EDGE COMPUTING IEEE PAPER 2022



Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is expected to improve response times and save bandwidth
Edge computing is a form of computing that is done on site or near a particular data source, minimizing the need for data to be processed in a remote data center.
Edge computing is already in use all around us from the wearable on your wrist to the computers parsing intersection traffic flow. Other examples include smart utility grid analysis, safety monitoring of oil rigs, streaming video optimization, and drone-enabled crop management.
Edge computing is used in the manufacturing sector to monitor manufacturing processes and apply machine learning and real-time analytics to improve product qualities and detect production errors. It also supports the environmental sensors to be incorporated in manufacturing plants.








Retention-aware container caching for serverless edge computing
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We consider an edge computing system consisting of a number of edge nodes dispersed in multiple geographical zones, serving different IoT services. Here, the zone is an area with

Data representation using robust nonnegative matrix factorization for edge computing
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) has been widely applied in edge computing information retrieval and pattern recognition. regularization and constraint propagation for edge computing called robust constrained

Zero trust in edge computing environment: a blockchain based practical scheme
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scheme of edge computing nodes based on edge computing node and sensing terminal is established to realize fine-grained authorization and access control in edge computing .

A blockchain-based creditable and distributed incentive mechanism for participant mobile crowdsensing in edge computing
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Our contributions can be summarized as follows: 1) In the scenario of MCS-based edge computing we propose a distributed incentive architecture based on the Hyperledger Fabric and AI) and cloud computing (and edge computing ) have emerged together to improve the lives of millions of people. Edge computing is a new advanced version of cloud computing . Today’

DQN Based Mobile Edge Computing for Smart Internet of Vehicle
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In this paper, we investigate a multiuser mobile edge computing (MEC)-aided smart internet of vehicle (IoV) network, where one edge server can help accomplish the intensive

Edge Computing Data Analytics in IoT networks for Nonlinear Dimension Reduction
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edge processing for information investigation by joining edge and distributed computing for different situations with going with edgebased models exhibiting edge processing abilities.

Optimization of Cooperative Offloading Model with Cost Consideration in Mobile Edge Computing
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edge mobile computing we combine collaborative computing with mobile edge computing to propose a multiuser collaborative mobile edge computing model. Based on collaborative

Edge Computing for Facial Recognition Emotion Detection
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Edge Computing describes a distributed framework that is designed to move computing When we talk about Edge Computing we are no longer talking about single endpoints but rather

Task Scheduling Scheme using Resource Allocation for Edge Computing Model
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multi-player multi-task edgecloud computing system. Additionally, the environment has concerned a single cloud computing connected with the multi edge computing server through an

An Optimal System on Data Challenge with Distributed Data Management on Cloud, Fog and Edge Computing
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and logistic agreements, edge computing and the related Without using the terminologies of the edge this paper aims the infrastructure further upstream (near edge ). The fact that the

Edge Computing and the Fifth Generation (5G) Mobile Communication: A Virtualized, Distributed System Towards a New Networking Concept
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(IoT) and edge computing . Hence, the transition towards the virtualized edge distributed virtualized 5G Wireless communication and Mobile Edge Computing (MEC) is constructed

Improved YOLOv3 Garbage Classification and Detection Model for Edge Computing Devices
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Finally, a household trash can test platform is built, and the proposed algorithm is transplanted to the edge computing module NVIDIA Xavier NX. The experimental results show that the

Optimal Admission Control Mechanism Design for Time-Sensitive Services in Edge Computing
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We consider an edge computing system that provides time-sensitive edge services such as object recognition with a fixed service price p. The homogeneous service request arrivesData and Channel-Adaptive Sensor Scheduling for Federated Edge Learning via Over-the-Air Gradient Aggregation Joint Shareability and Interference for Multiple Edge Application

Task Offloading Strategy Based on Improving Edge Server Computing Resources
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And the utilization of edge computing resources is better than other strategies proposed in Section II, the background of the edge computing task offloading strategies and related works

Mobile Fog Computing by Using SDN/NFV on 5G Edge Nodes
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mobile edge computing (MEC) connects them to the edge server. on edge nodes leads to reduced latency and increased scalability. The application of SDN/NFV in edge computing

Edge Intelligence: Architecture, Scope and Applications
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And the edge computing here refers to the idea of bringing the computation and storage closer to the source of data. Edge computing has many advantages over the cloud computing

Blockchain-aided Integrated Edge Framework of Cybersecurity for Internet of Things
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The edge computing model is identical to cloud computing in that it equips users with heterogeneity, low latency, location awareness, and improved QoS for applications, especially TheInternational Conference on Edge Computing ( EDGE 202 http://the edgecomputing . org/), which put its focus on the state of the art and practice of edge computing including,

The design of a novel smart home control system using a smart grid based on edge and cloud computing
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To remedy this problem, we propose a hybrid solution by using the Cloud and Edge Computing to process the data. We define a hybrid solution where we use the edge computing for

Lightweight edge Slice Orchestration Framework
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Edge computing is one of the critical components enabling low-latency demanding services in beyond 5G networks. Indeed, the deployed applications at the edge Lightweight edge

A Suvey on Edge Intelligent Video Surveillance with Deep Reinforcement Learning
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As one of the key technologies of 5G communication technology, edge computing has also been widely used in intelligent video surveillance system to solve low-latency, high-precision

Guest Editorial: Graph-powered machine learning in future-generation computing systems
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Meanwhile, the computing system evolves rapidly and becomes large-scale, collaborative, with many computing principles proposed such as cloud computing edge computing and

Specification and Operation of Privacy Models for Data Streams on the Edge
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Furthermore, the authors assess the advantages of edge networks for ML and how a model can be trained and extended on the go. Still, the low latency in edge computing is also

Analytical and Hierarchical Models for Availability Evaluation of EdgeFog-Cloud Continuum Applications
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Edge Computing at a Glance Edge computing paradigm processes the data locally at the edge nodes; then the selected data or insights flow to the cloud server. This is the opposite of

Geo-distributed Edge and Cloud Resource Management for Low-latency Stream Processing
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for allocating computing resources in edge and cloud computing environments. In edge computing model for allocating computing resources in edge computing platforms that allows

A Privacy-Preserving Middleware Framework for Fog ComputingEnhanced IoT using Differential Privacy
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on cloud services and edge computing is gradually increasing, such as cloud computing cloud storage, and cloud-fog communication. The emergence of fog computing solves the

From Wearable Device to OpenEMR: 5G Edge Centered Telemedicine and Decision Support System
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This study proposed a 5G mobile edge computing (MEC) based telemedicine design integrating wearable devices with an Open-EMR electronic health records system. This design has

Lead federated neuromorphic learning for edge artificial intelligence
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potential of edge artificial intelligence (AI) which is the convergence of edge computing 20 and AI, it on resource-constrained edge devices, hence hindering the application of edge AI at

A Quality-driven Machine Learning Governance Architecture for Self-Adaptive Edge Clouds
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edge cloud computing on clustered singleboard devices. In Intl Conf on Cloud Computing Deep learning for edge computing applications: A state-of-the-art survey. IEEE Access, 8:

Probabilistic Cooperative Coded Forwarding for Broadcast Transmissions in Industrial Mobile Edge Communications
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One of the key enabling technologies of IIoT is mobile edge computing (MEC), which integrates the cloud computing capabilities on the mobile IIoT node devices in the edge networks [2

Utilizing AI Planning on the Edge
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we argue that Edge Computing can help to (i) tackle the scalability problem by splitting the problem and (ii) overcome networks bottleneck by processing sensory data on the edge .

QoE-DASH: DASH QoE Performance Evaluation Tool for EdgeCache and Recommendation
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provided by Multi-access Edge Computing (MEC) has access Edge Computing (MEC) has motivated novel video caches at the network edge and recommendation systems .

Towards Approximate Computing for Achieving Energy vs. Accuracy Trade-offs
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Following the autonomous driving scenario, reconfigurable approximating accelerators could be developed to reach a lower level for cases of Edge computing . The need to redesign

Optimal Edge Caching with Individual Demand Dynamics
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With ever reducing memory costs coupled with explosive data demands at the network edges that are driven by the internet of things, edge computing and 5G, edge caching is

10 Fog-or EdgeBased Multimedia Data Computing and Storage Policie s
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The research reveals that the fog computing or edge computing ideas have been suggested in recent years to boost these shortcomings by bringing transaction processing

Software Architectural Solutions for Mobile Cloud Computing Systems
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mobile edge computing . The research and development activities are currently focused on utilizing software engineering methodologies to minimize the complexities and enhance the

End-to-End Data Authentication Deep Learning Model for Securing IoT Configurations
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Unlike these past efforts, our study presents a deep learning-based ECG authentication approach for edge computing platforms where, unlike in IoT, cloud resources and services are

A BRIEF OVERVIEW OF COGNITIVE COMPUTING
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cognitive computing from its definition to its applications in different fields. Furthermore, this research will classify cognitive computing Cognitive computing researchers made numerous defined networking (SDN) and cloud computing over 5G mobile communication in vehicular in the cloud and edge continuum. It presents key computing technologies of the past and the

Decentralized Machine Learning for Intelligent Health Care Systems on the Computing Continuum
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edge resources, presented a relevant computing alternative for supporting the next generation EHR systems. The computing His research interests include fog and edge computing

NOTE FOR NATIONAL DEFENCE: Cognitive Security Analyst and Why we Need It
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One of the main challenges of mobile edge computing is the We need a combination of mobile edge computing and that together will form a mobile edge computing server. One of the

NOTE FOR NATIONAL DEFENCE: Defence Policies on Zero Trust Model for Battlefield Applications
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for integration of 5G and edge computing . However, there edge computing projects are running in 40 cities of China. of trust, a 5G and edge computing integration can provide the

SEFSD: An Effective Deployment Algorithm for Fog Computing Systems
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Wang, An energy-aware edge server placement algorithm in mobile edge computing in Proceedings of IEEE International Conference on Edge Computing 201 pp. 66 73. 20.

Environmental, User, and Social Context-Aware Augmented Reality for Supporting Personal Development and Change
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use of edge computing a distributed computing paradigm Edge computingsupported SLAM and scene understanding: We argue for the need to develop additional edge computing

Object Identification Using Manipulated Edge Detection Techniques
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The edge detection described in this article is first-order edge detection, such as Canny, Sobel, and Prewitt Roberts methods. Based on these edge detection methods, the results of

Research Article Eco-Environmental Civilization Construction System in Remote Areas Based on Multiple Data Collection and the Internet of Things
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Edge computing is to offload part of the computing tasks in the cloud center to the edge of the Node monitoring system and edge computing network system architecture, this paper

Distributed Inference with Deep Learning Models across Heterogeneous Edge Devices
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Then for a specific layer l, the output range that device i is responsible for computing is xi−xi Chen, Edge ai: On-demand accelerating deep neural network inference via edge computing

Resource Allocation and Task Scheduling in Fog Computing and Internet of Everything Environments: A Taxonomy, Review, and Future Directions
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fog computing and IoE paradigms. Second, we delineate the optimization metric engaged with fog computing All one needs to know about fog computing and related edge computing

AI in 5G: The Case of Online Distributed Transfer Learning over Edge Networks
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Edge Computing Networks: We study the system over a series of consecutive time slots T = { T}, corresponding to our decision-making frequency. We consider a set of TheInternational Conference on Edge Computing ( EDGE 202 http://the edgecomputing . org/), which put its focus on the state of the art and practice of edge computing including,

Serverless Computing for NFV: Is it Worth it A Performance Comparison Analysis
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computing can help optimize operating costs by increasing resource utilization . Given its nature, serverless computing networking and edge computing . However, most of

Expediting Konica Minoltas Digital Transformation: AI-enabled Orchestration of Modern Workload and Software-Defined Infrastructure from Edge to Cloud
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Hybrid cloud combines the benefits of edge computing with the vast resource pool and services offered by public clouds by integrating the two systems and giving users the freedom to

Green Cloud Computing an Approach Towards Sustainability
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This study investigates the dynamics of Green Cloud Computing services and performs a cloud computing can be highly effective in enhancing the benefits of cloud computing further

Blockchain-Based SQKD and IDS in Edge Enabled Smart Grid Network
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With key management is presented for smart grid edge computing infrastructure. Mostly, attackers use hardware for capturing-sensitive energy-related information. A lightweight mutual

Experimental Implementation of a Neural Network Optical Channel Equalizer in Restricted Hardware Using Pruning and Quantization
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Within the context of edge computing not only is speed an important factor, but also power efficiency. In this work, the metric used to evaluate the energy consumption and compare theservices can take benefit from IoT and edge computing paradigm, not only for processing services to the edge . Since IoT devices produce a massive amount of IoT data at the edge we

Towards Low-Cost IoT and LPWAN-Based Flood Forecast and Monitoring System
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Moreover, we developed an edge A2IoT architecture in [ 9] and implemented in [ 11]. Towards landslides early warning system with fog- edge computing and artificial intelligence TheInternational Conference on Edge Computing ( EDGE 202 http://the edgecomputing . org/), which put its focus on the state of the art and practice of edge computing including,

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