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检索条件"任意字段=IEEE International Conference on Distributed Computing in Sensor Systems"

共 30727 条记录，以下是311-320 订阅

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VMR-Tree: Efficient and Verifiable Location-based kNN Queries on Blockchain 22

VMR-Tree: Efficient and Verifiable Location-based kNN Querie...

引用

ieee 22nd international conference on Trust, Security and Privacy in computing and Communications (TrustCom) / BigDataSE conference / CSE conference / EUC conference / ISCI conference

作者： Teng, Yiping Liu, Lei Qi, Jiawei Pan, Haochun Fan, Chunlong Shenyang Aerosp Univ Sch Comp Large Scale Distributed Syst Lab Liaoning Shenyang Peoples R China

ISBN: (纸本)9798350381993;9798350382006

In recent years, blockchain technology has received extensive attention and applied in various fields including healthcare, IoT and database systems. Utilizing the decentralization and anti-tampering properties, the blockchain provides potential solutions to achieve verification of data queries, without the assumption of the trusted third parties in traditional data verification studies. However, for kNN queries, a common query type in practical location-based scenarios, few existing solutions can directly support the location-based kNN query processing and result authentication based on blockchain. To address this problem, in this paper, we propose a blockchain-based verifiable kNN query processing method. In this method, we first design a novel authenticated data structure called VMR-Tree, which stores the data objects and their neighboring objects in leaf nodes and stores the hash values used for data verification in non-leaf nodes. To verify the results with the minimum size of verification objects (VOs), we design a query result verification method based on the blockchain, in which the client can verify the query results by processing the VOs generated based on the proposed VMR-Tree index and the blockchain. Besides, we further propose an optimization algorithm to reduce the size of VOs. We theoretically analyze the computational complexity and security guarantees of the proposed approaches. We also conducted extensive experiments on real and synthetic datasets to evaluate the efficiency of the proposed method on the result verification of location-based kNN queries.

关键词： Blockchain kNN Query Query Authentication

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Adaptive distributed UAV-Borne Radar Point Fusion Algorithm Based on Nearness Degree 6

Adaptive Distributed UAV-Borne Radar Point Fusion Algorithm ...

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6th ieee international conference on Power, Intelligent computing and systems, ICPICS 2024

作者： Zhou, Yansong Wang, Wei Zhang, Jun Xi'an Electronics and Engineering Research Institute Xi'an China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374315

This paper analyzes and researches the problems of poor robustness and high arithmetic complexity that exist in the traditional methods of distributed radar target detection and tracking, and proposes a point track fusion algorithm based on fuzzy closeness theory. The algorithm first uses the fuzzy closeness to evaluate the point track quality of each radar, and calculates the weight value of each radar according to the closeness, and then utilizes the obtained weight value to carry out adaptive allocation and point track fusion, which can effectively improve the quality and efficiency of point track fusion, and then improve the effect of point track fusion and filtering tracking of distributed UAV-borne radar. Simulation results show that the computational complexity and filter tracking accuracy of point fusion using the algorithm proposed in this paper are better than that of the traditional algorithm, which has better practicality and engineering application value. © 2024 ieee.

关键词： Radar tracking

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A New Scalable distributed Homomorphic Encryption Scheme for High Computational Complexity Models 19

A New Scalable Distributed Homomorphic Encryption Scheme for...

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

作者： Almaini, Amar Folz, Jakob Woelfl, Dominik Al-Dubai, Ahmed Schramm, Martin Heigl, Michael Edinburgh Napier Univ Deggendorf Inst Technol Deggendorf Germany Deggendorf Inst Technol Deggendorf Germany Edinburgh Napier Univ Edinburgh Midlothian Scotland

ISBN: (纸本)9798350333398

Due to the increasing privacy demand in data processing, Fully Homomorphic Encryption (FHE) has recently received growing attention for its ability to perform calculations over encrypted data. Since the data can be processed in encrypted form and the output remains encrypted, only an authorized user or a user who holds the key can decrypt the data and understand its meaning. Hence, it is possible to securely outsource data processing to untrustworthy but powerful public computing resources on the edge. However, due to the high computational complexity, FHE-based data processing experiences scalability related concerns. It is currently unclear whether FHE can be used to solve large-scale problems. In this paper, we propose a novel general distributed FHE-based data processing approach as a concrete step towards solving the scalability challenge. The main idea behind our approach is to use slightly more communication overhead for a shorter computing circuit in FHE, hence, reducing the overall complexity. We verify our new model's efficiency and effectiveness by comparing the distributed approach with the central approach over various FHE schemes (CKKS, BGV, and BFV). This is performed using one of the most popular libraries of FHE "Microsoft SEAL", by performing specific mathematical operations and observing the time consumed. The empirical results demonstrate that the proposed approach results in a significant reduction in time, up to 54% compared to the traditional central approach.

关键词： Fully Homomorphic Encryption distributed Data Processing Microsoft SEAL Security Edge computing

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Interpreting Temporal Dynamics in distributed Fuzzy Cognitive Maps for Time Series Prediction 11

Interpreting Temporal Dynamics in Distributed Fuzzy Cognitiv...

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11th ieee international conference on Advances in computing and Communications, ICACC 2024

作者： Haritha, K. Judy, M.V. Cochin University of Science and Technology Department of Computer Applications Ernakulam India

ISBN: (纸本)9798350379136

Fuzzy Cognitive Maps (FCMs) are powerful tools for the modeling of complex systems, one of which is time series modeling. Although advocated for their interpretability, existing methods measure concept relevance based on static structural features often overlooking the dynamic influences over the time. This paper presents a novel SHapley Additive exPlanations (SHAP) framework based distributed FCM model. The proposed approach invokes functions to determine the SHAP concept relevance scores for the distributed Fuzzy Cognitive Maps (DFCMs) for time series prediction, marginalizing over each concept and comparing the predicted states to an expected baseline iteratively. This method is interpreted as measuring the time-varying impact of each concept through the dynamic course of the system. The SHAP-based approach improves the interpretability and application of FCMs to the modeling of complex time-course systems. © 2024 ieee.

关键词： Fuzzy Cognitive Maps

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Transmission Order Optimization of Coded distributed computing in Heterogeneous Wireless Multiple-Access Network 19

Transmission Order Optimization of Coded Distributed Computi...

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

作者： Wu, Yaonan Gu, Shushi Zhang, Qinyu Zhang, Ning Xiang, Wei Harbin Inst Technol Shenzhen Guangdong Prov Key Lab Aerosp Commun & Networking Shenzhen 518055 Peoples R China Peng Cheng Lab Shenzhen 518052 Peoples R China Univ Windsor Windsor ON N9B 3P4 Canada La Trobe Univ Sch Comp Engn & Math Sci Melbourne Vic 3086 Australia

ISBN: (纸本)9798350333398

Coded distributed computing (CDC) has been recently proposed as a promising technique to mitigate the straggler effect in the distributed computing cluster which consists of workers with different computing capabilities, and to reduce the end-to-end task execution latency. However, the heterogeneity of computing and transmission will critically impact the latency performance, especially in the wireless multiple-access network. In this paper, we use CDC over the heterogeneous wireless multiple-access network (HWMAN) including both computation stragglers and transmission stragglers with various capabilities. In order to reduce the computing task completion latency (computing latency and transmission latency), the optimal stop computing time of workers and the sorting order of result transmission back are obtained via two designed algorithms, namely straggler detection and ordered transmission (SDOT) and worker sorting and ordered transmission (WSOT), respectively, which not only fully utilize the computing results of stragglers, but also improve the total latency performance compared with other existing state-of-the-art algorithms.

关键词： heterogeneous wireless multiple-access network coded distributed computing straggler detection transmission order latency optimization

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Scalable Node Embedding Algorithms using distributed Sparse Matrix Operations

Scalable Node Embedding Algorithms using Distributed Sparse ...

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Ranawaka, Isuru Azad, Ariful Indiana Univ Bloomington IN 47405 USA

ISBN: (纸本)9798350364613;9798350364606

We introduce a distributed memory parallel algorithm for force-directed node embedding that places vertices of a graph into a low-dimensional vector space based on the interplay of attraction among neighboring vertices and repulsion among distant vertices. We develop our algorithms using two sparse matrix operations, SDDMM and SpMM. We propose a configurable pull -push -based communication strategy that optimizes memory usage and data transfers based on computing resources and asynchronous MPI communication to overlap communication and computation. Our algorithm scales up to 256 nodes on distributed supercomputers by surpassing the performance of state-of-the-art algorithms

关键词： Embedding SDDMM Sparse Matrix Computation SpMM

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Proceedings - 2024 ieee international conference on Edge computing and Communications, EDGE 2024

Proceedings - 2024 IEEE International Conference on Edge Com...

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8th ieee international conference on Edge computing and Communications, EDGE 2024

ISBN: (纸本)9798350368499

The proceedings contain 20 papers. The topics discussed include: split DNN inference for exploiting near-edge accelerators;DONNA: distributed optimized neural network allocation on CIM-based heterogeneous accelerators;reliable network performance for edge networks with QoS-aware adaptive routing;the impact of GPU on containerized computer vision applications on edge nodes;cross network layer cognitive service orchestration in edge computing systems;a case for deploying dynamic neural network on edge-cloud continuum environment;data sharing-aware online algorithms for task allocation in edge computing systems;and SlimNet: a lightweight attentive network for speech-music-noise classification and voice activity detection.

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Modeling of Wireless sensor Network Based on Functioning Parameters of Unevenly distributed Nodes 17

Modeling of Wireless Sensor Network Based on Functioning Par...

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ieee 17th international conference on the Experience of Designing and Application of CAD systems (CADSM)

作者： Belej, Olexander Nestor, Natalia Artyshchuk, Iryna Spas, Nataliia Lviv Polytechn Natl Univ Dept Comp Aided Design Lvov Ukraine

ISBN: (纸本)9798350310856

Connection and routing parameters of wireless sensor networks are considered for static topologies and uniform distribution of nodes. Most of the studied models do not take into account the parameters of message connectivity and their delivery time between unevenly distributed nodes. in the proposed study, models of connectivity analysis and message delivery between unevenly distributed nodes are developed. Models of wireless sensor networks with uniform and normal distribution of nodes and research on the network connectivity parameter for these models are proposed. Network models with different types of distributions are built based on the Erdosh-Rani random graph model, which allows describing of the connectivity of wireless sensor networks as the connectivity of a random graph, that is, to determine the connectivity of wireless sensor networks with the probability of finding the distance between two vertices of the graph. Simulation models with a uniform and normal distribution of nodes are implemented to investigate the probability of network connection. The choice of these types of distribution is explained by possible real distributions of nodes in the studied area.

关键词： information system wireless sensor network network model multimodal distribution of nodes simulation model graph vertices

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Partial-distributed Filtering for Fault Detection, Isolation and Accommodation in Natural-Gas Pipelines 27

Partial-Distributed Filtering for Fault Detection, Isolation...

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27th international conference on Information Fusion (FUSION)

作者： Shaheen, Khadija Chawla, Apoorva Uilhoorn, Ferdinand Evert Rossi, Pierluigi Salvo Norwegian Univ Sci & Technol Dept Elect Syst N-7491 Trondheim Norway Warsaw Univ Technol Dept Gas Engn Warsaw Poland SINTEF Energy Res Dept Gas Technol N-7491 Trondheim Norway

ISBN: (纸本)9798350371420;9781737749769

This paper explores an innovative method for distributed state estimation aimed at reducing computational complexity while detecting sensor faults in natural gas pipelines. The proposed framework utilizes a partial-distributed ensemble Kalman filter (EnKF), comprising linear local filters and a non-linear main filter. The main filter handles non-linear computations during the time update, while the simultaneous operation of linear local filters manages linear computations during the measurement update. These local filters generate distinct local state estimates based on their specific sensor measurements, which are then transmitted to an information mixer to compute fault-free state estimates. Moreover, a fault diagnosis strategy is developed using local state variances and residuals. Faulty sensors are identified and isolated by comparing these metrics against a threshold. Additionally, an adaptive thresholding approach is incorporated to enhance effective fault identification. The effectiveness of the proposed technique is demonstrated in systems characterized by high nonlinearity and dimensionality, and featuring simultaneous multiple sensor faults, through extensive simulations and comparative analyses.

关键词： Partial-distributed ensemble Kalman filter model-based technique state estimation fault diagnosis adaptive threshold multiple sensor faults natural-gas pipelines

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distributed HBase Cluster Storage Engine and Database Performance Optimization 23

Distributed HBase Cluster Storage Engine and Database Perfor...

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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： Zhang, Hao Rong-Li, G.A.I. School of Information Engineering Dalian University Dalian China

ISBN: (纸本)9781665494571

With the development of network society, individuals and enterprises generate massive data every day. However, the traditional relational MySQL database has poor performance in storing and processing massive data. In the case of huge amount of data, MySQL may even crash, which obviously cannot meet the needs of massive data storage. Obviously, with more and more emphasis on user-friendliness, the storage and processing application of massive data determine the future development of enterprises. This paper discusses the storage engine, high concurrency, architecture and distributed cluster of HBase, and then compares the performance differences between MySQL and HBase optimized with Bloom filter(Bloom HBase) on Linux platform. © 2021 ieee.

关键词： Concurrent computing Smart cities Linux distributed databases Memory Big Data Computer crashes

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