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23 articles for “Edge Computing”
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Research ArticleOpen accessPhrase in the titleEdge Computing Enabled Human Activity Recognition (ECEHAR) Using LSTM and CNNSuresh Kumar, M Y. Mohamed ParveesHuman Activity Recognition (HAR) is an important research area for various application domains such as healthcare, gaming, telemonitoring, and sports. However, executing HAR algorithms on remote servers or in the cloud have challenges in terms of high latency, increased bandwidth demand, and high energy consumption. Moving the computation to edge-assisted HAR is more effective and flexible solution to address the … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,578 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleOptimizing Mobile Edge Computing Efficiency through Multidimensional Generative Adversarial NetworkAnitha Premkumar, Sowmya Vemagal Lakshminarayana, Shankar Rajagopal et al.Big data Processing and the IoT have recently gained popularity as study topics in MEC and thorough research is sought for well-informed decisions. Mobile edge equipment, such as base stations, routers, and edge servers, usually have limited processing capabilities compared to traditional data centers. According to this perspective, this research constructs MEC using Intelligent Outlier Detection with a Multidimensional Generative … …Journal of Computer Science, Vol. 21, Issue 2 · 18 Jan 2025 · 4,686 accessesView PDFCite
Review ArticleOpen accessIn the keywordsHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Intrusion Detection Framework for MEC-Enabled IoT NetworksRofaida Tawfik, Abdelfattah Hegazy, Hesham Dahshan, Ahmed Gaber AbuabdallahMobile Edge Computing (MEC) has emerged as a promising paradigm for supporting latency-sensitive Internet of Things (IoT) applications by bringing computational resources closer to data sources. However, the distributed nature of MEC environments increases exposure to network-based security threats, particularly network intrusions that can impact both system reliability and task offloading efficiency. This paper proposes a security-aware framework that integrates … …Journal of Computer Science, Vol. 22, Issue 4 · 1 Apr 2026 · 1,921 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEfficient Handling of Medical Data Classification in Cloud-Edge Network using Optimization AlgorithmS. S. Saranya, N. Sabiyath FatimaNowadays, a cloud-edge computing framework with IoT offers different medicinal facilities by classifying a massive amount of patients’ health data through a Deep Neural Network. But, how to optimize task scheduling while carrying multiple tasks from multiple edge devices in real-time was still challenging. This article introduces a cooperative cloud-edge computing structure to effectively perform the fuzzy DNN classification into … …Journal of Computer Science, Vol. 17, Issue 11 · 30 Nov 2021 · 6,480 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Edge Efficient and Lightweight Hybrid CNN Vision Transformer Network With CBAM for IoT Based Plant Disease DetectionNyabeye Pangop Doris-Khöler, Kengni Ngangmo OlgaDetecting crop disease early enough to act on it remains a bottleneck for smallholder and precision farming alike, particularly when diagnosis depends on manual inspection or lab analysis that cannot keep pace with an outbreak. We present AgriViTNet, a compact CNN-Vision Transformer hybrid built for exactly this constraint: It extracts local texture cues through convolution, relates them across the whole … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 578 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPrivacy-Preserving Deep Federated Learning on the Edge Using Homomorphic Encryption and Secure Multiparty ComputationNoman Aasif Gudur, Mohamed El-Dosuky, Sherif KamelThe increasing volume of consumer data necessitates reliable edge devices for personalized user experiences. Federated Learning (FL) offers a state-of-the-art approach to decentralized machine learning by leveraging data distributed across multiple client devices. However, user data privacy remains vulnerable to corruption through feature heterogeneity and malicious attacks. While several privacy-preserving techniques have been previously implemented, they suffer from implementation constraints … …Journal of Computer Science, Vol. 21, Issue 11 · 21 Dec 2025 · 4,381 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRoute Optimization using Hybrid GRU Learning Model for SDN and Edge-Based VANET TopologySavitha Kumar, Chandrasekar ChinnasamyIntelligent Transportation System (ITS) offersoutstanding features, including security applications and emergency alerts.Unfortunately, ITS limits traffic control services, adaptability, andadjustability due to the traffic volume. Hence, expanding the standard VehicularAd hoc Networks (VANET) framework is a requirement. As a result, in the latestdays, the concept of Software-Defined Networking based Vehicular Ad hocNetworks (SDN-VANETs) has drawn considerable attention, creating VANETssmarter. The SDN-VANETs … …Journal of Computer Science, Vol. 18, Issue 8 · 26 Aug 2022 · 6,160 accessesView PDFCite
Review ArticleOpen accessIn the keywordsIntegrating Data Mining Methods Across all Domains of a Smart CityRushit Dave, Nuo Xu, Simon Arneberg et al.As modern cities continue to develop, smart devices are being used to improve citizens’ lives. As these devices become more sophisticated, the amount of information that they collect increases. A Smart City is a city that uses a large amount of generated data to constantly improve the services offered to the people that live there. Data mining techniques can be … …Journal of Computer Science, Vol. 18, Issue 5 · 30 May 2022 · 7,075 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Fog Resource Provisioning and Resource Allocation using MKFCM and FPANagarjun E, Dharamendra Chouhan, Dilip Kumar SMThe expansion of Internet of Things (IoT) deployments has motivated the Fog Computing (FC) paradigm, which brings mobile-edge and cloud resources together under a single model. Allocating and provisioning application tasks across such environments poses challenges due to constrained resource capabilities, heterogeneity, mobility, network hierarchy, and unpredictability. This paper addresses the need for additional computing devices that prioritize delay-sensitive applications … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 462 accessesView PDFCite