Yong Ma¹, Han Zhao², Kunyin Guo^3,*, Yunni Xia^3,*, Xu Wang⁴, Xianhua Niu⁵, Dongge Zhu⁶, Yumin Dong⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 907-927, 2024, DOI:10.32604/cmes.2024.048759

Abstract Mobile Edge Computing (MEC) is a technology designed for the on-demand provisioning of computing and storage services, strategically positioned close to users. In the MEC environment, frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery, ultimately enhancing the quality of the user experience. However, due to the typical placement of edge devices and nodes at the network’s periphery, these components may face various potential fault tolerance challenges, including network instability, device failures, and resource constraints. Considering the dynamic nature of MEC, making high-quality content caching decisions for real-time mobile applications, especially… More >

Seungwoo Kang¹, Seyha Ros¹, Inseok Song¹, Prohim Tam¹, Sa Math², Seokhoon Kim^1,3,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1967-1983, 2023, DOI:10.32604/cmc.2023.045020

Abstract Intelligent healthcare networks represent a significant component in digital applications, where the requirements hold within quality-of-service (QoS) reliability and safeguarding privacy. This paper addresses these requirements through the integration of enabler paradigms, including federated learning (FL), cloud/edge computing, software-defined/virtualized networking infrastructure, and converged prediction algorithms. The study focuses on achieving reliability and efficiency in real-time prediction models, which depend on the interaction flows and network topology. In response to these challenges, we introduce a modified version of federated logistic regression (FLR) that takes into account convergence latencies and the accuracy of the final FL model within healthcare networks. To establish… More >

Amal H. Alharbi¹, S. Karthick², K. Venkatachalam³, Mohamed Abouhawwash^4,5, Doaa Sami Khafaga^1,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2773-2787, 2023, DOI:10.32604/iasc.2023.030763

Abstract Recent security applications in mobile technologies and computer systems use face recognition for high-end security. Despite numerous security techniques, face recognition is considered a high-security control. Developers fuse and carry out face identification as an access authority into these applications. Still, face identification authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized user. In the existing spoofing detection algorithm, there was some loss in the recreation of images. This research proposes an unobtrusive technique to detect face spoofing attacks that apply a single frame of the sequenced set of… More >

Siyuan Sun^1,*, Junhua Zhou², Jiuxing Wen³, Yifei Wei¹, Xiaojun Wang⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3277-3291, 2022, DOI:10.32604/cmc.2022.020471

Abstract The emerging mobile edge networks with content caching capability allows end users to receive information from adjacent edge servers directly instead of a centralized data warehouse, thus the network transmission delay and system throughput can be improved significantly. Since the duplicate content transmissions between edge network and remote cloud can be reduced, the appropriate caching strategy can also improve the system energy efficiency of mobile edge networks to a great extent. This paper focuses on how to improve the network energy efficiency and proposes an intelligent caching strategy according to the cached content distribution model for mobile edge networks based… More >

Merna Gamal¹, Hala M. Abbas², Nour Moustafa^3,*, Elena Sitnikova³, Rowayda A. Sadek¹

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1823-1837, 2021, DOI:10.32604/cmc.2021.012877

Abstract Intrusion Detection Systems (IDSs) have a great interest these days to discover complex attack events and protect the critical infrastructures of the Internet of Things (IoT) networks. Existing IDSs based on shallow and deep network architectures demand high computational resources and high volumes of data to establish an adaptive detection engine that discovers new families of attacks from the edge of IoT networks. However, attackers exploit network gateways at the edge using new attacking scenarios (i.e., zero-day attacks), such as ransomware and Distributed Denial of Service (DDoS) attacks. This paper proposes new IDS based on Few-Shot Deep Learning, named CNN-IDS,… More >

Sa Math¹, Prohim Tam¹, Seokhoon Kim^2,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3433-3450, 2021, DOI:10.32604/cmc.2021.015490

Abstract In the Next Generation Radio Networks (NGRN), there will be extreme massive connectivity with the Heterogeneous Internet of Things (HetIoT) devices. The millimeter-Wave (mmWave) communications will become a potential core technology to increase the capacity of Radio Networks (RN) and enable Multiple-Input and Multiple-Output (MIMO) of Radio Remote Head (RRH) technology. However, the challenging key issues in unfair radio resource handling remain unsolved when massive requests are occurring concurrently. The imbalance of resource utilization is one of the main issues occurs when there is overloaded connectivity to the closest RRH receiving exceeding requests. To handle this issue effectively, Machine Learning… More >

Yuxin Xu¹, Zilong Jin^1,2,*, Xiaorui Zhang¹, Lejun Zhang³

Journal on Internet of Things, Vol.2, No.4, pp. 163-173, 2020, DOI:10.32604/jiot.2020.011792

Abstract The vehicle edge network (VEN) has become a new research hotspot in the Internet of Things (IOT). However, many new delays are generated during the vehicle offloading the task to the edge server, which will greatly reduce the quality of service (QOS) provided by the vehicle edge network. To solve this problem, this paper proposes an evolutionary algorithm-based (EA) task offloading and resource allocation scheme. First, the delay of offloading task to the edge server is generally defined, then the mathematical model of problem is given. Finally, the objective function is optimized by evolutionary algorithm, and the optimal solution is… More >

Li Li^1,*, Yifei Wei¹, Lianping Zhang², Xiaojun Wang³

Journal of Cyber Security, Vol.2, No.3, pp. 141-150, 2020, DOI:10.32604/jcs.2020.010764

Abstract The rapid growth of Internet content, applications and services require more computing and storage capacity and higher bandwidth. Traditionally, internet services are provided from the cloud (i.e., from far away) and consumed on increasingly smart devices. Edge computing and caching provides these services from nearby smart devices. Blending both approaches should combine the power of cloud services and the responsiveness of edge networks. This paper investigates how to intelligently use the caching and computing capabilities of edge nodes/cloudlets through the use of artificial intelligence-based policies. We first analyze the scenarios of mobile edge networks with edge computing and caching abilities,… More >