GoDeep: Intelligent IoV Service Deployment and Execution with Privacy Preservation in Cloud-edge Computing

With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices. EdgeX Foundry is a representative open-source-based IoT gateway platform, providing various IoT protocol services and interoperability between them. However, due to the absence of container orchestration technology, such as automated deployment and dynamic resource management for application services, EdgeX Foundry has fundamental limitations of a potential edge computing platform. In this paper, we propose EdgeX over Kubernetes, which enables remote service deployment and autoscaling to application services by running EdgeX Foundry over Kubernetes, which is a product-grade container orchestration tool. Experimental evaluation results prove that the proposed platform increases manageability through the remote deployment of application services and improves the throughput of the system and service quality with real-time monitoring and autoscaling.

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Collaboration of Smart City Services with Appropriate Resource Management and Privacy Protection

Journal of Ubiquitous Computing and Communication Technologies - December 2019 ◽

10.36548/jucct.2021.1.005 ◽

2021 ◽

Vol 3 (1) ◽

pp. 43-51

Author(s):

Subarna Shakya

Keyword(s):

Smart City ◽

Privacy Protection ◽

Privacy Preservation ◽

Simulation Analysis ◽

Intelligent Transportation ◽

Edge Computing ◽

Processing Ability ◽

The City ◽

Collaborative Diagnosis ◽

High Processing

Smart city is a quickly developing approach that is powered by Internet of Things (IoTs), providing a number of services such as collaborative diagnosis and intelligent transportation. In general, in a smart city, the terminals have certain limitations that crib their capability of processing cross application and diversified services. Due to insufficient availability of resources that can be used to develop a collaborative smart city services, a novel methodology that is highly recommended is edge computing which holds facility with high processing ability in the city terminals. However, the threat of privacy and safety of information in the collaborative services is crucial in order to ensure a safer environment of edge computing. To address this privacy issue, we have proposed an offloading method that can be used in smarty city to strengthen the privacy, promote edge utility and improve offloading efficiency. In order to establish balance between the collaborative service and privacy preservation, edge computing is integrated with information entropy. The performance is further verified using simulation analysis in appropriate environment.

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An Exploration of Networking and Communication Methodologies for Security and Privacy Preservation in Edge Computing Platforms

10.1002/9781119785521.ch4 ◽

2021 ◽

pp. 69-98

Author(s):

G Arulkumaran ◽

P Balamurugan ◽

J Santhosh

Keyword(s):

Privacy Preservation ◽

Edge Computing ◽

Security And Privacy ◽

Computing Platforms

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Deploying GIS Services into the Edge: A Study from Performance Evaluation and Optimization Viewpoint

Security and Communication Networks ◽

10.1155/2020/8822990 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Jianbing Zhang ◽

Bowen Ma ◽

Jiwei Huang

Keyword(s):

Optimization Problem ◽

Real Life ◽

Computer Software ◽

Edge Computing ◽

Simulation Experiments ◽

Computing Architecture ◽

Mobile Gis ◽

Service Deployment ◽

Quantitative Analyses ◽

Critical Requirement

Geographic information system (GIS) is an integrated collection of computer software and data used to view and manage information about geographic places, analyze spatial relationships, and model spatial processes. With the growing popularity and wide application of GIS in reality, performance has become a critical requirement, especially for mobile GIS services. To attack this challenge, this paper tries to optimize the performance of GIS services by deploying them into edge computing architecture which is an emerging computational model that enables efficient offloading of service requests to edge servers for reducing the communication latency between end-users and GIS servers deployed in the cloud. Stochastic models for describing the dynamics of GIS services with edge computing architecture are presented, and their corresponding quantitative analyses of performance attributes are provided. Furthermore, an optimization problem is formulated for service deployment in such architecture, and a heuristic approach to obtain the near-optimal performance is designed. Simulation experiments based on real-life GIS performance data are conducted to validate the effectiveness of the approach presented in this paper.

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Resource-aware Dynamic Service Deployment for Local IoT Edge Computing: Healthcare Use Case

IEEE Access ◽

10.1109/access.2021.3102867 ◽

2021 ◽

pp. 1-1

Author(s):

Johirul Islam ◽

Tanesh Kumar ◽

Ivana Kovacevic ◽

Erkki Harjula

Keyword(s):

Edge Computing ◽

Use Case ◽

Healthcare Use ◽

Service Deployment ◽

Resource Aware

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A Survey on Secure Deployment of Mobile Services in Edge Computing

Security and Communication Networks ◽

10.1155/2021/8846239 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Mengmeng Cui ◽

Yiming Fei ◽

Yin Liu

Keyword(s):

Autonomous Vehicles ◽

Mobile Network ◽

Edge Computing ◽

Internet Of Vehicles ◽

It Service ◽

Computing Services ◽

Service Deployment ◽

Cloud Computing Services ◽

Complete Survey ◽

Research Studies

Mobile edge computing (MEC) is an emerging technology that is recognized as a key to 5G networks. Because MEC provides an IT service environment and cloud-computing services at the edge of the mobile network, researchers hope to use MEC for secure service deployment, such as Internet of vehicles, Internet of Things (IoT), and autonomous vehicles. Because of the characteristics of MEC which do not have terminal servers, it tends to be deployed on the edge of networks. However, there are few related works that systematically introduce the deployment of MEC. Also, secure service deployment frameworks with MEC are even rare. For this reason, we have conducted a comprehensive and concrete survey of recent research studies on secure deployment. Although numerous research studies and experiments about MEC service deployment have been conducted, there are few systematic summaries that conclude basic concepts and development strategies about secure service deployment of commercial MEC. To make up for the gap, a detailed and complete survey about relative achievements is presented.

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