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A Survey on Edge Performance Benchmarking
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpe.4257openalex-snapshot
RIoTBench: An IoT benchmark for distributed stream processing systems
inferredcites →https://doi.org/10.1002/cpe.728openalex-snapshot
The LINPACK Benchmark: past, present and future
inferredcites →https://doi.org/10.1002/spe.2509openalex-snapshot
iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments
inferredcites →https://doi.org/10.1007/978-0-387-78446-5_2openalex-snapshot
Benchmarking Grid Applications
inferredcites →https://doi.org/10.1007/978-3-030-32813-9_4openalex-snapshot
AIoT Bench: Towards Comprehensive Benchmarking Mobile and Embedded Device Intelligence
inferredcites →https://doi.org/10.1007/978-3-319-15350-6_1openalex-snapshot
Introducing TPCx-HS: The First Industry Standard for Benchmarking Big Data Systems
inferredcites →https://doi.org/10.1007/978-3-319-31409-9_10openalex-snapshot
Profiling the Performance of Virtualized Databases with the TPCx-V Benchmark
inferredcites →https://doi.org/10.1007/978-3-540-78849-2_21openalex-snapshot
CROWNBench: A Grid Performance Testing System Using Customizable Synthetic Workload
inferredcites →https://doi.org/10.1007/978-3-642-25707-0_9openalex-snapshot
SuperQuant Financial Benchmark Suite for Performance Analysis of Grid Middlewares
inferredcites →https://doi.org/10.1007/s00521-018-3761-1openalex-snapshot
A survey of FPGA-based accelerators for convolutional neural networks
inferredcites →https://doi.org/10.1007/s00521-019-04095-yopenalex-snapshot
Big data analytics for preventive medicine
inferredcites →https://doi.org/10.1007/s11227-016-1872-yopenalex-snapshot
Application-aware cloudlet selection for computation offloading in multi-cloudlet environment
inferredcites →https://doi.org/10.1007/s11704-012-2118-7openalex-snapshot
CloudRank-D: benchmarking and ranking cloud computing systems for data processing applications
inferredcites →https://doi.org/10.1007/s11761-017-0219-8openalex-snapshot
Optimized IoT service placement in the fog
inferredcites →https://doi.org/10.1016/j.adhoc.2011.08.005openalex-snapshot
A spatial correlation aware algorithm to perform efficient data collection in wireless sensor networks
inferredcites →https://doi.org/10.1016/j.future.2013.07.013openalex-snapshot
Tibidabo: Making the case for an ARM-based HPC system
inferredcites →https://doi.org/10.1016/j.future.2017.09.020openalex-snapshot
Next generation cloud computing: New trends and research directions
inferredcites →https://doi.org/10.1016/j.future.2020.02.043openalex-snapshot
DYVERSE: DYnamic VERtical Scaling in multi-tenant Edge environments
inferredcites →https://doi.org/10.1108/ir.1999.04926fae.001openalex-snapshot
Lecture Notes in Computer Science 1205
inferredcites →https://doi.org/10.1109/99.486757openalex-snapshot
Benchmarking with real industrial applications: the SPEC High-Performance Group
inferredcites →https://doi.org/10.1109/access.2017.2704444openalex-snapshot
Virtualization on Internet of Things Edge Devices With Container Technologies: A Performance Evaluation
inferredcites →https://doi.org/10.1109/access.2017.2710056openalex-snapshot
Energy-Saving Offloading by Jointly Allocating Radio and Computational Resources for Mobile Edge Computing
inferredcites →https://doi.org/10.1109/cvpr.1993openalex-snapshot
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/eucnc.2017.7980775openalex-snapshot
The ADRENALINE testbed: An SDN/NFV packet/optical transport network and edge/core cloud platform for end-to-end 5G and IoT services
inferredcites →https://doi.org/10.1109/hpdc.2006.1652128openalex-snapshot
Proceedings of the 15th IEEE International Symposium on High Performance Distributed Computing
inferredcites →https://doi.org/10.1109/iccd.2000openalex-snapshot
Proceedings 2000 International Conference on Computer Design
inferredcites →https://doi.org/10.1109/icws.2004openalex-snapshot
Proceedings. IEEE International Conference on Web Services, 2004.
inferredcites →https://doi.org/10.1109/iiswc.2005.1525988openalex-snapshot
Proceedings of the 2005 IEEE International Symposium on Workload Characterization
inferredcites →https://doi.org/10.1109/ipdps.2006.1639600openalex-snapshot
Making a case for a Green500 list
inferredcites →https://doi.org/10.1109/jiot.2016.2579198openalex-snapshot
Edge Computing: Vision and Challenges
inferredcites →https://doi.org/10.1109/jiot.2018.2849859openalex-snapshot
HERMIT: A Benchmark Suite for the Internet of Medical Things
inferredcites →https://doi.org/10.1109/jiot.2018.2875715openalex-snapshot
Dynamic Computation Offloading in Edge Computing for Internet of Things
inferredcites →https://doi.org/10.1109/lca.2016.2597818openalex-snapshot
Cloud Server Benchmark Suite for Evaluating New Hardware Architectures
inferredcites →https://doi.org/10.1109/mcc.2018.064181118openalex-snapshot
Accelerator Virtualization in Fog Computing: Moving from the Cloud to the Edge
inferredcites →https://doi.org/10.1109/mcom.2018.1700793openalex-snapshot
Experimental Testbed for Edge Computing in Fiber-Wireless Broadband Access Networks
inferredcites →https://doi.org/10.1109/mic.2020.2979161openalex-snapshot
Fog Computing as Privacy Enabler
inferredcites →https://doi.org/10.1109/mm.2015.4openalex-snapshot
The Movidius Myriad Architecture's Potential for Scientific Computing
inferredcites →https://doi.org/10.1109/mnet.2018.1700145openalex-snapshot
ThriftyEdge: Resource-Efficient Edge Computing for Intelligent IoT Applications
inferredcites →https://doi.org/10.1109/mnet.2018.1700175openalex-snapshot
Consolidate IoT Edge Computing with Lightweight Virtualization
inferredcites →https://doi.org/10.1109/mprv.2009.82openalex-snapshot
The Case for VM-Based Cloudlets in Mobile Computing
inferredcites →https://doi.org/10.1109/mspec.2019.8701189openalex-snapshot
Taking AI to the edge: Google's TPU now comes in a maker-friendly package
inferredcites →https://doi.org/10.1109/tcc.2016.2603476openalex-snapshot
Cloud Benchmarking for Maximising Performance of Scientific Applications
inferredcites →https://doi.org/10.1109/tcc.2019.2898657openalex-snapshot
Energy Efficient Dynamic Offloading in Mobile Edge Computing for Internet of Things
inferredcites →https://doi.org/10.1109/tii.2019.2899679openalex-snapshot
A Hybrid Computing Solution and Resource Scheduling Strategy for Edge Computing in Smart Manufacturing
inferredcites →https://doi.org/10.1109/tnet.2015.2487344openalex-snapshot
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
inferredcites →https://doi.org/10.1109/tnsm.2019.2901346openalex-snapshot
Fuzzy Workload Orchestration for Edge Computing
inferredcites →https://doi.org/10.1109/tpds.2011.66openalex-snapshot
Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing
inferredcites →https://doi.org/10.1109/tsc.2017.2753775openalex-snapshot
ENORM: A Framework For Edge NOde Resource Management
inferredcites →https://doi.org/10.1109/tsipn.2015.2448520openalex-snapshot
Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing
inferredcites →https://doi.org/10.1109/tvt.2019.2917890openalex-snapshot
Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks
inferredcites →https://doi.org/10.1109/twc.2016.2633522openalex-snapshot
Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading
inferredcites →https://doi.org/10.1111/j.1468-2273.1951.tb00568.xopenalex-snapshot
THE TECHNICAL UNIVERSITY OF DELFT
inferredcites →https://doi.org/10.1145/1168857openalex-snapshot
Proceedings of the 12th international conference on Architectural support for programming languages and operating systems
inferredcites →https://doi.org/10.1145/1735688openalex-snapshot
Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units
inferredcites →https://doi.org/10.1145/1807128openalex-snapshot
Proceedings of the 1st ACM symposium on Cloud computing
inferredcites →https://doi.org/10.1145/2188286openalex-snapshot
Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
inferredcites →https://doi.org/10.1145/2873587openalex-snapshot
Proceedings of the 17th International Workshop on Mobile Computing Systems and Applications
inferredcites →https://doi.org/10.1145/3102980openalex-snapshot
Proceedings of the 16th Workshop on Hot Topics in Operating Systems
inferredcites →https://doi.org/10.1145/3205289openalex-snapshot
Proceedings of the 2018 International Conference on Supercomputing
inferredcites →https://doi.org/10.1145/3239565openalex-snapshot
A Dynamic Service Migration Mechanism in Edge Cognitive Computing
inferredcites →https://doi.org/10.1145/3286719.3286720openalex-snapshot
Supporting the Evaluation of Fog-based IoT Applications During the Design Phase
inferredcites →https://doi.org/10.1145/3318216openalex-snapshot
Proceedings of the 4th ACM/IEEE Symposium on Edge Computing
inferredcites →https://doi.org/10.1145/3326066openalex-snapshot
Resource Management in Fog/Edge Computing
inferredcites →https://doi.org/10.1145/3347514openalex-snapshot
An Incentive Mechanism for Crowdsourcing Systems with Network Effects
inferredcites →https://doi.org/10.1145/3355369openalex-snapshot
Proceedings of the Internet Measurement Conference
inferredcites →https://doi.org/10.1145/3366623openalex-snapshot
Proceedings of the 5th International Workshop on Serverless Computing
inferredcites →https://doi.org/10.1145/3382734openalex-snapshot
Proceedings of the 39th Symposium on Principles of Distributed Computing
inferredcites →https://doi.org/10.1145/3605098openalex-snapshot
Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing
inferredcites →https://doi.org/10.1145/582034openalex-snapshot
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
inferredcites →https://doi.org/10.1155/2019/7218758openalex-snapshot
An FPGA-Based Hardware Accelerator for CNNs Using On-Chip Memories Only: Design and Benchmarking with Intel Movidius Neural Compute Stick
inferredcites →https://doi.org/10.1186/2192-113x-2-6openalex-snapshot
Fair Benchmarking for Cloud Computing systems
inferredcites →https://doi.org/10.48550/arxiv.1906.01878openalex-snapshot
pCAMP: Performance Comparison of Machine Learning Packages on the Edges
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/spe.3383openalex-snapshot
On Optimizing Resources for Real‐Time End‐to‐End Machine Learning in Heterogeneous Edges
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Artificial Intelligence of Things: Architectures, Applications, and Challenges
inferred← citeshttps://doi.org/10.1007/978-3-031-58388-9_5openalex-snapshot
Service Provisioning at the Edge: An AI Approach Based on Policies
inferred← citeshttps://doi.org/10.1007/978-3-031-80949-1_9openalex-snapshot
Machine Learning-Driven Task Offloading for Smart Vehicular Edge Computing: Taxonomy, Issues, and Opportunities
inferred← citeshttps://doi.org/10.1007/978-3-031-93106-2_16openalex-snapshot
Review of Key Factors in Task Offloading Decision-Making in Heterogeneous Vehicular Networks
inferred← citeshttps://doi.org/10.1007/978-3-032-26908-9_10openalex-snapshot
Sentryegde: an Automated Multi- Tenant Benchmarking for the Edge Devices
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An experimental study of edge deployment strategies for cryptocurrency analytics workloads
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Edge deep learning in computer vision and medical diagnostics: a comprehensive survey
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Robust Federated Learning for execution time-based device model identification under label-flipping attack
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Local Cloud-Based Collaborative Learning vs Other IIoT Decentralized AI Solutions: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1007/s11227-024-06605-9openalex-snapshot
Balanced segmentation of CNNs for multi-TPU inference
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Throughput impact of software multithreading for deep-learning inference on the AMD Kria KV260
inferred← citeshttps://doi.org/10.1016/j.comnet.2025.111858openalex-snapshot
TrafficT5: Multi-stage self-correcting framework for traffic generation
inferred← citeshttps://doi.org/10.1016/j.future.2025.107914openalex-snapshot
MicroFaaS: Adaptive serverless computing for Internet of Things
inferred← citeshttps://doi.org/10.1016/j.future.2025.108176openalex-snapshot
Performance analysis of microVMs and containers for edge computing: A focus on file and network I/O
inferred← citeshttps://doi.org/10.1016/j.hcc.2024.100212openalex-snapshot
Data cube-based storage optimization for resource-constrained edge computing
inferred← citeshttps://doi.org/10.1016/j.iot.2023.100764openalex-snapshot
LwHBench: A low-level hardware component benchmark and dataset for Single Board Computers
inferred← citeshttps://doi.org/10.1016/j.jnca.2022.103558openalex-snapshot
When machine learning meets Network Management and Orchestration in Edge-based networking paradigms
inferred← citeshttps://doi.org/10.1109/access.2023.3234761openalex-snapshot
Enabling All In-Edge Deep Learning: A Literature Review
inferred← citeshttps://doi.org/10.1109/access.2023.3267277openalex-snapshot
EVMTracer: Dynamic Analysis of the Parallelization and Redundancy Potential in the Ethereum Virtual Machine
inferred← citeshttps://doi.org/10.1109/access.2025.3602390openalex-snapshot
Toward Secure, Trustworthy, and Sustainable Edge Computing for Smart Cities: Innovative Strategies and Future Prospects
inferred← citeshttps://doi.org/10.1109/access.2026.3734116openalex-snapshot
Performance and Sustainability of Edge AI Accelerator Technologies: In-Memory AIPU Versus TPU, NPU, and GPU SoC
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11402502openalex-snapshot
Predicting Machine Learning Training Costs with MLPerf Benchmarks
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Performance Evaluation of AI Algorithms on Heterogeneous Edge Devices for Manufacturing
inferred← citeshttps://doi.org/10.1109/ccgrid54584.2022.00023openalex-snapshot
Pushing Serverless to the Edge with WebAssembly Runtimes
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The SPEC-RG Reference Architecture for The Compute Continuum
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Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
inferred← citeshttps://doi.org/10.1109/dcoss-iot61029.2024.00032openalex-snapshot
Balancing Energy Efficiency and Portability: Assessing Domain-Specific Languages in Edge Platforms
inferred← citeshttps://doi.org/10.1109/edge55608.2022.00016openalex-snapshot
ECBA-MLI: Edge Computing Benchmark Architecture for Machine Learning Inference
inferred← citeshttps://doi.org/10.1109/edge55608.2022.00024openalex-snapshot
EdgeFaaSBench: Benchmarking Edge Devices Using Serverless Computing
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A Survey of Faults and Fault-Injection Techniques in Edge Computing Systems
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Optimizing Heterogeneous Task Allocation for Edge Compute Micro Clusters Using PSO Metaheuristic
inferred← citeshttps://doi.org/10.1109/i2mtc60896.2024.10560978openalex-snapshot
Deep Neural Network Representation for Explainable Machine Learning Algorithms: A Method for Hardware Acceleration
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Towards a Benchmark for Fog Data Processing
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An Intellectual Diffused Configuration for High-Level Edge Network Elasticity
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Hybridization of Tabu Search and Grey Wolf Optimizer for Improved Workflow Scheduling and Optimization of Resources in Edge Computing
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On-Device AI for Maritime Communication: Trends, Challenges, and a Simulation-Only Case Study
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A Game Theoretical Balancing Approach for Offloaded Tasks in Edge Datacenters
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Edge Workload Trace Gathering and Analysis for Benchmarking
inferred← citeshttps://doi.org/10.1109/icps59941.2024.10640034openalex-snapshot
Sparse Measurement Algorithm Execution Time Prediction on Heterogeneous Edge Devices for Early Stage Software-Hardware Matching
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Integrating Digital Twins into the System Architecture of Brownfield Filtration Plants
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A Survey on Intelligent Attack Mitigation and Latency Optimization in High-Speed Edge Networks using Deep Learning and Bio-Inspired Algorithms
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Towards a Quantitative Time Analysis and Decision Support for the Deployment of AI-Algorithms in Distributed Cyber-Physical Production Systems
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A Latency Score based Benchmarking Framework integrating Quantum Computing in Edge-Cloud Environments
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Execution Time Oriented Design of an Adaptive Controller for Mobile Machines
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Measurement Methods for Software Execution Time on Heterogeneous Edge Devices
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BenchPilot: Repeatable & Reproducible Benchmarking for Edge Micro-DCs
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Worker Resource Characterization Under Dynamic Usage in Multi-access Edge Computing
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Intelligent Packet Processing for Performant Containers in IoT
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Performance Evaluation of Modern GPU Accelerator-Based Edge Systems: A Holistic Approach
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MicroVM on Edge: Is It Ready for Prime Time?
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The Necessary Shift: Toward a Sufficient Edge Computing
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Improving inference time in multi-TPU systems with profiled model segmentation
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Estimating Performances of Application Deployment on Distributed IoT-Edge-Cloud Infrastructures
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Performance Analysis of Lightweight Container Orchestration Platforms for Edge-Based IoT Applications
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Real-Time Load-Aware Resource Allocation in Cloud Systems: A Comparative Study of Adaptive and Threshold-Based Algorithm
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Continuum: Automate Infrastructure Deployment and Benchmarking in the Compute Continuum
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Proceedings of the 6th International Workshop on Edge Systems, Analytics and Networking
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Bang for the Buck: Evaluating the cost-effectiveness of Heterogeneous Edge Platforms for Neural Network Workloads
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SegaNet: An Advanced IoT Cloud Gateway for Performant and Priority-Oriented Message Delivery
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Providing Realtime Support for Containerized Edge Services
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Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly
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FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems
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Artificial Intelligence on the Shop Floor: A Comprehensive Review of Literature
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Comparative Study Between in-Memory Database and Hard Drive Database: An Application to Data Analytics
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Orchestrating a Resource-aware Edge
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A Benchmarking Framework for Hybrid Quantum–Classical Edge-Cloud Computing Systems
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Neural Network Implementation for Fire Detection in Critical Infrastructures: A Comparative Analysis on Embedded Edge Devices
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Intelligent Edge Computing and Machine Learning: A Survey of Optimization and Applications
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Analyzing Threats and Attacks in Edge Data Analytics within IoT Environments
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An Evaluation of Modern Accelerator-Based Edge Devices for Object Detection Applications
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Programming for High-Performance Computing on Edge Accelerators
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Evaluation of GPU-Accelerated Edge Platforms for Stochastic Simulations: Performance and Energy Efficiency Analysis
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Benchmarking Deep Learning for On-Board Space Applications
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TLS Protocol Analysis Using IoTST—An IoT Benchmark Based on Scheduler Traces
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Multi-Access Edge Computing (MEC) Based on MIMO: A Survey
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A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision
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A Survey on Reduction of Energy Consumption in Fog Networks—Communications and Computations
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A Study of Mobile Edge Computing for IOT
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Charting the Benchmarking Landscape – A Survey of Benchmarks for Modern Memory Architectures
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