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检索条件"任意字段=IEEE International Conference on Data Science and Data Intensive Systems"

共 86302 条记录，以下是331-340 订阅

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Integrating Multimodal Geospatiotemporal data for Societal, Economic, and Environmental (SEE) Analysis of Large Agricultural systems

Integrating Multimodal Geospatiotemporal Data for Societal, ...

引用

2024 ieee international conference on Big data, Bigdata 2024

作者： Akanbi, Olatunde D. Li, Jiaqi Mandayam, Vibha Nihar, Arafath Wu, Yinghui Bruckman, Laura S. Yarus, Jeffrey M. Barcelos, Erika I. French, Roger H. Sdle Department of Material Science and Engineering Case Western Reserve University ClevelandOH United States Department of Material Science and Engineering Case Western Reserve University ClevelandOH United States Department of Computer and Data Science Case Western Reserve University ClevelandOH United States United States

ISBN: (纸本)9798350362480

关键词： Agricultural economics

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A New Transmission Scheme: Semi-Blind Channel Estimation Combined with Precoding 13

A New Transmission Scheme: Semi-Blind Channel Estimation Com...

引用

13th ieee international conference on Communications, Circuits and systems (ICCCAS)

作者： Fan, Kuangang Yang, Chunrong Tan, Peiao Jiangxi Univ Sci & Technol Sch Elect Engn & Automat Key Lab Magnet Levitat Technol Ganzhou Ganzhou Peoples R China

ISBN: (纸本)9798350386288;9798350386271

In this paper, we first introduce the transmission model of MIMO-OFDM. A semi blind estimation method based on noise subspace is proposed to overcome some limitations of blind estimation methods. Then a new transmission scheme is proposed, in which the channel information obtained by blind or semi blind estimation will be used for the precoder. At the end of this paper, the performance of this data transmission scheme is analyzed and discussed, and the parameters, especially the size of the data frame, can be adjusted according to the needs, which can affect the transmission efficiency and delay. Adjusting parameters according to channel conditions and communication requirements is crucial for optimizing the efficiency and robustness of transmission systems.

关键词： MIMO-OFDM Semi-blind estimation Precoding data transmission scheme

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Towards Inference of Original Graph data Information from Graph Embeddings

Towards Inference of Original Graph Data Information from Gr...

引用

international Joint conference on Neural Networks (IJCNN)

作者： Li, Xinyang Lei, Xinyu Li, Yantao Qin, Huafeng Hu, Yiwen Chongqing Univ Coll Comp Sci Chongqing Peoples R China Michigan Technol Univ Dept Comp Sci Houghton MI USA Chongqing Technol & Business Univ Sch CSIE Chongqing Peoples R China Michigan State Univ Dept CSE E Lansing MI USA

ISBN: (纸本)9781665488679

This paper studies to what extent an adversary (without the original graph data) can recover the original raw graph data from graph embeddings. To quantify the original graph data information leakage from graph embeddings, we develop a deep neural network model InferNet that can be used by adversaries to infer the original graph data information from an adversary-accessible graph embedding database. Specifically, we propose the data-free reversed knowledge distillation (KD) technique to support InferNet training even if the original graph dataset is absent. To improve the performance of InferNet, we design two cycle-consistency loss functions to have an interactive training of InferNet over three series of datasets. Our intensive experiments demonstrate that InferNet can infer the original graph data information from the graph embedding dataset with high accuracy.

关键词： Graph neural networks graph embeddings privacy knowledge distillation cycle-consistency loss

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Joint Coverage and Latency for data-intensive Application Deployment in Mobile Edge Computing Environment 36

Joint Coverage and Latency for Data-intensive Application De...

引用

36th international conference on Software Engineering and Knowledge Engineering, SEKE 2024

作者： Gu, Yubiao Wang, Yaping Zhang, Zhaohui Wang, Pengwei School of Computer Science and Technology Donghua University China

ISBN: (纸本)1891706594

Mobile edge computing (MEC) is an emerging computing paradigm where application vendors deploy applications at the edge of the network by configuring computing and storage resources, to achieve low latency, high bandwidth, and exceptional user experience. However, end-users are extremely sensitive to the response latency of data-intensive applications, which is one of the main challenges in MEC. Therefore, application vendors must ensure that data-intensive applications deployed on edge servers have the lowest possible response latency, thereby maximizing the total Quality of Experience (QoE) for end-users. To address this challenge, this paper jointly considers user coverage and response latency as QoE, aiming to obtain application deployment strategy within the constraints of deployment budget, while maximizing the total QoE. We propose the data-intensive Application Deployment (DIAD) problem and model it as a constrained optimization problem. By taking QoE into account, a greedy heuristic strategy (DIAD-G) is proposed to effectively tackle the DIAD problem. Extensive experimental evaluations are conducted on real-world datasets, comparing DIAD-G with five representative methods. The experimental results demonstrate the effectiveness of this method, with total QoE for end-users significantly surpassing other methods and achieving the best performance. © 2024 Knowledge systems Institute Graduate School. All rights reserved.

关键词： Mobile edge computing

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Adaptive Sampling for Real-Time Status Update systems under Non-Stationary Delay Statistics

Adaptive Sampling for Real-Time Status Update Systems under ...

引用

ieee/CIC international conference on Communications in China (ICCC)

作者： Gu, Yifan Qu, Zhi Shenzhen Univ State Key Lab Radio Frequency Heterogeneous Integ Shenzhen 518060 Guangdong Peoples R China Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Guangdong Peoples R China

ISBN: (纸本)9798350377675;9798350377682

In this paper, we study the sampling rate design problem of status update systems under unknown and non-stationary delay statistics, where the delay statistics include both the distribution of transmission delay and the packet loss probability. When the delay statistics are non-stationary, short-term average Age-of-Information (AoI) is much more critical than the long-term average AoI. Motivated by this fact, we formulate a sampling rate control problem by minimizing the Mean Squared Error (MSE) of the average AoI in each control cycle to a predefined AoI target, such that both the short-term and long-term average AoI approach to the target. The formulated problem is different from the existing works on the minimization of long-term average AoI under known or stationary delay statistics. Based on the average AoI feedback at the end of each control cycle, we first present a Delta Sampling (DS) policy with a fixed updating step. Because the DS policy may converge slowly, we then propose a novel Adaptive Sampling Control (ASC) policy to adjust the sampling rate dynamically. The main challenge in developing ASC is the lack of an explicit model to reflect the relationship between the sampling rate and average AoI. To overcome this issue, we design an equivalent dynamic linearization data model with a Pseudo-Partial Derivative (PPD), where the unknown features of delay statistics can be captured by the time-varying PPD. By estimating the PPD in each control cycle, ASC can determine a suitable sampling rate based on the tractable data model. Numerical results show that the proposed ASC policy outperforms the DS, zero waiting, and fixed sampling policies significantly in terms of MSE by more than 100% under unknown and non-stationary delay statistics.

关键词： Age of Information data Freshness Short-Term Age Non-Stationary Delay Statistics

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Performance Analysis of data Processing in Distributed File systems with Near data Processing

Performance Analysis of Data Processing in Distributed File ...

引用

2024 international Symposium on Networks, Computers and Communications, ISNCC 2024

作者： Hou, Shiyue Tallent, Nathan R. Wang, Li Mi, Ningfang Northeastern University Department of Electrical and Computer Engineering MA United States Pacific Northwest National Laboratory Advanced Computations and Maths Division RichlandWA United States

ISBN: (纸本)9798350364910

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark [1] and Hadoop [2] manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape. © 2024 ieee.

关键词： data assimilation

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Osmotic Computing Based Secure Resource Orchestration Scheme for Vehicular Communication 17

Osmotic Computing Based Secure Resource Orchestration Scheme...

引用

17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Garg, Deepanshu Angurala, Mohit Bali, Rasmeet S. Kumar, Neeraj Chandigarh University Computer Science & Engineering Department India Guru Nanak Dev University Computer Science Department India Thapar University Patiala Computer Science & Engineering Department India

ISBN: (纸本)9798331531195

The advancement in technology leads to provide an efficient communication among vehicles to offload resource-intensive tasks for transportation-based services. However, it may cause issue related to efficient secure resource utilization among vehicular nodes. The key reason behind these considerations are the high mobility of vehicles and their high computational requirements for task execution. To solve these issues, an osmotic computing based vehicular communication scheme has been proposed. The primary objective of the scheme is to provide a communication model which can perform effective secure resource management among static or dynamic vehicular nodes through Osmotic Computing. By utilizing the key components of osmotic computing such as osmotic resource manager and node manager, numerous resources have been shared with the vehicles in an effective way. The performance of the proposed scheme has been evaluated using simulation. Results obtained show that the proposed scheme outperform the existing schemes in terms of various performance evaluation parameters. © 2025 ieee.

关键词： data privacy

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Performance Evaluation of Hybrid State Estimation Using Real TSO data Sources 18

Performance Evaluation of Hybrid State Estimation Using Real...

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18th international conference on Probabilistic Methods Applied to Power systems (PMAPS)

作者： ter Vehn, Anton Nordstrom, Lars Apelfrojd, Senad KTH Royal Inst Technol Elect Power & Energy Syst Stockholm Sweden Svenska Kraftnat Sundbyberg Sweden

ISBN: (纸本)9798350372793;9798350372786

To gain insight into grid dynamics, many transmission system operators are in the process of deploying phasor measurement units. However, observing all dynamic events which occur can still be challenging due to limited deployment and communication malfunctions, i.e. unmetered buses and missing data. The issue has incentivized the research into hybrid state estimation - where classic static state estimation is integrated with dynamic state estimation. The development of such techniques is still ongoing, and there are few real-world deployments. Using weighted least squares, the extended Kalman filter a nd the unscented Kalman filter, t his p aper p resents a h ybrid state estimation technique validated on data from a transmission system operator, where the PMUs are sparsely placed, implying low observability. The results demonstrate that the estimation error is low while exposed to dynamic phenomena, even with sparse PMU deployment.

关键词： Hybrid State Estimation Dynamic State Estimation State Estimation WAMS SCADA

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Factual Accuracy Checking by Validating Numerical data in Financial Summaries

Factual Accuracy Checking by Validating Numerical Data in Fi...

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2024 ieee international conference on Big data, Bigdata 2024

作者： Bera, Anup Goel, Aditya Accenture India

ISBN: (纸本)9798350362480

Ensuring factual accuracy in generated summaries is essential, particularly when summarizing technical documents like financial reports, where even slight errors in numerical data can lead to significant misinterpretation. While recent advancements in automatic abstractive summarization have improved the quality and comprehensiveness of summaries, they often fall short in guaranteeing factual accuracy, especially when dealing with complex numerical information. In financial reports, this challenge is particularly acute, as these documents contain key figures that must be represented correctly to maintain transparency and trust. This paper introduces a framework specifically designed to validate the numerical data in summaries without requiring human-written reference summaries. Our approach leverages a T5-based model to predict masked numerical values in the summary using the original financial report as context. By cross-checking these predicted values with the actual data, we can determine the factual correctness of individual sentences in the summary. To manage the size and complexity of financial documents, we split the source report into smaller passages, using only the most relevant sections to validate the masked numerical data in the summary. This method addresses the unique challenges of summarizing documents rich in numerical data, providing a more accurate way to verify the factual integrity of summaries in financial and other data-intensive domains. The code and results are available at https://***/anupb08/factualaccuracy © 2024 ieee.

关键词： data accuracy

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A Hierarchical Heterogeneous IoT Time Series data Index for NVM

A Hierarchical Heterogeneous IoT Time Series Data Index for ...

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2024 ieee international conference on systems, Man, and Cybernetics, SMC 2024

作者： Cai, Tao Lei, Tianle Niu, Dejiao Dai, Jianfei Huang, Zeyu Ni, Qiangqiang The School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China

ISBN: (纸本)9781665410205

The index plays an important role in the performance of IoT time series data storage systems. However, the current index designed for HDD or SSD can not adapt to the characteristics of IoT time series data and effectively leverage the performance advantages of NVM. A new hierarchical heterogeneous index is designed for IoT time series storage system based on NVM. The structure is given first and the group consists of several data blocks used to manage IoT time series data. The ordered construction strategy is designed for skip list by the sustained generation of IoT time series data and creating the index for each IoT time series data block group. Meanwhile, a compression and reconstruction strategy for skip list is given to effectively utilize NVM. Then, a TS- Radix tree is presented to index IoT time series data block groups by the temporal characteristics of IoT time series data. Finally, a prototype of it is implemented and YCSB-TS is used to evaluate. The results show that this new index can effectively improve the throughput of random and range queries by up to 262.4%, surpassing the performance of InfluxDB, OpenTSDB, and KairosDB. © 2024 ieee.

关键词： indexing IoT time series data NVM storage device storage system Time series data storage system

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