Article
Computer Science, Cybernetics
Yuqi Fan, Lunfei Wang, Weili Wu, Dingzhu Du
Summary: This paper presents a Stackelberg game model based on cloud/edge computing resource management to optimize CESP revenue, and proposes an efficient resource allocation and pricing algorithm. Simulation experiments show that the proposed algorithm can effectively improve the revenue of both the CESP and the IoT terminals.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2021)
Article
Computer Science, Information Systems
Zhiqing Tang, Fuming Zhang, Xiaojie Zhou, Weijia Jia, Wei Zhao
Summary: This paper proposes a novel pricing model for dynamic resource overbooking in edge computing, which includes methods for different user needs, auction billing, and resource prediction. Experimental results show that this dynamic resource overbooking mechanism maximizes the profit of edge nodes and ensures high QoS satisfaction.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Information Systems
Huaming Wu, Katinka Wolter, Pengfei Jiao, Yingjun Deng, Yubin Zhao, Minxian Xu
Summary: This article explores how to achieve secure task offloading collaboration between edge computing and cloud computing using blockchain. By combining MEC and MCC, a blockchain-enabled IoT-Edge-Cloud computing architecture is proposed, providing faster computing services and stronger computational power while minimizing energy consumption and task response time.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Ping-Chun Huang, Tai-Lin Chin, Tzu-Yi Chuang
Summary: Offloading tasks to edge servers has been utilized to reduce latency compared to cloud computing. Properly deploying edge servers and evenly distributing workload are crucial for enhancing user experience. This paper presents a novel approach using simulated annealing and Lagrangian duality theory for optimizing server placement and task allocation. Numerical simulations show improved results compared to conventional methods.
Article
Engineering, Electrical & Electronic
Taejin Kim, Sandesh Dhawaskar Sathyanarayana, Siqi Chen, Youngbin Im, Xiaoxi Zhang, Sangtae Ha, Carlee Joe-Wong
Summary: Edge computing capabilities in 5G wireless networks can reduce latency for mobile users by offloading computing tasks from user devices to nearby edge servers. This paper introduces MoDEMS, a system model and architecture that addresses the challenges of handling long-term user mobility in offloading, aiming to minimize service provider cost and user latency. The authors propose alternative heuristic algorithms for solving the cost minimization problem and validate the results through various experiments, showing a 33% reduction in latency compared to previous migration approaches.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Lingxiang Li, Marie Siew, Zhi Chen, Tony Q. S. Quek
Summary: The article discusses incentive mechanisms based on priority pricing in multi-access edge computing, proposing two pricing schemes: one based on known user profit functions and another based on partial knowledge.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Electrical & Electronic
Weifeng Lu, Shitao Zhang, Jia Xu, Dejun Yang, Lijie Xu
Summary: The research presents two user models for the P2P task offloading system, including the honest user model and the strategy user model. The honest user model solves the resource allocation maximization problem using integer linear programming, while the strategy user model maximizes the number of resource transactions through a double auction mechanism.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Huan Zhou, Zhenning Wang, Nan Cheng, Deze Zeng, Pingzhi Fan
Summary: This article proposes a game theory-based computation offloading method to improve the Quality of Service (QoS) of applications by encouraging cloud-edge servers to participate in the task offloading process. Numerical simulation results demonstrate that the method outperforms other benchmark schemes in different scenarios and effectively promotes the trade of computational resources between edge servers and cloud servers.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Angelo Vera Rivera, Ahmed Refaey, Ekram Hossain
Summary: In the context of a Multi-access Edge Computing (MEC) system, a task sharing mechanism among edge servers is essential for efficiency, but faces challenges in trust and real-time collaboration. This article introduces a blockchain framework with a permissioned scheme to address these challenges and provide incentives for collaboration among edge servers in a MEC environment. Experimental evaluation using Caliper tool and Hyperledger Fabric benchmarks demonstrates the effectiveness of the proposed blockchain scheme within the MEC framework.
Article
Engineering, Electrical & Electronic
Jia Yan, Suzhi Bi, Lingjie Duan, Ying-Jun Angela Zhang
Summary: A proposed MEC service pricing scheme coordinates service caching decisions and controls WDs' task offloading behavior in a cellular network. The study utilizes a two-stage dynamic game of incomplete information to analyze the interaction between the BS and multiple associated WDs, focusing on maximizing expected profit under constraints. The research derives an optimal threshold-based offloading policy at the Bayesian equilibrium and jointly optimizes BS' pricing and service caching through a low-complexity algorithm.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Bizheng Liang, Rongfei Fan, Han Hu, Yu Zhang, Ning Zhang, Alagan Anpalagan
Summary: The article introduces the application research of nonlinear pricing strategy in mobile edge computing, discussing the pricing mechanism and optimal solution of computing task offloading strategy between edge servers and mobile devices through Stackelberg game.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Wei Kuang Lai, Chin-Shiuh Shieh, Yen-Ping Chen
Summary: Edge computing is a computing paradigm designed for low-latency computing, utilizing edge servers deployed at the boundary of the Internet to bridge end devices and centralized cloud servers. Detailed task scheduling is crucial for the success of edge computing systems, considering factors such as servers' capabilities, loadings, and task attributes. A study on task scheduling for multicore edge computing environments shows promising results, improving task completion ratio compared to traditional scheduling algorithms.
Article
Computer Science, Hardware & Architecture
Boubakr Nour, Soumaya Cherkaoui
Summary: This article focuses on the correctness of the final output in computation reuse, and implements a proof of concept to evaluate its effectiveness and efficiency. The results show that computation reuse can significantly reduce task completion time while ensuring high correctness.
Article
Computer Science, Information Systems
Yaser Mansouri, Victor Prokhorenko, Faheem Ullah, Muhammad Ali Babar
Summary: This study experiments on various physical and virtualized computing nodes to reveal which database under which offloading scenario is more efficient in terms of energy, bandwidth, and storage consumption in edge-cloud environments.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Multidisciplinary
Baris Yamansavascilar, Ahmet Cihat Baktir, Cagatay Sonmez, Atay Ozgovde, Cem Ersoy
Summary: The improvements in edge computing technology enable diverse applications that require real-time interaction. However, it is challenging to handle task offloading in a high-performance manner due to the mobility of end-users and the dynamic edge environment. To address this, we propose DeepEdge, a deep reinforcement learning based task orchestrator that can adapt to different task requirements, even under heavily-loaded stochastic network conditions.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Chemistry, Physical
Zhiqian Yang, Liqun Duan, Gang Chang, Wenke Zhou, Zhi Zhang, Fan Wu, Aming Xie, Ziming Xiong
Summary: In this study, a series of carbon microfiber/FeS composites were synthesized using a molten-salt-guided synthetic strategy. The microstructures, electromagnetic response behaviors, and microwave absorption properties of these composites were systematically investigated. The results showed that the prepared composites exhibited effective microwave absorption performance, and the choice of molten salt system had an influence on the properties of the composites.
Article
Computer Science, Information Systems
Qianyi Huang, Youjing Lu, Zhicheng Luo, Hao Wang, Fan Wu, Guihai Chen, Qian Zhang
Summary: Wireless home surveillance cameras are becoming popular for elderly/baby care and burglary detection, but attackers can still infer activities even with encrypted traffic. Despite being overlooked due to requirements, attackers can recover missing packets' metadata and build inference models to launch attacks from a distance without prior knowledge. The article demonstrates that attackers can infer victims' activities up to 40m away without any personal or environmental information.
ACM TRANSACTIONS ON SENSOR NETWORKS
(2023)
Article
Computer Science, Information Systems
Yuben Qu, Dongyu Lu, Haipeng Dai, Haisheng Tan, Shaojie Tang, Fan Wu, Chao Dong
Summary: This paper studies the problem of resilient service provisioning for edge computing, aiming to determine a service placement strategy to maximize overall utility in the presence of uncertain service failures. Two novel solutions are proposed for the general and homogeneous case, respectively, achieving constant approximation ratio within polynomial time and better approximation ratio than previous methods. Extensive simulations and field experiments validate the effectiveness of the proposed algorithms.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Wenhao Fan, Shenmeng Li, Jie Liu, Yi Su, Fan Wu, Yuan'An Liu
Summary: This article proposes a joint task offloading and resource allocation scheme for accuracy-aware machine-learning-based IIoT applications in an edge-cloud-based network architecture. The Lyapunov optimization technique is applied to convert the long-term stochastic optimization problem into a short-term deterministic problem. Two algorithms are proposed to efficiently solve the problem, and the performance of the scheme is proved by theoretical analysis and extensive simulations.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Qinya Li, Zun Li, Zhenzhe Zheng, Fan Wu, Shaojie Tang, Zhao Zhang, Guihai Chen
Summary: With the fast-growing market demand, more and more IoT data is being traded online in cloud-based data marketplaces. However, data consumers face difficulties in making purchasing decisions due to uncertain data quality and inflexible pricing interface. To address these issues, potential solutions include launching data demonstrations and releasing free sampling data to reduce uncertainty about data quality, and implementing flexible pricing based on the volume of data used. The economic benefits of these mechanisms are not yet clear. In this paper, we design optimal data selling mechanisms for IoT data exchange and derive two main findings based on theoretical analysis and evaluation on a real-world Taxi GPS dataset.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Yuben Qu, Lihao Wang, Haipeng Dai, Weijun Wang, Chao Dong, Fan Wu, Song Guo
Summary: In this work, the problem of Robust Server Placement (RSP) for edge computing is studied. The objective is to determine a server placement strategy that maximizes the expected overall workload that can be served by edge servers in the presence of uncertain server failures. The RSP problem is formulated as a robust max-min optimization problem with knapsack constraints, which is challenging to solve. Two algorithms are proposed to solve the RSP problem, both achieving provable approximation ratios in polynomial time. Synthetic and trace-driven simulation results demonstrate the superiority of the proposed algorithms over state-of-the-art approaches.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Virology
Tingting Sun, Yingdan Wang, Peng Zou, Qimin Wang, Jiangyan Liu, Wanli Liu, Jinghe Huang, Fan Wu
Summary: The study constructed three different variants of M2e-specific monoclonal antibodies and found that IgG2a variant provided better protection against influenza virus. Additionally, the administration route and timing of administration were critical factors in determining the protective efficacy.
JOURNAL OF MEDICAL VIROLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Hao Ma, Fan Wu, Yun Guan, Le Xu, Jiangcong Liu, Lixia Tian
Summary: This study aims to improve the performance of individualized predictive models based on RS-fMRI by introducing effective feature extraction and utilization strategies, and making better use of hidden information in RS-fMRI data. A novel framework called multi-facet BrainNet with connectivity attention (MFBCA) was proposed, which showed superior performance compared to baselines.
COGNITIVE COMPUTATION
(2023)
Article
Computer Science, Hardware & Architecture
Fan Wu, Feng Lyu, Huaqing Wu, Ju Ren, Yaoxue Zhang, Xuemin (Sherman) Shen
Summary: This article explores data-driven approaches to optimize edge system performance by mining user association patterns in WLAN. The study describes the collected association traces and analyzes the impact of user association patterns on edge system performance. Three data-driven approaches are proposed, including efficient resource deployment, mobility-aware user service migration, and distributed cooperative learning for edge intelligence. A case study on distributed learning validates the effectiveness of the proposed cooperation scheme, CoLo.
Article
Engineering, Civil
Muhammad Asad Saleem, Xiong Li, Muhammad Faizan Ayub, Salman Shamshad, Fan Wu, Haider Abbas
Summary: The popularity of vehicles has led to the development of smart cities, making vehicular ad-hoc network (VANET) a widely used communication method for obtaining information about road conditions, speed, vehicle location, and traffic congestion. However, the security of private data in VANET is a critical task due to various security threats. In this article, a lightweight and secure privacy-preserving key agreement protocol for VANETs is proposed, which utilizes hashing technique for efficient and secure data transmission.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Xikun Jiang, Neal N. Xiong, Xudong Wang, Chenhao Ying, Fan Wu, Yuan Luo
Summary: This paper proposes an efficient and flexible online service platform architecture for data classification and investigates pricing design to maximize revenue. It addresses three significant challenges and proposes DIVINE, a query-based data classification service with an online pricing mechanism. Experimental results demonstrate that DIVINE outperforms existing pricing mechanisms in terms of revenue.
INFORMATION SCIENCES
(2023)
Review
Materials Science, Multidisciplinary
Jing Qiao, Lutong Li, Jiurong Liu, Na Wu, Wei Liu, Fan Wu, Zhihui Zeng
Summary: Rare earth plays a crucial role in electromagnetic wave absorption materials, and the strategies of doping rare earth elements and constructing rare earth oxide composites are important for the fabrication of high-efficiency electromagnetic wave absorption materials. This review provides a comprehensive summary of the research background, classification, features, progress, and future development of rare earth electromagnetic wave absorption materials, offering guidance for future development.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2024)