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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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An Efficient distributed Spatiotemporal Index for Parallel Top-k Frequent Terms Query

An Efficient Distributed Spatiotemporal Index for Parallel T...

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ieee international conference on Big Data and Smart computing (BigComp)

作者： Van Le, Hong Takasu, Atsuhiro Natl Inst Informat Tokyo Japan

ISBN: (纸本)9781665421973

As rich user-generated geotagged data, microblogs have been exploited in several data analytic contexts, e.g., popular topic trends, popular site detection, and geo-targeted recommendation. To support such analysis, we developed an efficient multidimensional index structure and parallel processing approaches for top-k frequent spatiotemporal terms query: a common analytic query on geotagged social data. Given a spatiotemporal range, the query aggregates the frequencies of terms among the social posts and identifies the most frequent terms in that range. The present work is different from studies that extract this information from stream data because we focus on large historical datasets. The key challenge is to improve query performance with minimum storage requirements. We propose a distributed index structure that transforms spatiotemporal coordinates into unique codes to generate rowkeys in key-value stores (KVSs) and balances the data distribution across distributed systems. Then, we utilize data localization to calculate sorted term lists (STLs) in parallel. To reduce input/output between KVSs and the client, we theoretically estimate the necessary length of STLs to calculate the top-k frequent terms and send only a part of the STLs to the client. Several experiments, on both real and artificial datasets, showed our approach to have both lower space requirements and better query performance than baseline approaches.

关键词： parallel processing top-k computing spatiotemporal database key-value store geotagged social data

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A Predictive Profiling and Performance Modeling Approach for distributed Stream Processing in Edge 40

A Predictive Profiling and Performance Modeling Approach for...

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40th ieee international conference on Data Engineering, ICDE 2024

作者： Geren, Hasan Sohrabi, Nasrin Tari, Zahir Moustafa, Nour RMIT University Melbourne Australia Deakin University Melbourne Australia UNSW/ADFA Canberra Australia

ISBN: (纸本)9798350317152

The advent of edge computing has allowed the continuously generated data to be processed closer to their sources instead of being sent to the cloud for processing. Given the heterogeneous and limited computational resources and dynamic nature of edge computing, stream processing systems need an accurate and easily accessible performance modeling/measurement to perform efficiently in edge environments. This paper proposes a predictive profiling model to enable measuring the performance of a system by predicting the operators' processing time on heterogeneous devices without having to carry out the testing on individual devices. This profiling model comprises a quadratic function to generate CPU clock speed/processing time curves for each operator. By using these curves, the model predicts the processing times of operators without requiring any extra profiling runs. Moreover, a performance model is proposed to deal with (performance) degradation of stream processing applications by modeling their topologies as systems comprising M/M/1 queues. The model uses the performance expectations of queueing models to define the data transfer rates inside topologies and uses Integer Linear Programming to specify the maximum input rate and an operator placement plan that can process that input rate. Experimental results showed that the profiling approach predicts the processing times of 17 operators with an average error rate of 5%. The performance model finds the maximum input rate accurately, while the operator placement plan achieves up to 84% higher throughput and 70% less latency in AWS EC2 instances and 257% higher throughput and 66% less latency in real hardware compared to the default resource-aware scheduler of Apache Storm. © 2024 ieee.

关键词： Edge computing

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IoT Based Healthcare Checking Framework 5

IoT Based Healthcare Checking Framework

引用

5th ieee international conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Pandey, Ratnesh Kumar Singh, Narendra Pal Verma, Kuldeep Chand, Jay Invertis University Department of Computer Science & Engineering U.P. Bareilly India Kamla Nehru Institute of Physical and Social Sciences Department of Computer Science & Engineering Faridipur U.P. Sultanpur India

ISBN: (纸本)9798350383522

In today's world, technology has a meaning of its own and plays an important role in many industries. Wireless technology has the potential to benefit the healthcare industry by improving healthcare facilities and providing timely remote monitoring and contactless technology. The patient's response to treatment is monitored by patient monitoring sensors. When used correctly, both types of sensors can track changes and provide some access to the system. Therefore, it is necessary to closely examine changes in the system. So IoT fills the gap between all of them. The current system has been discontinued and a new improved system is being used for treatment. It is built on cloud database APIs and at the Android level. IoT systems are also a source of artificial intelligence. IoT systems conduct research in space. This technology can be used to manage and monitor potentially infectious patients (PIPs) during lockdown to address critical health care quality issues. All vehicles in the project are at the limit of their capabilities. Use a wireless system while transmitting. These venues are the best choice for important events. © 2024 ieee.

关键词： API Layer ECG sensor MCU ESP8266 PIP Stage for IoT Bridge

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Optimizing sensor Placement for Air Quality Monitoring System Using Particle Swarm Optimization

Optimizing Sensor Placement for Air Quality Monitoring Syste...

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2023 international conference on Advanced computing and Communication Technologies, ICACCTech 2023

作者： Gupta, Divyansh Thakur, Samarth Gode, Aditya Jagtap, Kunal Gutte, Vitthal S. Dr. Vishwanath Karad Mit World Peace University Department of Computer Engineering and Technology Maharashtra Pune India

ISBN: (纸本)9798350380880

In this study, a Particle Swarm Optimization (PSO) framework for placing sensors in air quality monitoring systems is introduced. Effective sensor deployment has become crucial due to the growing significance of precise air quality data for environmental wellbeing and public health. The complexity of PSO, a bio-inspired optimization algorithm, and its applicability to the problem of carefully placing sensors to optimize data coverage while reducing resource use, are explored in depth in this work. The study demonstrates the PSO-based strategy's superior performance over conventional methods through extensive experimentation and evaluation. The outcomes show enhanced data coverage and accuracy, as well as cost-efficiency improvements. This study also highlights the larger effects of optimum sensor location, emphasizing how it affects urban planning, sensible environmental regulations, and pro-active public health initiatives. The study contributes to the continuous development of sensor location optimization approaches and emphasizes the need of data-driven decision-making in solving current air quality concerns. In conclusion, the incorporation of PSO into air quality monitoring systems is a viable way to solve crucial monitoring needs in a world that is changing quickly. © 2023 ieee.

关键词： Decision making

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Assessment of Voltage and Frequency in Islanded Microgrids by Varying Load Parameters Using Modified Gauss-Seidel Power Flow

Assessment of Voltage and Frequency in Islanded Microgrids b...

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2023 ieee international conference on Power Electronics, Smart Grid, and Renewable Energy, PESGRE 2023

作者： Lone, Ashiq Hussain Gupta, Neeraj National Institute of Technology Department of Electrical Engineering Srinagar India

ISBN: (纸本)9798350310573

Power flow studies play a crucial role in the planning and expansion of power systems, particularly with the increasing integration of distributed generation (DG) and the emergence of micro-grids. Micro-grids, which are localised power systems with their own generation and load, have become an attractive option for enhancing the resilience and efficiency of electric supply. The effect of load parameters in conjugation with the Modified Newton Raphson (MNR) power flow has been investigated in this paper. To validate the effectiveness of the proposed method, the MNR algorithm has been implemented and tested on a 6-bus islanded microgrid test bus system. This test system serves as a representative model for evaluating the performance and capabilities of the MNR method in solving power flow analysis for islanded micro-grids. © 2023 ieee.

关键词： distributed generation Microgrid modified Newton Raphson Power flow

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Backup Placement in WSNs in the Network Management distributed Setting 41

Backup Placement in WSNs in the Network Management Distribut...

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ieee 41st international conference on distributed computing systems (ICDCS)

作者： Oren, Gal Barenboim, Leonid Technion Israel Inst Technol Dept Comp Sci Haifa Israel Nucl Res Ctr Negev Sci Comp Ctr Beer Sheva Israel Open Univ Israel Dept Math & Comp Sci Raanana Israel

ISBN: (纸本)9781665449328

sensor nodes are inherently a cheap piece of hardware - due to the common need to use many of them over a large area - and usually contain a small amount of RAM and flash memory, which are insufficient in case of high degree of data sampling. An overloaded sensor can harm the data integrity, or even completely reject incoming messages. The problem gets even worse when data should be received from many nodes, as missing data becomes a more common phenomenon as deployed WSNs grow in scale. As a solution, we consider the Backup Placement problem in networks in the network management distributed setting: Given a network graph G = (V, E), the goal of each vertex v is an element of V is selecting a neighbor, such that the maximum number of vertices in V that select the same vertex is minimized. In cases of an overflow, our distributed Adaptive Clustering algorithm (D-ACR) reconfigures the network, by adaptively and hierarchically re-clustering parts of it, based on the rate of incoming data packages in order to minimize the energy-consumption, and prevent premature death of nodes. In the network management setting of a grid, we proved that a backup placement of load at most O(1) can be maintained within O(log(2) n) update time, and an O(n log(2) n) energy consumption using the constructed ACR tree.

关键词： Backup Placement WSNs Network Management distributed Setting

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Energy-Efficient computing Offloading Policy for MEC-assisted Power sensor Network: A D3QN Approach

Energy-Efficient Computing Offloading Policy for MEC-assiste...

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2023 international conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Guan, Ti Yao, Yushun Yuan, Chao Liu, Fuhao Liu, Yirong Gu, Rentao State Grid Shandong Electric Power Company Jinan China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing China State Grid Laiwu Electric Power Supply Company Jinan China State Grid Binzhou Electric Power Supply Company Binzhou China

ISBN: (纸本)9798350312492

With the deep and close integration of massive renewable and controllable terminals into the next generation smart power grid, the amount of data and various applications with different quality requirements will increase greatly, which will be tough challenges for the power sensor network to provide real-time data collecting and processing, global monitoring, and quick response, etc. Meanwhile, due to the limitation in energy supplement and computing capacity, it is a second issue for the sensor network how to work in an energy-efficient way. In this paper, our work sets out to study a reinforcement learning (RL) based computing offloading policy in the mobile edge computing (MEC) assisted power sensor network. By jointly optimizing task scheduling and resource allocation, we propose a new scheme to optimize data latency and energy efficiency. The optimization problem is modeled as a Markov decision process (MDP), and Dueling Double Deep Q Network (D3QN) algorithm is employed to solve this MDP problem. Simulation results demonstrate the effectiveness of the proposed algorithm and its outperformance in reduction of data latency and energy consumption as well as convergence and stability, compared with other benchmarks. © 2023 ieee.

关键词： Markov processes

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mpiQulacs: A Scalable distributed Quantum Computer Simulator for ARM-based Clusters 4

mpiQulacs: A Scalable Distributed Quantum Computer Simulator...

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

作者： Tabuchi, Akihiro Imamura, Satoshi Yamazaki, Masafumi Honda, Takumi Kasagi, Akihiko Nakao, Hiroshi Fukumoto, Naoto Nakashima, Kohta Computing Laboratory Fujitsu Limited Kawasaki Japan

ISBN: (纸本)9798350343236

Quantum computer simulators running on classical computers are essential for developing real quantum computers and emerging quantum applications. In particular, state vector simulators, which store a full state vector in memory and update it in every quantum operation, can be used to simulate an arbitrary form of quantum circuits, debug quantum applications, and validate future quantum computers. Since the time and space complexity grows exponentially with the number of qubits and easily exceeds the capability of a single machine, various distributed state vector simulators are developed. However, these are tuned for common CPUs and GPUs, not for ARM CPUs. Therefore, we develop a distributed state vector simulator, mpiQulacs, that is optimized for large-scale simulation on A64FX-based cluster systems. A64FX is a 48-core ARM-based CPU having high-bandwidth memory (HBM2) and also used in one of the world's top supercomputers, Fugaku. As computational optimization, we vectorize qubit operations with Scalable Vector Extension (SVE) to fully utilize its HBM2. To reduce the amount of inter-node communication for scalable simulation, mpiQulacs provides a fused-swap gate that collectively performs multiple swap operations as one operation and a quantum circuit optimizer that automatically adds fused-swap gates to a circuit. We evaluate weak and strong scaling of mpiQulacs with up to 39 qubits on our 512-node A64FX-based cluster system. The result shows that mpiQulacs achieves high-scalability on hundreds of nodes in benchmark and practical quantum circuits, and its performance is comparable with the existing well-known distributed state vector simulators. © 2023 ieee.

关键词： Benchmarking

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Development of Verification Model for Intelligence of Multiagent systems 12

Development of Verification Model for Intelligence of Multia...

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12th ieee international conference on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications, IDAACS 2023

作者： Martynyuk, Oleksandr Drozd, Oleksandr Sachenko, Anatoliy Martynyuk, Dmitry Mileiko, Igor Kopytchuk, Igor Hladiy, Grygoriy National University 'Odesskaya Polytechnica' Odessa650044 Ukraine West Ukrainian National University Ternopil46009 Ukraine Kazimierz Pulaski University of Technology and Humanities Radom26-600 Poland Join Venture 'Nippon Auto' Odessa65000 Ukraine

ISBN: (纸本)9798350358056

The development of distributed information systems essentially relies on the complex application of Web services technologies, cloud, 'green', GRID, multi-agent and many others. In many of these technologies, intellectualization is increasingly manifested, which is clearly inherent, for example, in semantic and intelligent Web services, multi-agent systems. Intelligence, often defined as a set of properties of knowledge and mechanisms for their formation, requires its own ways of formalization and implementation, which is also reflected in the problems of analysis and synthesis of intelligent systems, including the problems of their identification and verification. This paper consider the fuzzy and component development of a model for verifying the intelligence of multi-agent systems based on the previously proposed model for verifying the intelligence of multi-agent systems, which, in turn, is based on behavioral experiments for extended Petri nets. The features of the proposed model for verifying intelligence are the presentation of fuzzy production models of all components of intelligence for parallel, associative-evolutionary search for known identifying primitives and recognition of fragments of system behavior based on them, the construction of new identifying primitives as part of a three-level model of new knowledge, as well as a fuzzy inference mechanism, as the basis for obtaining new knowledge, and for identifying and verifying the behavioral properties of the system. The intelligence verification model makes it possible to reduce the computational complexity of the behavioral verification of multi-agent systems and increase its flexibility. © 2023 ieee.

关键词： associative-evolutionary search behavior identifying behavior verification distributed information system intelligence verification model multiagent system

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A Graph-based Approach to Human Activity Recognition 6

A Graph-based Approach to Human Activity Recognition

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6th international conference on Cognitive Machine Intelligence

作者： Peroutka, Thomas Murturi, Ilir Donta, Praveen Kumar Dustdar, Schahram TU Wien Distributed Syst Grp A-1040 Vienna Austria Stockholm Univ Dept Comp & Syst Sci S-16425 Stockholm Sweden

ISBN: (纸本)9798350386738;9798350386721

Advanced wearable sensor devices have enabled the recording of vast amounts of movement data from individuals regarding their physical activities. This data offers valuable insights that enhance our understanding of how physical activities contribute to improved physical health and overall quality of life. Consequently, there is a growing need for efficient methods to extract significant insights from these rapidly expanding real-time datasets. This paper presents a methodology to efficiently extract substantial insights from these expanding datasets, focusing on professional sports but applicable to various human activities. By utilizing data from Inertial Measurement Units (IMU) and Global Navigation Satellite systems (GNSS) receivers, athletic performance can be analyzed using directed graphs to encode knowledge of complex movements. Our approach is demonstrated on biathlon data and detects specific points of interest and complex movement sequences, facilitating the comparison and analysis of human physical performance.

关键词： Human Activity Recognition IoT GNSS Graphs

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