Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing by Xin Li (51274)

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Incentive-Vacation Queueing in Extreme Edge Computing: An Analytical Reward-Based Framework by Sherif B. Azmy (21633329)

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Incentive-Vacation Queueing for Edge Crowd Computing by Sherif B. Azmy (21633329)

“…Edge crowd computing (ECC) is an orchestrated sharing economy model within XEC that uses idle resources on userowned devices for service provision, compensating owners. …”

PFDI: a precise fruit disease identification model based on context data fusion with faster-CNN in edge computing environment by Poonam Dhiman (12889038)

“…This research examines and explores four different diseases of Citrus fruits using CNN deep learning models to be adopted as edge computing solutions. …”

Crowd counting at the edge using weighted knowledge distillation by Muhammad Asif Khan (7367468)

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…<p dir="ltr">In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. …”

Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

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Efficient real-time license plate recognition using deep learning on edge devices by Fedi Sonnara (22928650)

Big Data Analytics from the Rich Cloud to the Frugal Edge by M. Awaysheh, Feras

“…With the advent of edge computing, that traditional deployment model shifted closer to the data sources at the network’s edge. …”
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Collaborative Federated Learning for Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge by Adnan Qayyum (16875936)

“…In this paper, we leverage the capabilities of edge computing in medicine by evaluating the potential of intelligent processing of clinical data at the edge. …”

Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

Edge-Optimized Deep Learning Architectures for Classification of Agricultural Insects with Mobile Deployment by Akhtar, Muhammad Hannan

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A provable secure and lightweight ECC-based authenticated key agreement scheme for edge computing infrastructure in smart grid by Cong Wang (107450)

“…The security properties are also evaluated by using the Canetti and Krawczyk (CK) adversary model. The performance simulation results denotes that the proposed scheme not only owns stronger security functions but also improves computation efficiency by 24.5% on average than other four schemes. …”

A Formal Assisted Approach for Modeling and Testing Security Attacks in IoT Edge Devices by Bhanpurawala, Alifiya

“…A Master of Science thesis in Computer Engineering by Alifiya Bhanpurawala entitled, “A Formal Assisted Approach for Modeling and Testing Security Attacks in IoT Edge Devices”, submitted in November 2023. …”
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An IoT System Using Deep Learning to Classify Camera Trap Images on the Edge by Zaulkernan, Imran

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Collaborative hierarchical caching and transcoding in edge network with CE-D2D communication by Emna Baccour (16896366)

“…<p dir="ltr">To support multimedia applications, Mobile Edge Computing (MEC) servers offer storage and computing capacities to handle videos close to end-users. …”

HALOGrid—HyperAdaptive long short term memory model with intelligent grid optimization by Kamran Ahmad Awan (23643430)

Reputation-Aware Multi-Agent DRL for Secure Hierarchical Federated Learning in IoT by Noora Mohammed Al-Maslamani (17541798)

Subjects: “…Information and computing sciences…”

Novel Distribution-Aware and Learning-Based Dynamic Scheme for Efficient User Incentivization in Edge Sensing Systems by Omar Naserallah (22155367)

“…<p dir="ltr">Edge sensing (ES) systems employ users’ owned smart devices with built-in sensors to gather data from users’ surrounding environments and use their processors to carry out edge computing tasks. …”

UAV-assisted Multi-tier Computing Framework for IoT Networks by Tout, Abeer

“…This thesis leverages a hierarchical computational model where IoT devices offload their computational tasks to a number of unmanned aerial vehicles (UAVs) that can be deployed in a way to establish strong Line-of-Sight (LoS) links. …”
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