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09/13/2023
DNNShifter: An Efficient DNN Pruning System for Edge Computing
Deep neural networks (DNNs) underpin many machine learning applications....
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04/11/2023
Communication Efficient DNN Partitioning-based Federated Learning
Efficiently running federated learning (FL) on resource-constrained devi...
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10/28/2022
ROMA: Run-Time Object Detection To Maximize Real-Time Accuracy
This paper analyzes the effects of dynamically varying video contents an...
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08/18/2022
FedComm: Understanding Communication Protocols for Edge-based Federated Learning
Federated learning (FL) trains machine learning (ML) models on devices u...
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11/27/2021
Roadmap for Edge AI: A Dagstuhl Perspective
Based on the collective input of Dagstuhl Seminar (21342), this paper pr...
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11/09/2021
QUDOS: Quorum-Based Cloud-Edge Distributed DNNs for Security Enhanced Industry 4.0
Distributed machine learning algorithms that employ Deep Neural Networks...
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11/02/2021
FedFly: Towards Migration in Edge-based Distributed Federated Learning
Federated learning (FL) is a privacy-preserving distributed machine lear...
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07/09/2021
FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning
Applying Federated Learning (FL) on Internet-of-Things devices is necess...
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06/29/2021
NEUKONFIG: Reducing Edge Service Downtime When Repartitioning DNNs
Deep Neural Networks (DNNs) may be partitioned across the edge and the c...
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06/23/2021
Revisiting the Arguments for Edge Computing Research
This article argues that low latency, high bandwidth, device proliferati...
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05/18/2021
TOD: Transprecise Object Detection to Maximise Real-Time Accuracy on the Edge
Real-time video analytics on the edge is challenging as the computationa...
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05/05/2021
ScissionLite: Accelerating Distributed Deep Neural Networks Using Transfer Layer
Industrial Internet of Things (IIoT) applications can benefit from lever...
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03/08/2021
AVEC: Accelerator Virtualization in Cloud-Edge Computing for Deep Learning Libraries
Edge computing offers the distinct advantage of harnessing compute capab...
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08/08/2020
Scission: Context-aware and Performance-driven Edge-based Distributed Deep Neural Networks
Partitioning and distributing deep neural networks (DNNs) across end-dev...
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08/04/2020
A Case For Adaptive Deep Neural Networks in Edge Computing
Edge computing offers an additional layer of compute infrastructure clos...
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05/30/2020
WattsApp: Power-Aware Container Scheduling
Containers are becoming a popular workload deployment mechanism in moder...
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04/24/2020
A Survey on Edge Benchmarking
Edge computing is the next Internet frontier that will leverage computin...
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03/17/2020
Cross Architectural Power Modelling
Existing power modelling research focuses on the model rather than the p...
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02/12/2020
Modelling Fog Offloading Performance
Fog computing has emerged as a computing paradigm aimed at addressing th...
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01/24/2020
Context-aware Distribution of Fog Applications Using Deep Reinforcement Learning
Fog computing is an emerging paradigm that aims to meet the increasing c...
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01/24/2020
Priority-based Fair Scheduling in Edge Computing
Scheduling is important in Edge computing. In contrast to the Cloud, Edg...
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09/11/2019
Performance Estimation of Container-Based Cloud-to-Fog Offloading
Fog computing offloads latency critical application services running on ...
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07/25/2019
DeFog: Fog Computing Benchmarks
Fog computing envisions that deploying services of an application across...
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02/10/2019
Cloud Futurology
The Cloud has become integral to most Internet-based applications and us...
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12/04/2018
Realizing Edge Marketplaces: Challenges and Opportunities
The edge of the network has the potential to host services for supportin...
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10/14/2018
Accelerator Virtualization in Fog Computing: Moving From the Cloud to the Edge
Hardware accelerators are available on the Cloud for enhanced analytics....
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09/30/2018
Resource Management in Fog/Edge Computing: A Survey
Contrary to using distant and centralized cloud data center resources, e...
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09/19/2018
DYVERSE: DYnamic VERtical Scaling in Multi-tenant Edge Environments
Multi-tenancy in resource-constrained environments is a key challenge in...
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03/14/2018
Addressing the Challenges in Federating Edge Resources
This book chapter considers how Edge deployments can be brought to bear ...
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12/12/2017
Intra-node Memory Safe GPU Co-Scheduling
GPUs in High-Performance Computing systems remain under-utilised due to ...
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11/24/2017
Plug and Play Bench: Simplifying Big Data Benchmarking Using Containers
The recent boom of big data, coupled with the challenges of its processi...
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11/24/2017
A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade
The Cloud computing paradigm has revolutionized the computer science hor...
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11/24/2017
A Survey and Taxonomy of Resource Optimisation for Executing Bag-of-Task Applications on Public Clouds
Cloud computing has been widely adopted due to the flexibility in resour...
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10/27/2017
Power Modelling for Heterogeneous Cloud-Edge Data Centers
Existing power modelling research focuses not on the method used for dev...
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10/27/2017