Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 19 of 19 for “"Edge Cloud"”.
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Machine Learning driven Resource Allocation in Edge Cloud
… remotely by offloading them to the back-end cloud (BC) and utilizing its abundant compute resources. However, the long distance between a mobile/IoT device and the BC causes huge network delay, thus, deteriorating the user experience of real-time applications. Edge-cloud (EC) and beyond 5G …
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ASSURANCE-AWARE 5G EDGE-CLOUD ARCHITECTURES FOR INTENSIVE DATA ANALYTICS
… di continuum che comprende infrastrutture Edge e Cloud. In questo scenario, le infrastrutture utilizzate per il deployment dei servizi svolgono un ruolo cruciale nel fornire o supportare le proprietà non funzionali dell'applicazione. Ad esempio, la bassa latenza può essere ottenuta …
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Adaptive Effort Classifiers: A System Design For Partitioned Edge/Cloud Inference
… across the spectrum of computing devices from edge/Internet-of-Things (IoT) devices to data centers and the cloud. However, DNNs incur high computational cost (compute operations, memory footprint and bandwidth),which far outstrip the capabilities of modern computing platforms. Therefore …
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Armada: A Robust Latency-Sensitive Edge Cloud in Heterogeneous Edge-Dense Environments
Edge computing has enabled a large set of emerging edge applications by exploiting data proximity and offloading latency-sensitive and computation-intensive workloads to nearby edge servers. However, supporting edge application users at scale in wide-area environments poses challenges due to …
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Utility-driven optimization and placement framework for Visual IoT analytics over edge-cloud environments
… This happens in parallel with advances in Edge computing and Serverless computing. Edge computing, has emerged to allow analyzing visual IoT data closer to where it is generated, and hence avoiding sending vast amounts of visual data streams to be analyzed in one remote location. On the …
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Real-time data operations and causal security analysis for edge-cloud-based Smart Grid infrastructure
… in Smart Grid. Taking an integrated approach of edge-cloud design, real-time data operations, and causal security analysis, the proposed frameworks enhance security protection by anomaly detection and managing as well as causal reasoning of alerts, and reduce traffic volume by online data …
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An adaptive placement framework for efficient near-data stream processing over data source-edge-cloud systems
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01
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Dossier: Distributed operating system and infrastructure for scientific data management
… old scientific instruments and its advanced cloud-based infrastructure. In this thesis, we aim to address the above diversity challenges by taking a holistic approach in designing a distributed operating system and infrastructure for scientific data management, named DOSSIER. At the core of …
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A framework for proactive fault tolerance in cloud-IoT applications
… Internet of Things (IoT) devices with the cloud has several benefits, including expanding local IoT resources and improving cloud-IoT application performance. Cloud computing can benefit from IoT devices and applications by extending its scope to include real-world surroundings. On the …
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GICEDCAM: A Geospatial Internet of Things Framework for Complex Event Detection in Camera Streams
… of Smart Cameras (IoSC) architecture that uses edge–cloud collaboration and overlapping camera views to compensate for missed detections. By integrating simple events detected from multiple viewpoints, the IoSC framework significantly reduces false negatives and improves complex-event …
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Building interactive distributed processing applications at a global scale
… Microsoft) extends processing to the emerging edge. Integrated with Azure, Steel dynamically optimizes placement and data-motion across the entire edge-cloud environment. Finally, we have designed FreeFlow, a high performance networking mechanisms for containers. Using the container placement, …
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Multi-server federated learning in vehicular edge computing
… and roadside units (RSUs) host FL servers at the edge. However, practical deployments face multiple challenges: highly non-IID and noisy data across vehicles, heterogeneous computation and communication resources, private training costs, intermittent connectivity, and the need to coordinate …
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Big data toward vehicle health monitoring system: an engine health perspective
… for future studies in federated learning, edge-cloud deployment, and multimodal sensor fusion, offering scalable, low-cost, and inclusive solutions for modern transportation systems. This research advances both practical and scholarly understanding of intelligent VHMS, demonstrating that …
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Intelligent orchestration of computation and networking for drone swarm applications
… This requires sensor localization and access to edge computation and networking resources to provide environmental situational awareness in the applications. Orchestration of the computation and networking resources in practice are performed in isolation, and do not sufficiently account for …
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Robust planning and scheduling using column generation
… We validate our approach on a realistic Mobile Edge Cloud (MEC) network architecture and show that our model can find near optimal solutions to practical sized problems within a reasonable time. The second problem we address is a scheduling problem called Strong Controllability (SC). SC of …
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An open vendor agnostic fog computing framework for mission critical and data dense applications
… of these applications emphasize mandatory cloud connectivity. However, this is not feasible in many real-world situations particularly where data dense and mission critical applications with stringent requirements are concerned. Cloud computing offers unlimited on-demand computing, storage …
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Online Optimization for Edge Computing under Uncertainty in Wireless Networks
Edge computing is an emerging technology that can overcome the limitations of centralized cloud computing by enabling distributed, low-latency computation at a network edge. Particularly, in edge computing, some of the cloud's functionalities such as storage, processing, and computing are migrated …
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Machine Learning Approach for Resource Allocation in Mobile Edge Computing
<p>Mobile Edge Computing (MEC) is recognized as a pivotal technology supporting cloud computing and innovative services at the network edge, offering significant reductions in system delay and mitigating network traffic congestion. It supports latency-sensitive applications like Augmented Reality …
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Ad-hoc formation of edge clouds over heterogeneous non-dedicated resources
… existent en aquest espai. El concepte d'Ad-Hoc Edge Clouds proposa la creació d'ecosistemes dinàmics de dispositius d'IoT Edge de manera distribuïda i descentralitzada. Les novetats principals deriven de: (1) la consideració dels dispositius d'IoT Edge com a entorns d'execució vàlids, (2) el fet …