Kuriakose, Eldho Aziz, Asma Qays, Md Ohirul Hossain, Md. Liton Hasan, Rasedul Sohan, Moshiur Rahman School of Engineering Edith Cowan University JoondalupWA6027 Australia University of Liberal Arts Bangladesh Department of Electrical and Electronic Engineering Dhaka1207 Bangladesh Aurecon Australasia North SydneyNSW2060 Australia

ISBN: (纸本)9798350350289

External and internal disruptions into power system stability motivates to research on a qualified grid resilience system. With this, indispensability of electricity infrastructure emphasizes the critical need for power system resilience in facing interruptions, especially extreme incidents e.g. natural disasters, deliberate attacks etc. Thus, this study concentrates on distribution networks, emphasizing the effect of natural disasters and integration of distributed energy resources to the grid. It offers a contemporary overview of grid resilience, introducing an advanced framework to assess distribution network resilience and analyse relevant terminologies. An adaptable grid resiliency framework derived from a meticulous examination of existing metric structures is presented in this study. PSCAD software is further utilized to present the real-world grid system analysis. The proposed model is, additionally, assessed by applying into an ieee 9 bus test system to elucidate its potential impacts and feasible solution. The designed circuit demonstrate the recovery of faulty bus from potential blackout conditions with the help of integration of renewable energy sources. © 2024 ieee.

关键词： Electric power distribution

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