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2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN)最新文献

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Proactive Content Caching at Self-Driving Car Using Federated Learning with Edge Cloud 使用边缘云联合学习的自动驾驶汽车的主动内容缓存
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528638
Subina Khanal, K. Thar, M. Hossain, E. Huh
Proactive content caching in self-driving cars poses several challenges, particularly because of the dynamic nature of content popularity, heterogeneity in user preferences, and privacy issues for data sharing. To tackle these issues, in this paper, we study the significance of proactive content caching strategy in self-driving cars for optimizing content retrieval cost and quality-of-experience (QoE) with the edge cloud infrastructure. To that end, we propose a low-complexity content popularity prediction mechanism in a federated setting where we extract local content popularity patterns in the self-driving cars using long short-term memory (LSTM)-based prediction mechanism. Then, we leverage the privacy-preserving distributed model training paradigm of Federated Learning (FL) to create a global model by applying the Federated Averaging (FedAvg) algorithm on local LSTM models to create a regional content popularity prediction model. With extensive simulations on real-world datasets, we show the obtained global model helps to improve the local cache hit ratio, cache space utilization, and correspondingly minimize latency overhead at the self-driving cars.
自动驾驶汽车的主动内容缓存带来了一些挑战,特别是因为内容受欢迎程度的动态性、用户偏好的异质性以及数据共享的隐私问题。为了解决这些问题,本文研究了主动内容缓存策略在自动驾驶汽车中利用边缘云基础设施优化内容检索成本和体验质量(QoE)的意义。为此,我们提出了一种在联邦环境下的低复杂度内容流行度预测机制,我们使用基于长短期记忆(LSTM)的预测机制提取自动驾驶汽车中的本地内容流行度模式。然后,我们利用联邦学习(FL)的隐私保护分布式模型训练范式,通过在局部LSTM模型上应用联邦平均(FedAvg)算法创建区域内容流行度预测模型来创建全局模型。通过对真实世界数据集的广泛模拟,我们证明了获得的全局模型有助于提高本地缓存命中率,缓存空间利用率,并相应地最小化自动驾驶汽车的延迟开销。
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引用次数: 2
A High Accuracy Low Power Convolution Operator with 12T SRAM for CNN 基于12T SRAM的CNN高精度低功耗卷积算子
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528655
Tae Seob Oh, Younggun Pu, Kangyoon Lee
To get high accuracy, various weight should be stored in memory. For this, this paper presents tri-state weight static random access memory(SRAM). 12T SRAM is a form of power gating on the conventional 10T SRAM. By using power gating, the inverter can be turned off. The new weight (0) can be stored in 12T SRAM when inverter is turned off. The operator fabricated in a 0.18-µm CMOS process dissipates 172.3µW with the supply of 1.8V while convolution. Even without sizing, the writing margin is better than the conventional SRAM and the accuracy is improved by 23.2%.
为了获得较高的精度,需要将各种权重存储在内存中。为此,本文提出了三态权重静态随机存取存储器(SRAM)。12T SRAM是传统10T SRAM上的一种功率门控形式。通过使用功率门控,可以关闭逆变器。当逆变器关闭时,新的权重(0)可以存储在12T SRAM中。在0.18µm CMOS工艺中制造的算子在卷积时功耗为172.3µW,电源为1.8V。即使没有调整大小,写入余量也比传统的SRAM好,精度提高了23.2%。
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引用次数: 1
Schema Ontology Model to Support Semantic Interoperability in Healthcare Applications: Use Case of Depressive Disorder 支持医疗保健应用中语义互操作性的模式本体模型:抑郁症用例
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528708
I. Chong, Sajjad Ali
The provision of semantic interoperability among heterogeneous data is important issue to cope with a tremendous potential of diverse healthcare applications. This paper describes schema ontology models to support semantic interoperability in healthcare applications of depressive disorder (DD) using the framework of Web of Objects (WoO). And the implementation aspects of semantics interoperability with required schema ontology models and their integrated associations are defined to characterize the target interoperable ontology of affective DD states.
在异构数据之间提供语义互操作性是应对各种医疗保健应用程序巨大潜力的重要问题。本文利用对象Web (Web of Objects, WoO)框架,描述了支持抑郁症(DD)医疗保健应用中语义互操作性的模式本体模型。定义了语义互操作与所需模式本体模型的实现方面及其集成关联,以表征情感DD状态的目标互操作本体。
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引用次数: 0
Channel Capacity for a Model of Packet Level Index Modulation in LPWA Networks 低功耗广域网中分组级索引调制模型的信道容量
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528540
Riku Yamabe, M. Nishiara, O. Takyu
Packet level index modulation is a modulation scheme that can expand the transmission capacity without changing the existing LPWA (Low Power Wide Area) communication standard. In this paper, we calculate the theoretical capacity of the channel. In this modulation scheme, time is treated as a unit of slots and there are multiple channels that can transmit packets. To comply with the 10 % duty cycle of LPWA specification, we assume that only 1 packet is transmitted per 10 slot. In general, it is possible to transmit $N$ packets in 10N slots. We calculate the capacity of the channel for this model.
分组级索引调制是一种在不改变现有低功率广域(LPWA)通信标准的情况下扩大传输容量的调制方案。在本文中,我们计算了信道的理论容量。在这种调制方案中,时间被视为一个时隙单位,并且有多个信道可以传输数据包。为了符合LPWA规范的10%占空比,我们假设每10个时隙只传输1个数据包。一般来说,在10N个插槽中传输$N$数据包是可能的。我们计算了这个模型的信道容量。
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引用次数: 1
Measurement of Colored Noise from Spot-Welding Machine in a Factory 某工厂点焊机有色噪声的测量
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528742
J. Park, Wanjei Cho, Kyoung-Min Park, Seong-Hwan Hyun, Seong-Cheol Kim, DongEun Kim, Hyung Jun Park
A smart factory environment is becoming increasingly important as the 4th industrial revolution has garnered increasing attention. Formulating a complete wireless condition is the most important aspect of a smart factory. Therefore, making a factory suitable for wireless communication is essential. However, excessive spot-welding machines in a factory result in colored noises, which may cause severe performance degradation in wireless communication. In this study, we measured and analyzed channel noise from a spot-welding machine in a Hyundai Motors Group factory using a spectrum analyzer.
随着第四次工业革命受到越来越多的关注,智能工厂环境变得越来越重要。制定一个完整的无线条件是智能工厂最重要的方面。因此,使工厂适合无线通信是必不可少的。然而,工厂中过多的点焊机会产生有色噪声,这可能会导致无线通信性能的严重下降。在本研究中,我们使用频谱分析仪测量和分析了现代汽车集团工厂点焊机的通道噪声。
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引用次数: 0
FFT and Machine Learning Application on Major Chord Recognition FFT和机器学习在大调和弦识别中的应用
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528762
Nolan Monnier, Darien Ghali, Sophie X. Liu
The purpose of this project was to use theory of Fast Fourier Transforms and a machine learning algorithm called Treebagger in order to process and recognize musical chords. Four musical chords were selected: C, D, G, and A. To be successful, the program should recognize chords in various octaves and musical inversions. Our goal is to use digital signal processing techniques such as sampling and frequency decomposition to preprocess audio files for input and train into the machine learning algorithms. For our application, we used MATLAB's machine learning tool Treebagger.
这个项目的目的是使用快速傅里叶变换理论和一种叫做Treebagger的机器学习算法来处理和识别和弦。选择了C、D、G、a四个和弦。要想成功,该程序必须能够识别不同八度的和弦和音乐倒位。我们的目标是使用采样和频率分解等数字信号处理技术对音频文件进行预处理,以便输入并训练成机器学习算法。对于我们的应用,我们使用了MATLAB的机器学习工具Treebagger。
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引用次数: 0
ICUFN 2021 Program at a Glance ICUFN 2021计划概览
Pub Date : 2021-08-17 DOI: 10.1109/icufn49451.2021.9528802
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引用次数: 0
Dynamic Priority Scheduling Mechanism Based on Spatio-Temporal Correlation for VANETs 基于时空相关性的vanet动态优先级调度机制
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528829
Shuai Zhang, Jinglei Li, Qinghai Yang, K. Kwak
A dynamic priority scheduling scheme is conceived for the safety messages of vehicular ad-hoc networks (VANETs). The priority of a message is dynamically adjusted for satisfying the specific VANETs safety requirements. A spatio-temporal correlation function based on the message-priority is developed, which monotonically decreases as the transmission range and the transmission duration increasing. Additionally, the spreading of a message is limited to the dynamic life-span and spatial area. Our simulations demonstrate that the proposed scheduling scheme is capable of significantly reducing the network's duplicated teletraffic when the vehicular density is high, whilst improving the achievable transmission range in the low vehicular density.
针对车载自组织网络(VANETs)的安全信息,提出了一种动态优先级调度方案。消息的优先级是动态调整的,以满足特定的VANETs安全要求。建立了基于消息优先级的时空相关函数,该函数随着传输距离和传输时间的增加而单调减小。此外,信息的传播受动态生命周期和空间区域的限制。仿真结果表明,在车辆密度较大的情况下,该调度方案能够显著减少网络的重复通信,同时在车辆密度较低的情况下提高可实现的传输距离。
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引用次数: 0
Storing Blockchain Data in Public Storage 将区块链数据存储在公共存储中
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528568
Khikmatullo Tulkinbekov, Deok‐Hwan Kim
The idea of blockchain has emerged in many applications, including IoT data processing, over the last few years. Because of the guaranteed security, the blockchain is believed to create the backbone of future technologies as a P2P network. However, applying the blockchain protocol in IoT data computing faces a severe challenge related to extensive data management. This paper presents a BlockStore, the method for storing blockchain data in single public storage while maintaining the security features. The BlockStore also resolves the access management and recovery issues among the blockchain nodes. The preliminary experiments prove that the expected research brings a considerable advantage to IoT data management using blockchain.1
在过去的几年里,区块链的概念已经出现在许多应用中,包括物联网数据处理。由于有保证的安全性,区块链被认为是未来P2P网络技术的支柱。然而,区块链协议在物联网数据计算中的应用面临着与广泛的数据管理相关的严峻挑战。本文提出了一种区块链存储方法,该方法将区块链数据存储在单个公共存储中,同时保持安全特性。BlockStore还解决了区块链节点之间的访问管理和恢复问题。初步实验证明,预期的研究为使用区块链进行物联网数据管理带来了相当大的优势
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引用次数: 2
The Impact of Energy-Inefficient Communications on Location Privacy Protection in Monitoring Wireless Networks 低能耗通信对监控无线网络位置隐私保护的影响
Pub Date : 2021-08-17 DOI: 10.1109/ICUFN49451.2021.9528714
L. Mutalemwa, Seokjoo Shin
Wireless sensor networks (WSNs) have gained increasing popularity in ubiquitous support of sensing system services. Often, WSNs are energy-constrained and they are deployed in harsh and unattended environments. Consequently, WSNs are vulnerable to energy and environmental factors. To ensure secure and reliable operations in safety-critical monitoring WSNs, it is important to guarantee energy-efficient communications, location privacy protection, and reliability. Fake packet-based source location privacy (SLP) protocols are known to be energy-inefficient. Therefore, in this study, we investigate the impact of energy-inefficient communications on the privacy performance of the fake packet-based SLP protocols. Experiment results show that the protocols achieve short-term and less reliable SLP protection.
无线传感器网络(WSNs)在无处不在的传感系统服务支持中越来越受欢迎。通常,无线传感器网络是能源有限的,它们部署在恶劣和无人值守的环境中。因此,无线传感器网络容易受到能源和环境因素的影响。为了确保安全关键型监控wsn安全可靠地运行,必须保证通信的高能效、位置隐私保护和可靠性。假的基于数据包的源位置隐私(SLP)协议被认为是低效的。因此,在本研究中,我们研究了能源效率低下的通信对基于假数据包的SLP协议的隐私性能的影响。实验结果表明,该协议实现了短期且不可靠的SLP保护。
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2021 Twelfth International Conference on Ubiquitous and Future Networks (ICUFN)
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