scholarly journals Simulator for Interactive and Effective Organization of Things in Edge Cluster Computing

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2616
Author(s):  
Woojae Kim ◽  
Inbum Jung
Keyword(s):  
Internet Of Things ◽  
Cluster Computing ◽  
Edge Computing ◽  
Virtual Space ◽  
Raspberry Pi ◽  
The Internet ◽  
Cluster Architecture ◽  
Material Resources ◽  
Effective Organization ◽  
The Internet Of Things

Edge computing is intended to process events that occur at the endpoint of the Internet of Things (IoT) network quickly and intelligently. Edge regions must be organized effectively to facilitate cooperation so that the intention of edge computing can be realized. However, inevitably, many human and material resources are required in the process of arranging things in the edge area to confirm the appropriateness of the thing operation. To address this problem, we proposed a simulator that created a virtual space for edge computing and provided an interactive role and effective organization for edge things. The proposed simulator was aimed at Raspberry Pi as the physical hardware target. To prove the accuracy of the proposed simulator, the similarity between the proposed simulator and the physical target Raspberry Pi was evaluated based on three metrics while executing several applications. In the experiment, several edge-computing service applications were performed in various cluster architecture types formed by the proposed simulator. To support effective resource usage and fast real-time response for edge computing, the proposed simulator identified a suitable number of things in forming the edge cluster.

DEVELOPMENT OF THE HARDWARE AND SOFTWARE PLATFORM FOR MODERN IOT SOLUTIONS BASED ON FOG COMPUTING USING CLOUD-NATIVE TECHNOLOGIES

2017 ◽  
Vol 2 (1) ◽  
pp. 102-112
Author(s):  
Shevchenko A. ◽  
◽  
Puzyrov S.
Keyword(s):  
Internet Of Things ◽  
Fog Computing ◽  
Digital Transformation ◽  
Edge Computing ◽  
Raspberry Pi ◽  
The Internet ◽  
Service Network ◽  
Keywords Internet ◽  
The Moment ◽  
The Internet Of Things

The concept of digital transformation is very relevant at the moment due to the epidemiological situation and the transition of the world to the digital environment. IoT is one of the main drivers of digital transformation. The Internet of Things (IoT) is an extension of the Internet, which consists of sensors, controllers, and other various devices, the so-called "things," that communicate with each other over the network. In this paper, the development of hardware and software for the organization of fog and edge computing was divided into three levels: hardware, orchestration, application. Application level also was divided into two parts: software and architectural. The hardware was implemented using two versions of the Raspberry Pi: Raspberry Pi 4 and Raspberry Pi Zero, which are connected in master-slave mode. The orchestration used K3S, Knative and Nuclio technologies. Technologies such as Linkerd service network, NATS messaging system, implementation of RPC - GRPC protocol, TDengine database, Apache Ignite, Badger were used to implement the software part of the application level. The architecture part is designed as an API development standard, so it can be applied to a variety of IoT software solutions in any programming language. The system can be used as a platform for construction of modern IoT-solutions on the principle of fog\edge computing. Keywords: Internet of Things, IoT-platform, Container technologies, Digital Twin, API.

scholarly journals Edge Computing for the Internet of Things: A Case Study

2018 ◽  
Vol 5 (2) ◽  
pp. 1275-1284 ◽  
Author(s):  
Gopika Premsankar ◽  
Mario Di Francesco ◽  
Tarik Taleb
Keyword(s):  
Internet Of Things ◽  
Edge Computing ◽  
The Internet ◽  
The Internet Of Things

Distributing Computing in the Internet of Things: Cloud, Fog and Edge Computing Overview

2017 ◽  
pp. 87-115 ◽  
Author(s):  
P. J. Escamilla-Ambrosio ◽  
A. Rodríguez-Mota ◽  
E. Aguirre-Anaya ◽  
R. Acosta-Bermejo ◽  
M. Salinas-Rosales
Keyword(s):  
Internet Of Things ◽  
Edge Computing ◽  
The Internet ◽  
The Internet Of Things

Bridging the IoT Gap Through Edge Computing

2019 ◽  
pp. 1-9
Author(s):  
R. I. Minu ◽  
G. Nagarajan
Keyword(s):  
Internet Of Things ◽  
Information Needs ◽  
Edge Computing ◽  
The Internet ◽  
Cloud Server ◽  
The Cost ◽  
The Internet Of Things ◽  
Clear Objective ◽  
Origin Point

In the present-day scenario, computing is migrating from the on-premises server to the cloud server and now, progressively from the cloud to Edge server where the data is gathered from the origin point. So, the clear objective is to support the execution and unwavering quality of applications and benefits, and decrease the cost of running them, by shortening the separation information needs to travel, subsequently alleviating transmission capacity and inactivity issues. This chapter provides an insight of how the internet of things (IoT) connects with edge computing.

Towards Autonomous IoT Logistics Objects

2017 ◽  
pp. 210-222
Author(s):  
Bill Karakostas
Keyword(s):  
Internet Of Things ◽  
System Performance ◽  
Credit Card ◽  
Raspberry Pi ◽  
The Internet ◽  
Simulated Environment ◽  
Embedded Knowledge ◽  
New Knowledge ◽  
The Internet Of Things ◽  
Computing Infrastructure

To improve the overall impact of the Internet of Things (IoT), intelligent capabilities must be developed at the edge of the IoT ‘Cloud.' ‘Smart' IoT objects must not only communicate with their environment, but also use embedded knowledge to interpret signals, and by making inferences augment their knowledge of their own state and that of their environment. Thus, intelligent IoT objects must improve their capabilities to make autonomous decisions without reliance to external computing infrastructure. In this chapter, we illustrate the concept of smart autonomous logistic objects with a proof of concept prototype built using an embedded version of the Prolog language, running on a Raspberry Pi credit-card-sized single-board computer to which an RFID reader is attached. The intelligent object is combining the RFID readings from its environment with embedded knowledge to infer new knowledge about its status. We test the system performance in a simulated environment consisting of logistics objects.

Cooperative Edge Computing of Data Analytics for the Internet of Things

2020 ◽  
Vol 6 (4) ◽  
pp. 1166-1179
Author(s):  
Apostolos Galanopoulos ◽  
Theodoros Salonidis ◽  
George Iosifidis
Keyword(s):  
Internet Of Things ◽  
Data Analytics ◽  
Edge Computing ◽  
The Internet ◽  
The Internet Of Things

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.

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