The paper presents a framework for resource allocation in a mobile edge computing (MEC) system to provide customized virtual reality (VR) services to heterogeneous users. It introduces a quality of…
Continue readingThe research presents a three-stage training model for intrusion detection in edge computing devices. The model uses advanced deep learning techniques and is designed to work effectively within resource-constrained devices….
Continue readingThe paper presents STarEdgeChain, a system for secure and privacy-aware targeted message dissemination in IoT. The system uses a permissioned blockchain assisted edge computing to expedite a single signcrypted message…
Continue readingThe paper discusses the security and privacy aspects of Mobile Edge Computing (MEC) from an Artificial Intelligence (AI) perspective. MEC is a new computing paradigm that moves cloud computing to…
Continue readingThe paper conducts an in-depth exploration of Web 3.0, focusing on blockchain, artificial intelligence, and edge computing. The authors summarize the internet evolution and provide an overview of these three…
Continue readingThe article discusses a consensus-based resource scheduling strategy for multi-robot tasks. It proposes the integration of edge-computing into multi-robot collaborative scheduling to maximize resource utilization for complex tasks. The approach…
Continue readingThe article presents FedPEAT, a system that merges federated learning, parameter-efficient fine-tuning, and emulator-assisted tuning for AI foundation models with mobile edge computing. The system is designed to address challenges…
Continue readingThe research introduces a novel framework, FedPEAT, which converges Federated Learning, Parameter-Efficient Fine Tuning, and Emulator Assisted Tuning. The framework is designed to address the challenges in deploying and fine-tuning…
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