scholarly journals EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX

2021 ◽  
Vol 12 (1) ◽  
pp. 140
Author(s):  
Seunghwan Lee ◽  
Linh-An Phan ◽  
Dae-Heon Park ◽  
Sehan Kim ◽  
Taehong Kim
Keyword(s):  
Edge Computing ◽  
Computing Platform ◽  
Fundamental Limitations ◽  
Service Deployment ◽  
Dynamic Resource Management ◽  
Numerous Data ◽  
Dynamic Resource ◽  
Iot Devices ◽  
Container Orchestration ◽  
The Internet Of Things

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.

scholarly journals Satellite Edge Computing for the Internet of Things in Aerospace

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4375 ◽  
Author(s):  
Yuxuan Wang ◽  
Jun Yang ◽  
Xiye Guo ◽  
Zhi Qu
Keyword(s):  
Internet Of Things ◽  
Computing System ◽  
Edge Computing ◽  
The Internet ◽  
New Paradigm ◽  
Long Distance ◽  
Modeling Analysis ◽  
Iot Devices ◽  
Terrestrial Network ◽  
The Internet Of Things

As one of the information industry’s future development directions, the Internet of Things (IoT) has been widely used. In order to reduce the pressure on the network caused by the long distance between the processing platform and the terminal, edge computing provides a new paradigm for IoT applications. In many scenarios, the IoT devices are distributed in remote areas or extreme terrain and cannot be accessed directly through the terrestrial network, and data transmission can only be achieved via satellite. However, traditional satellites are highly customized, and on-board resources are designed for specific applications rather than universal computing. Therefore, we propose to transform the traditional satellite into a space edge computing node. It can dynamically load software in orbit, flexibly share on-board resources, and provide services coordinated with the cloud. The corresponding hardware structure and software architecture of the satellite is presented. Through the modeling analysis and simulation experiments of the application scenarios, the results show that the space edge computing system takes less time and consumes less energy than the traditional satellite constellation. The quality of service is mainly related to the number of satellites, satellite performance, and task offloading strategy.

Edge Architecture Integration of Technologies

2021 ◽  
pp. 1-30
Author(s):  
Sandhya Devi R. S. ◽  
Vijaykumar V. R. ◽  
Sivakumar P. ◽  
Neeraja Lakshmi A. ◽  
Vinoth Kumar B.
Keyword(s):  
Data Privacy ◽  
Response Times ◽  
Management Strategies ◽  
Cost Savings ◽  
Edge Computing ◽  
Battery Life ◽  
Computing Platform ◽  
Computing Paradigm ◽  
Time Latency ◽  
The Internet Of Things

The enormous growth of the internet of things (IoT) and cloud-based services have paved the way for edge computing, the new computing paradigm which processes the data at the edge of the network. Edge computing resolves issues related to response time, latency, battery life limitation, cost savings for bandwidth, as well as data privacy and protection. The architecture brings devices and data back to the consumer. This model of computing as a distributed IT system aims at satisfying end-user demands with faster response times by storing data closer to it. The enormous increase in individuals and locations, connected devices such as appliances, laptops, smartphones, and transport networks that communicate with each other has raised exponentially. Considering these factors in this chapter, edge computing architecture along with the various components that constitute the computing platform are discussed. The chapter also discusses resource management strategies deliberate for edge computing devices and integration of various computing technologies to support efficient IoT architecture.

scholarly journals A lightweight cryptographic algorithm for the transmission of images from road environments in self-driving

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Runchen Gao ◽  
Shen Li ◽  
Yuqi Gao ◽  
Rui Guo
Keyword(s):  
Large Scale ◽  
Edge Computing ◽  
Sensitive Information ◽  
Security Strategy ◽  
Privacy Leakage ◽  
Computational Overhead ◽  
Cryptographic Algorithm ◽  
Comparable Encryption ◽  
Iot Devices ◽  
The Internet Of Things

AbstractWith the large-scale application of 5G in industrial production, the Internet of Things has become an important technology for various industries to achieve efficiency improvement and digital transformation with the help of the mobile edge computing. In the modern industry, the user often stores data collected by IoT devices in the cloud, but the data at the edge of the network involves a large of the sensitive information, which increases the risk of privacy leakage. In order to address these two challenges, we propose a security strategy in the edge computing. Our security strategy combines the Feistel architecture and short comparable encryption based on sliding window (SCESW). Compared to existing security strategies, our proposed security strategy guarantees its security while significantly reducing the computational overhead. And our GRC algorithm can be successfully deployed on a hardware platform.

scholarly journals A Conceptual Architecture in Decentralizing Computing, Storage, and Networking Aspect of IoT Infrastructure

IoT ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 205-221
Author(s):  
Yustus Eko Oktian ◽  
Elizabeth Nathania Witanto ◽  
Sang-Gon Lee
Keyword(s):  
Overlay Networks ◽  
Distributed Storage ◽  
Internet Service ◽  
Computing Platform ◽  
Smart Contract ◽  
Secure Computing ◽  
Storage Network ◽  
Application Data ◽  
Iot Devices ◽  
The Internet Of Things

Since the inception of the Internet of Things (IoT), we have adopted centralized architecture for decades. With the vastly growing number of IoT devices and gateways, this architecture struggles to cope with the high demands of state-of-the-art IoT services, which require scalable and responsive infrastructure. In response, decentralization becomes a considerable interest among IoT adopters. Following a similar trajectory, this paper introduces an IoT architecture re-work that enables three spheres of IoT workflows (i.e., computing, storage, and networking) to be run in a distributed manner. In particular, we employ the blockchain and smart contract to provide a secure computing platform. The distributed storage network maintains the saving of IoT raw data and application data. The software-defined networking (SDN) controllers and SDN switches exist in the architecture to provide connectivity across multiple IoT domains. We envision all of those services in the form of separate yet integrated peer-to-peer (P2P) overlay networks, which IoT actors such as IoT domain owners, IoT users, Internet Service Provider (ISP), and government can cultivate. We also present several IoT workflow examples showing how IoT developers can adapt to this new proposed architecture. Based on the presented workflows, the IoT computing can be performed in a trusted and privacy-preserving manner, the IoT storage can be made robust and verifiable, and finally, we can react to the network events automatically and quickly. Our discussions in this paper can be beneficial for many people ranging from academia, industries, and investors that are interested in the future of IoT in general.

scholarly journals Distributed Learning Based Joint Communication and Computation Strategy of IoT Devices in Smart Cities

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 973
Author(s):  
Tianyi Liu ◽  
Ruyu Luo ◽  
Fangmin Xu ◽  
Chaoqiong Fan ◽  
Chenglin Zhao
Keyword(s):  
Smart Cities ◽  
Wireless Channel ◽  
Edge Computing ◽  
Resource Allocation Algorithm ◽  
Q Learning ◽  
Joint Policy ◽  
Low Efficiency ◽  
Learning Policies ◽  
Iot Devices ◽  
The Internet Of Things

With the development of global urbanization, the Internet of Things (IoT) and smart cities are becoming hot research topics. As an emerging model, edge computing can play an important role in smart cities because of its low latency and good performance. IoT devices can reduce time consumption with the help of a mobile edge computing (MEC) server. However, if too many IoT devices simultaneously choose to offload the computation tasks to the MEC server via the limited wireless channel, it may lead to the channel congestion, thus increasing time overhead. Facing a large number of IoT devices in smart cities, the centralized resource allocation algorithm needs a lot of signaling exchange, resulting in low efficiency. To solve the problem, this paper studies the joint policy of communication and computing of IoT devices in edge computing through game theory, and proposes distributed Q-learning algorithms with two learning policies. Simulation results show that the algorithm can converge quickly with a balanced solution.

scholarly journals SoftSystem: Smart Edge Computing Device Selection Method for IoT Based on Soft Set Technique

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Muhammad Shafiq ◽  
Zhihong Tian ◽  
Ali Kashif Bashir ◽  
Korhan Cengiz ◽  
Adnan Tahir
Keyword(s):  
Critical Issue ◽  
Soft Set ◽  
Edge Computing ◽  
Computing Device ◽  
Framework Model ◽  
Device Selection ◽  
Iot Devices ◽  
The Given ◽  
The Internet Of Things ◽  
New Framework

The Internet of Things (IoT) is growing day by day, and new IoT devices are introduced and interconnected. Due to this rapid growth, IoT faces several issues related to communication in the edge computing network. The critical issue in these networks is the effective edge computing IoT device selection whenever there are several edge nodes to carry information. To overcome this problem, in this paper, we proposed a new framework model named SoftSystem based on the soft set technique that recommends useful IIoT devices. Then, we proposed an algorithm named Softsystemalgo. For the proposed system, three different parameters are selected: IoT Device Security (IDSC), IoT Device Storage (IDST), and IoT Device Communication Speed (IDCS). We also find out the most significant parameters from the given set of parameters. It is evident that our proposed system is effective for the selection of edge computing devices in the IoT network.

Sign in / Sign up

Export Citation Format

Share Document