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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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A middle-ware approach to leverage the distributed data deduplication capability on HPC and Cloud storage systems 8

A middle-ware approach to leverage the distributed data dedu...

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8th ieee international conference on Big Data (Big Data)

作者： Chen, Hsing-bung Tang, Sihai Fu, Song Los Alamos Natl Lab HPC Design Grp Los Alamos NM 87545 USA Univ North Texas CSE Dept Denton TX 76203 USA

ISBN: (纸本)9781728162515

The unprecedented growth in the volume and diversity of the data in today's HPC and Enterprise computing environment has posted challenging problems on data management and data space reduction. More than 71% of enterprise and HPC communities are seeking de-duplication technologies to reduce cost and increase the storage efficiency. The importance of applying data de-duplication techniques is critical for active research and development. Current implementations of data de-duplication systems are mainly hardware dependent, system dependent, and platform dependent. Also, most of these implementations are proprietary software and not in open source domains. In this paper, we present a new middle-ware design and implementation approach, named D3M, to support distributed data de-duplication feature on existing file and object storage systems. We also incorporate this proposed D3M middle-ware with the Redhat's Linux device layer de-duplication and compression driver, called VDO (Virtual Data Optimizer). With these two layers of data de-duplication support, we accommodate both client side and server-side data de-duplication features. Finally, we conduct various testing cases on HPC data sets and Enterprise data sets to illustrate the benefits and advantages of applying our bilayer data de-duplication middle-ware solution.

关键词： De-duplication Storage HPC Middle-ware Data Chunking Performance evaluation

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Posture Tracking Meets Fitness Coaching: A Two-Phase Optimization Approach with Wearable Devices 17

Posture Tracking Meets Fitness Coaching: A Two-Phase Optimiz...

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17th ieee international conference on Mobile Ad Hoc and Smart systems (ieee MASS)

作者： Zhou, Han Gao, Yi Liu, Wenxin Jiang, Yuefang Dong, Wei Zhejiang Univ Hangzhou Zhejiang Peoples R China Alibaba Zhejiang Univ Joint Inst Frontier Technol Hangzhou Peoples R China Soyea Technol Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781728198668

Fitness training is becoming an increasingly popular way of maintaining overall health and preventing illness. However, in some cases the training could be risky and fitness-related injuries have increased by 48% in the USA. The training itself will not cause hurt, but if it is performed in a crucial-improper form (using the wrong technique), it will injure the exerciser. Research has explored the potential of using wearables to monitor fitness training, but the consideration of proper/improper form is not included. In this paper, we propose WearCoach, a wearable-based fitness training assistant, which acquires the user's fitness form information and generates real-time feedback during training. WearCoach differs from previous work of training assistant in 1) it employs a two-phase tracking algorithm to achieve accurate and real-time tracking of body motion, 2) it analyzes the captured arm posture and generates training guidance based on the user's form, 3) it uses joint orientation as an exercise classification feature to improve recognition accuracy. We conducted experiments with eight participants and nine exercises. Three kinds of feedback are generated, including injury alert, movement correction and symmetry analysis.

关键词： Fitness Training Assistant Motion Tracking Multi sensor Fusion Wearable computing

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Fuzzy-as-a-Service for Real-Time Human Activity Recognition Using ieee 1855-2016 Standard

Fuzzy-as-a-Service for Real-Time Human Activity Recognition ...

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ieee international conference on Fuzzy systems (FUZZ-ieee)

作者： Pandya, Bhavesh Pourabdollah, Amir Lotfi, Ahmad Nottingham Trent Univ Sch Sci & Technol Nottingham England

ISBN: (纸本)9781728169323

Fuzzy Logic systems (FLSs) have shown their potentials in Ambient Intelligence (AmI) applications. However, the implementation of FLSs is typically linked to dedicated and non-scalable hardware/software systems. As a result, some specific AmI requirements such as web communications and Service-Oriented Architecture (SOA), which can be found in many modern systems, are rarely adapted for FLSs. Sharing FLSs accessibility as web services (called fuzzy-as-a-service), in which the service is developed independently from a specific FLS, allows for system autonomy, openness, load balancing, efficient resource allocation and eventually cost-efficiency, particularly for computationally intense FLSs. In a wider context, such features can open new dimensions for FLSs' applicability in Cloud computing and Internet of Things devices. Recent advances in standardising Fuzzy Mark-up Language (ieee 1855-2016) and its associated software libraries (such as JFML) has made this even more achievable. This paper proposed fuzzy-as-a-service architecture based on ieee 1855-2016, JFML and SOA. Through a simulated experiment, this paper concerned the collection, processing and monitoring the distributed data over the web, thus a real-time human activity recognition simulated scenario using a rule based FLS is demonstrated.

关键词： fuzzy-as-a-service ambient intelligence human activity recognision service-oriented architecture internet of things IoT fuzzy markup language FML

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Secure and Energy-Efficient Remote Monitoring Technique (SERMT) for Smart Grid 5th

Secure and Energy-Efficient Remote Monitoring Technique (SER...

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5th international conference on ICT for Sustainable Development, ICT4SD 2020

作者： Roy, Sohini Sen, Arunabha Arizona State University TempeAZ85281 United States

ISBN: (纸本)9789811582882

Monitoring and automation of the critical infrastructures like the power grid are improvised by the support of an efficient and secure communication network. Due to the low-cost, low-power profile, dynamic nature, improved accuracy and scalability, wireless sensor networks (WSN) became an attractive choice for the Information and Communication Technology (ICT) system of the smart grid. However, the energy efficiency and security of WSN depend highly on the network design and routing scheme. In this paper, a WSN-based secure and energy-efficient remote monitoring technique (SERMT) is proposed by demonstrating a WSN-based ICT network model for pervasive monitoring of the generation and transmission part of the power network in a smart grid system. The performance of the proposed network model designed for a smart grid of ieee 118-Bus system coupled with the secure routing technique is tested during cyber-attacks by means of NS2, and the simulation results indicate that it performs better than existing smart grid monitoring methods like Lo-ADI (Dhunna and Al-Anbagi in ieee Sens J 19(13), 2019 [1]) with respect to packet drop count and throughput. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： sensor nodes

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Design and Development of Wireless sensor for Variable Temperature and for Various Security Purposes 4th

Design and Development of Wireless Sensor for Variable Tempe...

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4th international conference on Information and Communication Technology for Intelligent systems, ICTIS 2020

作者： Singh, Prabhakar Saxena, Minal SIRT Bhopal India

ISBN: (纸本)9789811570773

The word sensor simply illustrates the conversion of non-electrical signal, physical or chemical quantity into an electrical signal and the measuring quantity by it is called the measurand. There are many autonomous devices using sensors with cluster of networks and spatially distributed network to provide more facility (Rowayda and Sadek in Future Comput. Inf. J. 3(2):166–177, 2018) (Bosman et al. in Inf. Fusion 33:41–56, 2017) [1, 2]. A routine protocol in WSN is enhanced to hierarchical-based routine protocol because of its energy-saving capability, network scalability, and network topology stabilities (Zhang et al. in J. Softw. Eng. Appl. 03(12):1167–1171, 2010) [3]. This sensor will not pose high SNR as compared to Arduino/DS18B20 temperature sensors and because the use of an optimal dynamic stochastic resonance (SR) processing method is introduced to improve the SNR of the receiving signal under certain conditions, which is not been done in others. SNR = (10 log s/n) in db, where σ =1 or 0.1 or 0.01 depending on various circumstances which is quiet low as compared to other sensor noise ratios. As per result, perspective pulling sensor data from the sensor approximately every 4 s got a lot of errors throughout the day (Cheng and Chang in Expert Syst. Appl. 39(10):9427–9434, 2012) [4]. WSN is emerging as a popular and essential ways of providing pervasive computing environment for numerous applications. There are periods of times where it can go several minutes before getting an error-free value. Similarly, it can also go several hours and not have any errors, so it is very intermittent. The errors range from "no sensors found" to CRC errors. These problems will be removed in this sensor because use of DSR and percentage of error will fall to ~0.001–1% only depending on variable weather, location, and environment. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Topology

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Internet of Toys for Measuring Drawing Skills and Supporting Childcare

Internet of Toys for Measuring Drawing Skills and Supporting...

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Big Data, Cloud computing, Data Science & Engineering (BCD)

作者： Keiko Yamamoto Taichi Fujihara Ichi Kanaya dept. of Design Engieering and Techonolgy Tokyo Denki University Tokyo Japan Graduate Shool of Science and Techonology Kyoto Institute of Technology Kyoto Japan School of Information and Data Sciences Nagasaki University Nagasaki Japan

ISBN: (数字)9798350394191

ISBN: (纸本)9798350394207

During childhood, play is important for promoting the mental and physical development of children. For this reason, those involved with childcare (guardians and childcare workers) need to create an environment suitable for child development and provide children with support and guidance. However, because there are unique elements to the development of each individual child, childcare workers caring for large numbers of children, and guardians in remote areas, may struggle to oversee the daily development of the children in their care. Particularly in Japan, the lack of vacancy at nursery schools and the number of nursery school teachers is regarded as a problem in spite of declining birth rate. Therefore, there is a strong desire to realize a society in which children can be raised safely and securely without burdening parents and childcare workers. To solve this problem, we propose various types of toys with built-in sensors that are used to collect motion data during play activities, and a system intended to help estimate the child's development stage by creating a data visualization for childcare workers. In this paper, we built a pen-holder type device for measuring the development of drawing skills. Using this prototype, as the first step of an evaluation, we conducted an experiment to verify whether it is possible to discern four types of drawings focusing on changes in drawing skills related to child development. The results showed that they could be identified with 75.75% (SVM) and 69.25% (RF) accuracy.

关键词： Support vector machines Radio frequency Accuracy Toy manufacturing industry Data visualization Prototypes Focusing sensor systems sensors Object recognition

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Job Placement Strategy with Opportunistic Resource Sharing for distributed Deep Learning Clusters 22

Job Placement Strategy with Opportunistic Resource Sharing f...

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22nd ieee international conference on High Performance computing and Communications, 18th ieee international conference on Smart City and 6th ieee international conference on Data Science and systems, HPCC-SmartCity-DSS 2020

作者： Li, Hongliang Sun, Ting Li, Xiang Xu, Haixiao Jilin University College of Computer Science and Technology Changchun China

ISBN: (纸本)9781728176499

distributed deep learning frameworks train large deep leaning workload with multiple training jobs on shared distributed GPU servers. There are new challenges when scheduling resources for these systems. Modern deep learning training jobs tend to consume large amount of GPU memory. A training job has an iterative nature that causes the memory usage fluctuate overtime. Jobs sharing a host may suffer from significant performance degradation caused by memory overload in runtime. Moreover, even without memory overloads, deep learning training jobs still experience different levels of performance interference when sharing a GPU device. This paper studies these two issues. We introduced an opportunistic memory sharing model to allocate resources for training jobs with time-varying memory requirements. Based on this model, we introduced an opportunistic Job Placement Problem (OJPP) for shared GPU clusters that seeks job placement configurations using minimum number of GPU devices and guarantees user-defined performance requirements. We proposed a greedy algorithm and a heuristic algorithm with computational complexities of O(n\log n) and O(n^systems\log n), respectively, to solve the problem. Extensive experiments are conducted using a GPU cluster to verify the correctness, effectiveness, and the scalability of our approaches. The proposed approach achieved over 80% percent of the standalone performance, in term of average job completion time, with less than 30% extra resources consumption. © 2020 ieee.

关键词： Graphics processing unit

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Towards Efficient and Adaptive Cyber Physical Spiking Neural Integrated systems 27

Towards Efficient and Adaptive Cyber Physical Spiking Neural...

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27th ieee international conference on Electronics, Circuits and systems (ieee ICECS)

作者： Madrenas, Jordi Zapata, Mireya Fernandez, Daniel Maria Sanchez-Chiva, Josep Valle, Juan Mata-Hernandez, Diana Angel Oltra, Josep Cosp-Vilella, Jordi Sato, Shigeo Univ Politecn Cataluna Dept Elect Engn Barcelona Catalunya Spain Univ Tecnol Indoamer Res Ctr Mechatron & Interact Syst Quito Ecuador IFAE BIST Inst Fis Altes Energies Bellaterra Catalunya Spain Tohoku Univ Res Inst Elect Commun Sendai Miyagi Japan

ISBN: (纸本)9781728160443

This work introduces multi-sensor integration combined with an efficient and adaptive Spiking Neural Network (SNN) emulation architecture for local intelligent processing. For this purpose, we propose CMOS-MEMS with on-chip conditioning electronics together with spike processing by means of a real-time bioinspired and model-programmable SIMD multiprocessor. System integration considerations and results in the MEMS and processor developments are provided.

关键词： sensor Neural computing Integration Integrated sensors MEMS CMOS-MEMS Spiking Neural Networks SNN Cyber Physical Neural systems

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Model Checking as a Service using Dynamic Resource Scaling 27

Model Checking as a Service using Dynamic Resource Scaling

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27th ieee international conference on High Performance computing, Data, and Analytics (HiPC)

作者： Palavalasa, Surya Teja Singh, Yuvraj Singla, Adhish Purini, Suresh Choppella, Venkatesh Int Inst Informat Technol Hyderabad India

ISBN: (纸本)9781665422925

Model checking is now a standard technology for verifying large and complex systems. While there are a range of tools and techniques to verify various properties of a system under consideration, in this work, we restrict our attention to safety checking procedures using explicit state space generation. The necessary hardware resources required in this approach depends on the model complexity and the resulting state transition graph that gets generated. This cannot be estimated apriori. For reasonably realistic models, the available main memory in even high end servers may not be sufficient. Hence, we have to use distributed safety verification approaches on a cluster of nodes. However, the problem of estimating the minimum number of nodes in the cluster for the verification procedure to complete successfully remains unsolved. In this paper, we propose a dynamically scalable model checker using an actor based architecture. Using the proposed approach, an end user can invoke a model checker hosted on a cloud platform in a push button fashion. Our safety verification procedures automatically expands the cluster by requesting more virtual machines from the cloud provider. Finally, the user gets to pay only for the hardware resources he rented for the duration of the verification procedure. We refer to this as Model Checking as Service. We approach this problem by proposing an asynchronous algorithm for safety checking in actor framework. The actor based approach allows for scaling the resources on a need basis and redistributes the work load transparently through state migration. We tested our approach by developing a distributed version of SpinJA model checker using Akka actor framework. We conducted our experiments on Google Cloud Engine (GCE) platform wherein we scale our resources automatically using the GCE API. On large models such as anderson.8 from BEEM benchmark suite, our approach reduced the model checking cost in dollars by 8.6x while reducing the wall clock

关键词： Model Checking Cloud Native Horizontal Scaling Actor model distributed Asynchronous computing

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Integrating Wireless sensor Networks with Cloud computing, a Survey

Integrating Wireless Sensor Networks with Cloud Computing, a...

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2020 international conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020

作者： Ali, Afrah Al-Omary, Alauddin University of Bahrain College of It Sakhir Bahrain

ISBN: (纸本)9781728196756

The necessity of wireless sensor networks comes with the wide ranges of important applications that collect and process information from the physical world. In a similar way, cloud computing is needed in the distributed resource sharing. Integrating wireless sensor networks with cloud computing, which enables the sharing of the sensor resources, brings a new technology called sensor-Cloud. Combining the data of sensor applications with web-based virtual communities is very beneficial in various important domains such as health and environment. The sensor data needs more capability for the analysis. Cloud computing can be combined with the wireless sensor network in many applications. Using cloud computing to form wireless sensor networks of several application as one virtual sensor network is a new trend in computing. This makes it easier to share and analyze real time sensor data. However, sensor-Cloud needs to be energy-efficient, because the sensor battery life is limited. In this paper, we provided a survey on sensor-Cloud. The major issues and challenges when designing sensor-Cloud infrastructure have been addressed. In addition, an analysis of various energy-efficient scheduling approaches has been provided. © 2020 ieee.

关键词： Cloud computing

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