Article
Computer Science, Information Systems
Huan Li, Daosen Zhai, Ruonan Zhang, Chen Wang, Xiao Tang
Summary: This letter investigates an air-and-ground cooperative network, where aerial base stations assist terrestrial base stations for coverage enhancement. The space-time coverage ratio (STCR) is quantified by considering antenna models and the dynamic of the aerial base stations. The joint deployment problem and antenna downtilt optimization problem are formulated to maximize the STCR. A genetic algorithm (GA) is employed to effectively solve the problem, and a deep neural network architecture is proposed to reduce computational time.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Shengchao Su, Chen Yang, Xiang Ju, Chaojie Xu
Summary: This article presents a method for deployment optimization and critical node identification using self-powered sensors to address the limited coverage problem in the sensing layer of the Internet of Things. By improving the particle swarm optimization algorithm, the position of self-powered sensors can be obtained to achieve the desired coverage performance. When failed critical nodes are detected, redundancy nodes are activated to enhance coverage tolerance.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Yang Zhao, Xiaoxia Zhao, Lingyun Li, Xianhui Liu, Qinwei Li
Summary: Passive ultrahigh-frequency radio-frequency identification (UHF RFID) is gaining popularity in indoor localization due to its low cost and low complexity. However, densely deployed tags induce antenna interference, leading to poor signal similarity between nearby tags. This article proposes a tag interference model, called Timing, to analyze the relationship between signal fluctuations and spacing distances. Experimental results demonstrate its suitability in authentic situations and show that the spacing distance identified by Timing achieves better accuracy in scene analysis localization algorithms.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Ziaul Haq Abbas, Muhammad Sajid Haroon, Fazal Muhammad, Ghulam Abbas, Frank Y. Li
Summary: Heterogeneous cellular networks (HetNets) are crucial for 5G networks, offering higher throughput and improved coverage. However, challenges such as inter-cell interference, MBS interference, and lower SIR for edge users need to be addressed in multi-tier base station deployment.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Multidisciplinary
Yuhao Jing, Zhaohui Yang, Pingfang Zhou, Yueying Wang, Huaicheng Yan
Summary: This paper proposes an Earth-observation model with considerations of loading devices' side-swing characteristics and field of view (FOV), and establishes a collaborative deployment model of Multi-airship Earth-observation Coverage Network (MAEON) to achieve observation coverage, target point statistics, observation resolution, and multi-airship community profit objectives. A multi-objective evolutionary optimization algorithm (MOEA) with associated bi-criterion is proposed to efficiently and extensively obtain the solution set of cooperative deployment problem. Through simulation experiments, it is shown that the proposed algorithm outperforms popular MOEAs in performance, universality, and stability.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Information Systems
Bin Cao, Yu Gu, Zhihan Lv, Shan Yang, Jianwei Zhao, Yujie Li
Summary: An improved RFID reader anticollision model is proposed in this article, utilizing intelligent computing technologies and distributed parallel cooperative co-evolution particle swarm optimization to address the high-dimensional problem of dense deployment of large numbers of readers.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Civil
Peng Yu, Yahui Ding, Zifan Li, Jingyue Tian, Junye Zhang, Yanbo Liu, Wenjing Li, Xuesong Qiu
Summary: With the development of 5G/6G networks, the use of unmanned aerial vehicles as base stations for ground users has become a trend to enhance coverage and capacity in fast access scenarios. This paper focuses on the energy-efficient deployment of UAV-BSs for coverage and capacity enhancement in disaster areas or burst data traffic. By using DQN and A3C algorithms, optimal flight paths and user connections are obtained, showing that dynamic flying paths consume less energy for user detection and the proposed solution provides high-quality service with high energy efficiency.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Chemistry, Analytical
Luoheng Yan, Yuyao He, Zhongmin Huangfu
Summary: This study presents an optimization algorithm that can enhance the coverage and reliability of UWSNs, addressing key deployment issues and effectively avoiding energy holes.
Article
Computer Science, Information Systems
Yongjian Yang, Jufeng Hou, Yuanbo Xu
Summary: In the era of smart cities, the challenge of choosing signal station locations for efficient transmission and reception of multi-modal data persists. To address this, we propose the SRD model, which optimizes signal station deployment through image-based super resolution deduction.
Article
Automation & Control Systems
Haipeng Li, Dazheng Feng, Xiaohui Wang
Summary: To address the problem of building linear barrier coverage with location restriction, this paper proposes an optimization method for deploying multistatic radars. The deployment line is divided into two segments due to the location restriction. An optimal deployment sequence consisting of multiple deployment patterns is proposed and exploited to cover each segment by proving the characteristics of deployment patterns. The algorithm combines integer linear programming (ILP) and exhaustive method (EM) to determine the types and numbers of deployment patterns.
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
(2023)
Article
Telecommunications
Hao Qin, Zhen Liu, Chuanchuan Yang
Summary: This letter investigates the impact of indoor RIS deployment on indoor signal coverage and proposes an indoor RIS deployment strategy considering human mobility to minimize the outage probability. Numerical results demonstrate that deploying RIS correctly can significantly decrease the indoor communication outage probability.
IEEE COMMUNICATIONS LETTERS
(2022)
Article
Computer Science, Hardware & Architecture
M. A. Tahouri, M. Abbasi, M. R. Mosavi
Summary: GPS signals can easily be interfered with, and interference cancellation is a major challenge. The use of an Adaptive Notch Filter helps reduce the impact of interference on GPS signals. Heuristic Evolutionary Algorithms are used to design and implement the filter in hardware.
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS
(2021)
Article
Engineering, Electrical & Electronic
Renxin Sun, Dong Zhao, Lige Ding, Jing Zhang, Huadong Ma
Summary: Nowadays, in scenarios with insufficient or unstable network bandwidth, unmanned aerial vehicle mounted base stations (UAV-BSs) provide a promising solution. It is important to investigate the effective deployment of UAVs to maximize the sum throughput and service time of mobile clients. This study proposes algorithms based on deep reinforcement learning (DRL) to efficiently solve the NP-hard sub-problems of chunk selection and chunk search, achieving a significant throughput gain with minimal time cost.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Jung-Hoon Noh, Byungju Lee, Seong-Jun Oh
Summary: This study investigates the operation of a user-number threshold-based base station on/off control and presents a space-based analysis of the system using stochastic geometric approach. The study derives closed-form expressions and optimal thresholds for coverage probability in homogeneous and heterogeneous networks. Results show that heterogeneous networks can be analyzed as a combination of weighted densities of homogeneous networks, with independently adjustable thresholds for each tier.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Muhammad Adil, Said Nabi, Summair Raza
Summary: Cloud computing is a technology that provides hosted services over the internet, offering scalability, efficiency, and cost reduction. However, the main challenge in cloud computing is the even distribution of workload across heterogeneous servers. Most existing cloud scheduling and load balancing schemes do not consider the content type of user tasks. This paper proposes a novel hybrid approach, named Particle Swarm Optimization based Content-Aware Load Balancing Algorithm (PSO-CALBA), which combines machine learning and meta-heuristic algorithm to classify user tasks based on content type and map them onto the cloud using Particle Swarm Optimization. The proposed approach shows significant improvements in terms of makespan and degree of imbalance.
COMPUTING AND INFORMATICS
(2022)
Article
Environmental Sciences
Linze Li, Dalai Hao, Xuecao Li, Min Chen, Yuyu Zhou, Dawn Jurgens, Ghassam Asrar, Amir Sapkota
Summary: Climate change impacts pollen exposure among sensitive populations, and the lack of high spatial resolution pollen data has led to a growing interest in using satellite-derived phenology information to infer key pollen events. Results show that MODIS-based SOS is more closely aligned with in-situ SPS and PPS, while Landsat-based SOS has better precision. Data products obtained using DLM processing methods tend to perform better than HPLM-based methods.
ENVIRONMENTAL RESEARCH
(2022)
Article
Environmental Sciences
Fang Wang, Biao Zheng, Jintao Zhang, Yuyu Zhou, Mingrui Jia
Summary: This study established an efficient evaluation method to quantify the benefits from the potential heat stress reduction. Results showed that delayed mitigation efforts could greatly increase the frequency, duration, and intensity of extreme heat stress, while more ambitious efforts could significantly reduce the impact of heat stress. Low latitude regions, where most developing countries are located, are most sensitive to emission reduction.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Remote Sensing
Xuecao Li, Yuyu Zhou, Peng Gong
Summary: This study proposes a conceptual model to characterize the spatial sprawl pattern of urban clusters using Zipf's law and 30-year time series of global urban extent data. The study reveals different sprawl patterns at different scales, with small urban clusters growing slightly faster than large clusters globally. It also finds that Asia and Africa show equilibrium patterns of sprawl, while other continents mostly exhibit diffuse patterns. The study provides insights into urban development pathways and contributes to the development of future urban growth models.
REMOTE SENSING LETTERS
(2023)
Article
Urban Studies
Wanru He, Xuecao Li, Yuyu Zhou, Xiaoping Liu, Peng Gong, Tengyun Hu, Peiyi Yin, Jianxi Huang, Jianyu Yang, Shuangxi Miao, Xi Wang, Tinghai Wu
Summary: Cellular automata (CA) based models are widely used in urban sprawl modeling for sustainable urban planning. However, most existing urban CA models only consider abrupt conversion, ignoring the difference in urbanization levels among grids and the gradual increase in urban densities. In this study, we proposed an impervious surface area (ISA) based urban CA model that can simulate urban fractional change within each grid. The model was implemented in Beijing and evaluated through comparison and scenario analyses. Results showed that the ISA-based urban CA model captures the dynamics of urban sprawl better than the traditional urban CA model and has great potential in supporting sustainable urban development.
Article
Agronomy
Tongxi Hu, Xuesong Zhang, Gil Bohrer, Yanlan Liu, Yuyu Zhou, Jay Martin, Yang Li, Kaiguang Zhao
Summary: Statistical crop modeling is crucial for understanding the impact of climate on crop yields. The choice of models is important, as linear regression is interpretable but lacks predictive power, while machine learning is highly predictive but often lacks interpretability. In this study, a Bayesian ensemble model (BM) was developed to explore historical crop yield data and predict future yields, providing both interpretability and high predictive power. BM incorporates many models via Bayesian model averaging, fits complex functions, and quantifies model uncertainty.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Chunyu Guo, Kevin Lanza, Dongying Li, Yuyu Zhou, Kristin Aunan, Becky P. Y. Loo, Jason Kai Wei Lee, Bin Luo, Xiaoli Duan, Wangjian Zhang, Zhengjun Zhang, Shao Lin, Kai Zhang
Summary: This study examines the effects of heat on mortality in 12 metropolitan areas across Texas. The results show that high temperatures have a significant impact on all-cause mortality in Texas, and the effect varies by region, age group, and cause of death.
ENVIRONMENTAL RESEARCH
(2023)
Article
Environmental Sciences
Long Li, Wenfeng Zhan, Weimin Ju, Josep Penuelas, Zaichun Zhu, Shushi Peng, Xiaolin Zhu, Zihan Liu, Yuyu Zhou, Jiufeng Li, Jiameng Lai, Fan Huang, Gaofei Yin, Yongshuo Fu, Manchun Li, Chao Yu
Summary: Urban vegetation is influenced by complex urban environments. The study reveals that greenness trends decrease from urban cores to urban new towns, and brownish trends are observed in urban fringes. These results highlight the joint influence of biogeochemical drivers and land-cover changes on the urban-rural gradient in vegetation trends, providing insights into future global vegetation change.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Agronomy
Songhan Wang, Alessandro Cescatti, Yongguang Zhang, Yuyu Zhou, Lian Song, Ji Li
Summary: By analyzing high spatial resolution satellite solar-induced chlorophyll fluorescence (SIF) data from 160 mega-cities worldwide, we investigated the impact of urbanization on vegetation primary productivity and its drivers. The results showed that SIF enhancements resulting from indirect urbanization impact offset approximately 47% of SIF reductions caused by land cover change. Atmospheric CO2, air temperature, radiation, and atmospheric nitrogen dioxide (NO2) were identified as the main drivers of enhanced SIF in urban areas. Our findings demonstrate a dominant and global enhancement of vegetation photosynthesis in urban conditions, providing insights into the specific contribution of climatic and environmental factors.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Geography, Physical
Qiming Zheng, Karen C. Seto, Yuyu Zhou, Shixue You, Qihao Weng
Summary: Nighttime light (NTL) remote sensing data have been extensively used to understand urbanization. A literature review of 688 papers published between 1992 and 2022 identified the trends and challenges in NTL-based urban applications. Future research directions include understanding scale effects and variations in NTL data, integrating multi-source NTL data with other geospatial data, focusing on the Global South, and developing new urban applications with new NTL data products. Addressing research gaps in these areas will provide new insights into urbanization under different settings.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Geography, Physical
Yixuan Wang, Xuecao Li, Peiyi Yin, Guojiang Yu, Wenting Cao, Jinxiu Liu, Lin Pei, Tengyun Hu, Yuyu Zhou, Xiaoping Liu, Jianxi Huang, Peng Gong
Summary: In this study, the annual dynamics of built-up heights in Beijing from 1990 to 2020 were reconstructed using Landsat time-series data. The results revealed that most expanded built-up areas during this period were located at the fringe of the central city, with about 16% experiencing multiple changes. The study also found that outward growth was prominent in Beijing during the first decade, while upward growth became dominant in most districts thereafter.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Jia Hu, Yuyu Zhou, Yingbao Yang, Gang Chen, Wei Chen, Mohamad Hejazi
Summary: This study used the SOLWEIG model and remote sensing data to generate hourly heat exposure maps in three US cities during heat wave and non-heat wave days. The study found high heat exposure in urban downtown areas due to low building height and limited shading effect. Heat exposure during heat waves was increased by 6°C to 10°C compared to non-heat wave conditions, and hot cities had higher heat exposure than warm cities. Sky view factor was the most important factor influencing heat exposure, while the role of impervious surface and trees varied among cities.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Multidisciplinary Sciences
Chenghao Wang, Jiyun Song, Dachuan Shi, Janet L. Reyna, Henry Horsey, Sarah Feron, Yuyu Zhou, Zutao Ouyang, Ying Li, Robert B. Jackson
Summary: Climate, technologies, and socio-economic changes will influence future building energy use in cities. A study on 277 U.S. urban areas shows that climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, with population and power sector changes being the primary factors driving city-scale building energy use changes. Considering intercity heterogeneity is crucial when developing sustainable and resilient urban energy systems.
NATURE COMMUNICATIONS
(2023)
Article
Geochemistry & Geophysics
Hanzeyu Xu, Yuyu Zhou, Yuchun Wei, Houcai Guo, Xiao Li
Summary: Relative radiometric normalization (RRN) is an effective method for enhancing radiometric consistency among multitemporal satellite images. In this study, we propose a multirule-based RRN method that identifies spectral- and spatial-invariant pseudo-invariant features (PIFs) and uses partial least-squares (PLS) regression to model RRN, resulting in improved radiometric consistency between reference-target image pairs. Our method outperforms six other RRN methods and shows potential for generating more comparable bitemporal multisensor images.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geosciences, Multidisciplinary
Wanru He, Xuecao Li, Yuyu Zhou, Zitong Shi, Guojiang Yu, Tengyun Hu, Yixuan Wang, Jianxi Huang, Tiecheng Bai, Zhongchang Sun, Xiaoping Liu, Peng Gong
Summary: This study developed a dataset of global urban fractional changes, which can support quantitative analysis of urbanization-induced ecological and environmental change at a fine scale.
EARTH SYSTEM SCIENCE DATA
(2023)
Article
Engineering, Electrical & Electronic
Hanzeyu Xu, Yuyu Zhou, Yuchun Wei, Chong Liu, Xiao Li, Wei Chen
Summary: In this study, a novel RRN method was proposed to enhance the radiometric consistency of Landsat time-series images by trend-based PIFs identification, PIFs optimization, and combined RRN modeling. The experimental results showed that the proposed method achieved good performance in model precision and radiance consistency improvement, outperforming seven commonly used RRN methods.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Computer Science, Hardware & Architecture
Zihang Zhen, Xiaoding Wang, Hui Lin, Sahil Garg, Prabhat Kumar, M. Shamim Hossain
Summary: In this paper, a blockchain architecture based on dynamic state sharding (DSSBD) is proposed to solve the problems caused by cross-shard transactions and reconfiguration. By utilizing deep reinforcement learning, the number of shards, block spacing, and block size can be dynamically adjusted to improve the performance of the blockchain. The experimental results show that the crowdsourcing system with DSSBD has better performance in terms of throughput, latency, balancing, cross-shard transaction proportion, and node reconfiguration proportion, while ensuring security.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Gabriel F. C. de Queiroz, Jose F. de Rezende, Valmir C. Barbosa
Summary: Multi-access Edge Computing (MEC) is a technology that enables faster task processing at the network edge by deploying servers closer to end users. This paper proposes the FlexDO algorithm to solve the DAG application partitioning and offloading problem, and compares it with other solutions to demonstrate its superior performance in various test scenarios.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shahid Latif, Wadii Boulila, Anis Koubaa, Zhuo Zou, Jawad Ahmad
Summary: In the field of Industrial Internet of Things (IIoT), networks are increasingly vulnerable to cyberattacks. This research introduces an optimized Intrusion Detection System based on Deep Transfer Learning (DTL) for heterogeneous IIoT networks, combining Convolutional Neural Networks (CNNs), Genetic Algorithms (GA), and ensemble techniques. Through rigorous evaluation, the framework achieves exceptional performance and accurate detection of various cyberattacks.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Rongji Liao, Yuan Zhang, Jinyao Yan, Yang Cai, Narisu Tao
Summary: This paper proposes a joint control approach called STOP to guarantee user-perceived deadline using curriculum-guided deep reinforcement learning. Experimental results show that the STOP scheme achieves a significantly higher average arrival ratio in NS-3.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Miguel Rodriguez-Perez, Sergio Herreria-Alonso, J. Carlos Lopez-Ardao, Raul F. Rodriguez-Rubio
Summary: This paper presents an implementation of an active queue management (AQM) algorithm for the Named-Data Networking (NDN) architecture and its application in congestion control protocols. By utilizing the congestion mark field in NDN packets, information about each transmission queue is encoded to achieve a scalable AQM solution.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Angel Canete, Mercedes Amor, Lidia Fuentes
Summary: This paper proposes an energy-aware placement of service function chains of Virtual Network Functions (VNFs) and a resource-allocation solution for heterogeneous edge infrastructures. The solution has been integrated with an open source management and orchestration project and has been successfully applied to augmented reality services, achieving significant reduction in power consumption and ensuring quality of service compliance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Sachin Kadam, Kaustubh S. Bhargao, Gaurav S. Kasbekar
Summary: This paper discusses the problem of estimating the node cardinality of each node type in a heterogeneous wireless network. Two schemes, HSRC-M1 and HSRC-M2, are proposed to rapidly estimate the number of nodes of each type. The accuracy and efficiency of these schemes are proven through mathematical analysis and simulation experiments.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Jean Nestor M. Dahj, Kingsley A. Ogudo, Leandro Boonzaaier
Summary: The launch of commercial 5G networks has opened up opportunities for heavy data users and highspeed applications, but traditional monitoring and evaluation techniques have limitations in the 5G networks. This paper presents a cost-effective hybrid analytical approach for detecting and evaluating user experience in real-time 5G networks, using statistical methods to calculate the user quality index.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Ali Nauman, Haya Mesfer Alshahrani, Nadhem Nemri, Kamal M. Othman, Nojood O. Aljehane, Mashael Maashi, Ashit Kumar Dutta, Mohammed Assiri, Wali Ullah Khan
Summary: The integration of terrestrial and satellite wireless communication networks offers a practical solution to enhance network coverage, connectivity, and cost-effectiveness. This study introduces a resource allocation framework that leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to improve energy efficiency. Through the use of a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG), the proposed approach optimizes user association, cache design, and transmission power control, resulting in enhanced energy efficiency and reduced time delays compared to existing methods.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Wu Chen, Jiayi Zhu, Jiajia Liu, Hongzhi Guo
Summary: With advancements in technology, large-scale drone swarms will be widely used in commercial and military fields. Current application methods are mainly divided into autonomous methods and controlled methods. This paper proposes a new framework for global coordination through local interaction.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Peiying Zhang, Zhihu Luo, Neeraj Kumar, Mohsen Guizani, Hongxia Zhang, Jian Wang
Summary: With the development of Industry 5.0, the demand for network access devices is increasing, especially in areas such as financial transactions, drone control, and telemedicine where low latency is crucial. However, traditional network architectures limit the construction of low-latency networks due to the tight coupling of control and data forwarding functions. To overcome this problem, researchers propose a constraint escalation virtual network embedding algorithm assisted by Graph Convolutional Networks (GCN), which automatically extracts network features and accelerates the learning process to improve network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Review
Computer Science, Hardware & Architecture
P. Anitha, H. S. Vimala, J. Shreyas
Summary: Congestion control is crucial for maintaining network stability, reliability, and performance in IoT. It ensures that critical applications can operate seamlessly and that IoT devices can communicate efficiently without overwhelming the network. Congestion control algorithms ensure that the network operates within its capacity, preventing network overload and maintaining network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shunmugapriya Ramanathan, Abhishek Bhattacharyya, Koteswararao Kondepu, Andrea Fumagalli
Summary: This article presents an experiment that achieves live migration of a containerized 5G Central Unit module using modified open-source migration software. By comparing different migration techniques, it is found that the hybrid migration technique can reduce end-user service recovery time by 36% compared to the traditional cold migration technique.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Fatma Foad Ashrif, Elankovan A. Sundararajan, Rami Ahmad, Mohammad Kamrul Hasan, Elaheh Yadegaridehkordi
Summary: This article introduces the development and current status of authentication protocols in 6LoWPAN, and proposes an innovative perspective to fill the research gap. The article comprehensively surveys and evaluates AKA protocols, analyzing their suitability in wireless sensor networks and the Internet of Things, and proposes future research directions and issues.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Pranjal Kumar Nandi, Md. Rejaul Islam Reaj, Sujan Sarker, Md. Abdur Razzaque, Md. Mamun-or-Rashid, Palash Roy
Summary: This paper proposes a task offloading policy for IoT devices to a mobile edge computing system, aiming to balance device utility and execution cost. A meta heuristic approach is developed to solve the offloading problem, and the results show its potential in terms of task execution latency, energy consumption, utility per unit cost, and task drop rate.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
