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

共 30781 条记录，以下是4881-4890 订阅

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Elastic distributed Rendering Service Placement in Capacitated Cloud/Fog Gaming systems 11

Elastic Distributed Rendering Service Placement in Capacitat...

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11th international conference on Information, Intelligence, systems and Applications (IISA)

作者： Tsipis, Athanasios Komianos, Vasileios Oikonomou, Konstantinos Stavrakakis, Ioannis Ionian Univ Dept Informat Corfu Greece Ionian Univ Dept Audio & Visual Arts Corfu Greece Natl & Kapodistrian Univ Athens Dept Informat & Telecommmun Athens Greece

ISBN: (纸本)9780738123462

Fog-assisted cloud computing advances have paved the way for new solutions in online gaming, by integrating all rendering resources directly into the edges of the cloud. However, despite the numerous benefits, these systems still remain prone to network delays, ergo, the discovery of an optimal rendering service placement in the fog layer, that effectively reduces capital deployment cost for the game providers and access latency cost for the game clients, is a challenging issue. In fact, it falls into the category of the well-known (NP-hard) facility location problems. As such, conventional centralized approaches, that require global network knowledge, in most cases are deemed unscalable and cost-prohibitive, thus, distributed solutions must be further explored. The approach followed here, introduces a Rendering Service Allocation Policy (RSAP) to autonomously allocate services towards an optimal placement, based strictly on local information available to the fog renderers regarding their aggregate rendering demands, yielding reduced access latency and deployment costs, whilst meeting their stringent capacity bounds. Simulation results showcase the efficiency of RSAP and verify its elastic behavior under different deployment scenarios.

关键词： Cloud/Fog Gaming Capacitated Facility Location Problems Rendering Service Placement Resource Allocation Cost Reduction

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Bundle Charging: Wireless Charging Energy Minimization in Dense Wireless sensor Networks 39

Bundle Charging: Wireless Charging Energy Minimization in De...

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39th ieee international conference on distributed computing systems (ICDCS)

作者： Wang, Ning Wu, Jie Dai, Haipeng Rowan Univ Dept Comp Sci Glassboro NJ 08028 USA Temple Univ Ctr Networked Comp Philadelphia PA 19122 USA Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China

ISBN: (纸本)9781728125190

Using a mobile charger to wirelessly charge sensors is a promising yet not well-solved technique. Existing trajectory planning schemes for wireless charger either (1) fail to optimize the one-to-many characteristic of wireless charging or (2) fail to jointly optimize the charger movement cost and the charging cost. The objective of this paper is to find the optimal trajectory planning for a mobile charger in terms of energy minimization in the quadratic attenuation charging model. There exists a trade-off between charging efficiency and trajectory distance. If the mobile charger comes close to sensors, the charging efficiency is high, but the entire charging trajectory of the charger will be long and vice versa. To address this trade-off, we propose the idea of charging bundle and optimize the charger's trajectory based on the charging bundle rather than each sensor. The optimal charging bundle generation problem and the bundle trajectory optimization problem are discussed gradually. Both of them are proven to be NP-hard. Then, we first propose a greedy bundle generation algorithm with an approximation ratio of In n, where n is the number of sensors. After that, we propose a TSP-based solution and further optimize the TSP-trajectory by jointly considering the adjacent charging locations. Theorems are proposed to effectively find the optimal location. Extensive experiments show that our scheme achieves a much better performance than traditional schemes.

关键词： wireless energy transfer wireless sensor networks trajectory planning mobile charging

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3DP Check: A Deep Learning-Based Diagnostic Tool for Fault Monitoring in Additive Manufacturing

3DP Check: A Deep Learning-Based Diagnostic Tool for Fault M...

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international conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Gabriel Avelino Sampedro Made Adi Paramartha Putra Mideth B. Abisado Dong-Seong Kim Jae-Min Lee Department of IT Convergence Engineering Kumoh National Institute of Technology Gumi South Korea Faculty of Information and Communication Studies University of the Philippines–Open University Los Baños Philippines Informatic Enginering STMIK Primakara Denpasar Indonesia College of Computing and Information Technologies National University Manila Philippines

An agile approach to the design and development of hardware has been made possible by fast prototyping using additive manufacturing (AM). Although the procedure is short, a disadvantage would be any potential mistakes or problems that would be hard to spot. Failures that go unnoticed might harm the AM device and result in wasted output, costing more time and money. The goal of the research is to create a system that tracks 3D printing activities and forecasts printer temperature readings in the future. This article describes the creation of 3DP Check, a diagnostic tool for additive manufacturing that uses deep learning to look for errors. The system will employ a web application built on the Internet of Things (IoT) to gather real-time data from several sensors linked to an AM device. Forecasting metrics, including the root mean square error (RMSE), mean average error (MAE), symmetric mean absolute percentage error (sMAPE), and r-square (R 2 ) values, will be analyzed when the model is put to the test. With an RSME of 0.4391, MAE of 0.2834, sMAPE of 0.1416, and R 2 of 0.6922, LSTM is shown to perform best after a thorough comparative examination.

关键词： Deep learning Temperature sensors Three-dimensional displays Three-dimensional printing sensor systems and applications Real-time systems Printers

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Design and Implementation of RAP - A Randomized Asynchronous Protocol for Data Aggregation in Wireless sensor Networks

Design and Implementation of RAP - A Randomized Asynchronous...

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2020 international conference on computing, Networking and Communications, ICNC 2020

作者： Dai, Jiahui Degtyarev, Dmitry Gao, Jingya Wang, Adrian Burman, Scott Zillig, Ken Ghosal, Dipak University of California Department of Computer Science Davis United States University of California Department of Land Air and Water Resources Davis United States Department of Wildlife Fish and Conservation Biology University of California Davis United States

ISBN: (纸本)9781728149059

We consider a distributed deployment of sensors and a network of wireless relay nodes designed to operate in an environment in which there exists neither a stable energy source nor a global clock to which the network (sensor, relay, and gateway) nodes can synchronize. For such an environment, we design and implement a randomized asynchronous protocol (RAP) for aggregating data at the gateway. The protocol is based on the randomized sleeping of nodes in an asynchronous manner, taking advantage of the birthday paradox to ensure eventual communication. We present an approximate mathematical analysis and develop a simulation model to study the performance of the protocol under different sleep parameters: specifically, the duration of the random sleep times of the transmitter and the receiver. We show that a low average data transfer time can be achieved with low energy usage. We implemented the protocol on an Adafruit Feather 32u4 board, including a number of optimization to further improve the performance and minimize energy usage. Finally, we deployed a wireless sensor network for distributed temperature monitoring of aquaculture research at the Center of Aquatic Biology and Aquaculture (CABA) of University of California, Davis. © 2020 ieee.

关键词： Data transfer

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sensor Virtualization for Enabling Novel Services 10

Sensor Virtualization for Enabling Novel Services

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10th ieee international conference on Intelligent Data Acquisition and Advanced computing systems - Technology and Applications (IDAACS)

作者： Chenaru, Oana Hanganu, Cristina Elena Popescu, Dan Ichim, Loretta Univ POLITECH Bucharest 313 Splaiul Independentei Bucharest Romania

ISBN: (纸本)9781728140681

The paper presents a model for the virtualization of a wireless sensor network in a smart home application for energy consumption monitoring. By correlating physical sensor data with information on home's design, sunrise and sunset time according to day of year, time of day and weather data, novel services for consumed power statistics and efficiency of use of natural light were developed in the virtualized environment. Based on this model, distributed applications were developed to implement analysis of energy consumption over large scale areas. We detail the solution implementation based on the OpenSHS simulator and NodeRed.

关键词： distributed applications energy consumption monitoring smart home application sensor virtualization

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Information Fusion and Decision Support for Autonomous systems

Information Fusion and Decision Support for Autonomous Syste...

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2021 ieee international conference on Autonomous systems (ICAS)

作者： Henry Leung University of Calgary 2500 University Drive NW Calgary AB Canada

ISBN: (纸本)9781728172903

In this talk we present our works on decision support analytic for autonomous systems. Decision support analytic process multiple sensory information collected by an autonomous system such as lidar, camera, RGBD, acoustic to perform signal detection, target tracking, object recognition. As multiple sensors are involved, our system uses sensor registration, data association and fusion to combine sensory information. The next layer of the proposed decision support system orients the processed sensory information at feature and classification levels to perform situation assessment and treat evaluation. Based on the assessment, the decision support system will recommend decision. If the uncertainty is high, actions including resource allocation, planning will be used to extract or reassess the sensory information to get a recommended decision with lower uncertainty. This talk will also presents the applications of the proposed decision support analytic in four industrial projects including 1) goal-driven net-enabled distributed sensing for maritime surveillance, 2) autonomous navigation and perception of humanoid service robots, 3) distance learning for oil and gas drilling and 4) cognitive vehicles.

关键词： Decision support systems Uncertainty Target tracking Service robots Surveillance sensor fusion Robot sensing systems

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Design of distributed Plant Temperature and Humidity Monitoring System

Design of Distributed Plant Temperature and Humidity Monitor...

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2020 ieee international conference on Power, Intelligent computing and systems, ICPICS 2020

作者： Ying, Jingda Zhang, Xiaomin Pan, Yibin Liu, Li Ci, Yanke Peng, Xushan Li, Yongping Chen, Haosong Dahongying University Department of Information Engineering Xueyuan Road 899# Ningbo Zhejiang Province315175 China

ISBN: (纸本)9781728198736

In recent years, the technology of industrial and agricultural generation driven by information technology is developing vigorously. The design and research of distributed temperature and humidity monitoring system is immeasurable for the impact and promotion of tertiary industry, agriculture and industry. It is the general trend of modern prosperity and future development. It is self-evident that it is of great significance to occupy the supreme prestige and level of international advanced science and technology strategy, especially for the development of economy and the improvement of industrial automation. © 2020 ieee.

关键词： Agriculture

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Poster abstract: Federated learning for speech emotion recognition applications 19

Poster abstract: Federated learning for speech emotion recog...

引用

19th ACM/ieee international conference on Information Processing in sensor Networks, IPSN 2020

作者： Latif, Siddique Khalifa, Sara Rana, Rajib Jurdak, Raja Australia CSIRO Distributed Sensing Systems Group Data61 Australia

ISBN: (数字)9781728154978

ISBN: (纸本)9781728154978

Privacy concerns are considered one of the major challenges in the applications of speech emotion recognition (SER) as it involves the complete sharing of speech data, which can bring threatening consequences to people's lives. Federated learning is an effective technique to avoid privacy infringement by involving multiple participants to collaboratively learn a shared model without revealing their local data. In this work, we evaluated federated learning for SER using a publicly available dataset. Our preliminary results show that speech emotion recognition can benefit from federated learning by not exporting sensitive user data to central servers, while achieving promising results compared to the state-of-the-art. © 2020 ieee.

关键词： Deep neural networks

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Communication Architecture of Solar Energy Monitoring systems for Telecommunication Objects

Communication Architecture of Solar Energy Monitoring System...

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international conference on Information Science and Communications Technologies (ICISCT)

作者： Ilkhom Siddikov Doston Khasanov Halim Khujamatov Ernazar Reypnazarov Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781665432597

The sources of energy supply for telecommunication stations are territorially distributed facilities with a multi-level management hierarchy and a large number of structural units. Monitoring them is one of the pressing issues, the main challenge of which is to develop an effective communication architecture for the monitoring system. This article analyzes the communication architecture of solar power supply monitoring, based on the analysis, a new architecture is developed that differs from the communication architecture of other monitoring systems. In this communication architecture, wireless sensor networks, which are considered cost-effective and practical in the application of solar power supply sources for remote monitoring systems, are analyzed. One of the leading directions in this field as a basic wireless sensor technology for monitoring system communication architecture is the development of recommendations for the use of ZigBee technology based on the ieee 802.15.4 standard.

关键词： ieee 802.15 Standard Wireless sensor networks Wireless networks Standards organizations Zigbee Solar energy Communications technology

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A Multi-agent Reinforcement Learning Risk Management Model for distributed Agile Software Projects

A Multi-agent Reinforcement Learning Risk Management Model f...

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ieee international conference on Intelligent computing and Information systems (ICICIS)

作者： Rehab Adel Hany Harb Ayman Elshenawy Faculty of Engineering Al-Azhar University Cairo Egypt Faculty of Engineering and Technology Egyptian Chinese University Cairo Egypt

ISBN: (纸本)9781665411592

Nowadays, due to the benefits of the agile method, such as changing rapidly and fast delivery of working software, most software projects are naturally distributed agile projects (DAD). DAD team members work from various remote sites. This leads to the emergence of many significant challenges in risk management. Hence, it requires risk safety techniques to be implemented to mitigate the occurrence of risks. There is no standardized process for teams to deal with DAD risks. In this paper, a multi-agent reinforcement learning risk management model for distributed agile software projects is proposed. The proposed model is implemented to apply a dynamic policy. The model is applied as an experiment to definite numbers for a set of risk factors such as communication and coordination risk, project management risk, and SDLC risk. The proposed model is developed using multiple individual learning using the Q- learning algorithm. A DAD project with two projects is used to evaluate the proposed model. The proposed model was assessed and analyzed for its effectiveness. The results of the evaluation are given.

关键词： Analytical models Computational modeling Heuristic algorithms Software algorithms Project management Reinforcement learning Software

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