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International Journal of Ad Hoc and Ubiquitous Computing最新文献

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Wireless communications with hybrid solar and RF energy harvesting 无线通信与混合太阳能和射频能量收集
IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2022.10052806
Raed I. Alhamad
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引用次数: 0
Merit: an on-demand IoT service delivery and resource scheduling scheme for federated learning and blockchain empowered 6G edge networks with reduced time and energy cost 优点:针对联邦学习和区块链支持的6G边缘网络的按需物联网服务交付和资源调度方案,减少了时间和能源成本
4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.134603
Mahfuzulhoq Chowdhury
Federated learning (FL) can improve the privacy-preserving issue of users' IoT devices, in which users complete the local training and transfer the updated model data to the central server for a global update. Due to high latency, the central server-based FL may suffer from huge energy loss at local user devices. MEC-based FL can improve the model accuracy and energy consumption at user devices via edge server-based task execution. Along with FL, blockchain can improve data security via permission-based access. Existing works explored only single type of IoT task without any appropriate resource scheduling for multiple tasks with different preferences, FL, and blockchain operations. This paper provides a merit-based resource scheduling scheme for different tasks with preferences, blockchain, and FL operations by checking resources, deadlines, delays, and resource costs. The simulation results verify that 45% running time and 53% cost gain is achieved in proposed scheme over the baseline schemes.
联邦学习(FL)可以改善用户物联网设备的隐私保护问题,其中用户完成本地训练并将更新的模型数据传输到中央服务器进行全局更新。由于中心服务器的高时延,可能会造成本地用户设备的巨大能量损失。基于mec的FL可以通过基于边缘服务器的任务执行来提高用户设备上的模型精度和能耗。与FL一起,区块链可以通过基于权限的访问来提高数据安全性。现有的工作只探索了单一类型的物联网任务,没有对具有不同偏好、FL和区块链操作的多个任务进行适当的资源调度。本文通过检查资源、截止日期、延迟和资源成本,为具有偏好、区块链和FL操作的不同任务提供了基于绩效的资源调度方案。仿真结果表明,与基准方案相比,该方案的运行时间提高了45%,成本提高了53%。
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引用次数: 0
Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces (STAR-RIS) with Multi-antenna Energy Harvesting and Adaptive Power 具有多天线能量收集和自适应功率的同步发射和反射可重构智能表面(STAR-RIS)
4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.10058370
RAED ALHAMAD
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引用次数: 0
A hybrid approach for feature selection using SFFS and SBFS with extra-tree and classification using XGBoost 使用SFFS和SBFS进行特征选择的混合方法,并使用XGBoost进行额外树和分类
4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.132998
Ankit Kharwar, Devendra Thakor
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引用次数: 0
Analysis of sponsoring and caching data: the case of competing ISPs in information-centric networks 赞助和缓存数据的分析:信息中心网络中相互竞争的isp的案例
IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.10054346
M. Jourhmane, R. Ayachi, Mohamed Baslam, Hamid Garmani, Khadija Touya
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引用次数: 0
Disaster evacuation route planning strategy based on traffic prediction 基于交通预测的灾害疏散路线规划策略
4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.133463
Hsin Chung Huang, Chih Min Chao
A well-planned evacuation route can help to prevent traffic congestion and reduce the time required for evacuation; however, many existing evacuation route-planning solutions based on real-time traffic conditions fail to consider the degree to which evacuation guidance can exacerbate traffic congestion. This paper proposes an evacuation route-planning algorithm based on predictions of future traffic conditions. The proposed scheme tries to find evacuation routes out of a given disaster area such that evacuation is completed as fast as possible. Simulation results verify that the proposed algorithm can complete evacuations 18% faster than MacroServ, currently the best evacuation route-planning system.
周密规划的疏散路线有助于防止交通堵塞,减少疏散所需的时间;然而,现有的许多基于实时交通状况的疏散路线规划方案没有考虑疏散引导对交通拥堵的加剧程度。本文提出了一种基于未来交通状况预测的疏散路线规划算法。拟议的方案试图找到撤离特定灾区的路线,以便尽快完成撤离。仿真结果表明,该算法完成疏散的速度比目前最好的疏散路线规划系统MacroServ快18%。
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引用次数: 0
A novel compact radiator for WLAN, WiMAX and 5G applications 一款适用于WLAN、WiMAX和5G应用的新型紧凑型散热器
IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.131781
Abhilash S. Vasu, T. Sreeja
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引用次数: 0
An optimised Darknet traffic detection system using modified locally connected CNN - BiLSTM network 基于改进的本地连接CNN - BiLSTM网络的优化暗网流量检测系统
IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2022.10051751
A. Shaikh, M. Bhargavi, C. P. Kumar
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引用次数: 0
A survey of intelligent load monitoring in IoT-enabled distributed smart grids 基于物联网的分布式智能电网智能负荷监测研究
4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.127781
Jixiang Gan, Lei Zeng, Qi Liu, Xiaodong Liu
Power load monitoring has been a research hotspot since a few years ago. With development of artificial intelligence, construction of smart grid has become the most important part of power load monitoring. At the same time, task scheduling mechanism combined with the distributed internet of things (IoT) improves efficiency of smart grid. In this paper, applications of cloud/edge platform in the data acquisition, processing and scheduling of the IoT is introduced step by step, as well as applications and differences of artificial intelligence algorithm in each step, including data acquisition, load disaggregation, load forecasting and so on. Finally, combined with various optimisation methods, future research directions are prospected, including data and network security issues, and challenges faced by cloud/edge architecture, adaptive fine-grained load disaggregation, and load forecasting.
近年来,电力负荷监测一直是一个研究热点。随着人工智能的发展,智能电网的建设已成为电力负荷监测的重要组成部分。同时,与分布式物联网相结合的任务调度机制提高了智能电网的效率。本文逐步介绍了云/边缘平台在物联网数据采集、处理和调度中的应用,以及人工智能算法在数据采集、负荷分解、负荷预测等各个步骤中的应用和差异。最后,结合各种优化方法,展望了未来的研究方向,包括数据和网络安全问题,以及云/边缘架构、自适应细粒度负载分解和负载预测面临的挑战。
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引用次数: 1
Impact: A Mission-driven, Human-centric, Super-smart Service Orchestration Scheme for Society 5.0 and Industry 4.0 Application Execution Over CPSS Enhanced 6G Networks 影响:在CPSS增强型6G网络上为社会5.0和工业4.0应用执行提供任务驱动、以人为本、超智能的服务编排方案
4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-01-01 DOI: 10.1504/ijahuc.2023.10059943
Mahfuzulhoq Chowdhury
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引用次数: 0
期刊
International Journal of Ad Hoc and Ubiquitous Computing
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