scholarly journals A New Task Offloading Algorithm in Edge Computing

2020 ◽  
Author(s):  
Zhenjiang Zhang ◽  
Chen Li ◽  
ShengLung Peng ◽  
Xintong Pei
Keyword(s):  
Internet Of Things ◽  
User Experience ◽  
Mobile Internet ◽  
Edge Computing ◽  
The Internet ◽  
Disruptive Technology ◽  
Computing Power ◽  
New Applications ◽  
The Internet Of Things ◽  
Task Offloading

Abstract In the last few years, the Internet of Things (IOT), as a new disruptive technology, has gradually changed the world. With the prosperous development of the mobile Internet and the rapid growth of the Internet of Things, various new applications continue to emerge, such as mobile payment, face recognition, wearable devices, driverless, VR/AR, etc. Although the computing power of mobile terminals is getting higher and the traditional cloud computing model has higher computing power, it is often accompanied by higher latency and cannot meet the needs of users. In order to reduce user delay to improve user experience, and at the same time reduce network load to a certain extent, edge computing, as an application of IOT, came into being. In view of the new architecture after dating edge computing, this paper focuses on the task offloading in edge computing, from task migration in multi-user scenarios and edge server resource management expansion, and proposes a multi-agent load balancing distribution based on deep reinforcement learning DTOMALB, a distributed task allocation algorithm, can perform a reasonable offload method for this scenario to improve user experience and balance resource utilization. Simulations show that the algorithm has a certain adaptability compared to the traditional algorithm in the scenario of multi-user single cell, and reduces the complexity of the algorithm compared to the centralized algorithm, and reduces the average response delay of the overall user. And balance the load of each edge computing server, improve the robustness and scalability of the system.

scholarly journals A New Task Offloading Algorithm in Edge Computing

2021 ◽  
Author(s):  
Zhenjiang Zhang ◽  
Chen Li ◽  
ShengLung Peng ◽  
Xintong Pei
Keyword(s):  
Internet Of Things ◽  
User Experience ◽  
Mobile Internet ◽  
Edge Computing ◽  
The Internet ◽  
Disruptive Technology ◽  
Computing Power ◽  
New Applications ◽  
The Internet Of Things ◽  
Task Offloading

Abstract In the last few years, the Internet of Things (IOT), as a new disruptive technology, has gradually changed the world. With the prosperous development of the mobile Internet and the rapid growth of the Internet of Things, various new applications continue to emerge, such as mobile payment, face recognition, wearable devices, driverless, VR/AR, etc. Although the computing power of mobile terminals is getting higher and the traditional cloud computing model has higher computing power, it is often accompanied by higher latency and cannot meet the needs of users. In order to reduce user delay to improve user experience, and at the same time reduce network load to a certain extent, edge computing, as an application of IOT, came into being. In view of the new architecture after dating edge computing, this paper focuses on the task offloading in edge computing, from task migration in multi-user scenarios and edge server resource management expansion, and proposes a multi-agent load balancing distribution based on deep reinforcement learning DTOMALB, a distributed task allocation algorithm, can perform a reasonable offload method for this scenario to improve user experience and balance resource utilization. Simulations show that the algorithm has a certain adaptability compared to the traditional algorithm in the scenario of multi-user single cell, and reduces the complexity of the algorithm compared to the centralized algorithm, and reduces the average response delay of the overall user. And balance the load of each edge computing server, improve the robustness and scalability of the system.

scholarly journals A new task offloading algorithm in edge computing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Zhenjiang Zhang ◽  
Chen Li ◽  
ShengLung Peng ◽  
Xintong Pei
Keyword(s):  
Internet Of Things ◽  
User Experience ◽  
Mobile Internet ◽  
Edge Computing ◽  
The Internet ◽  
Disruptive Technology ◽  
Computing Power ◽  
New Applications ◽  
The Internet Of Things ◽  
Task Offloading

AbstractIn the last few years, the Internet of Things (IOT), as a new disruptive technology, has gradually changed the world. With the prosperous development of the mobile Internet and the rapid growth of the Internet of Things, various new applications continue to emerge, such as mobile payment, face recognition, wearable devices, driverless, VR/AR, etc. Although the computing power of mobile terminals is getting higher and the traditional cloud computing model has higher computing power, it is often accompanied by higher latency and cannot meet the needs of users. In order to reduce user delay to improve user experience, and at the same time reduce network load to a certain extent, edge computing, as an application of IOT, came into being. In view of the new architecture after dating edge computing, this paper focuses on the task offloading in edge computing, from task migration in multi-user scenarios and edge server resource management expansion, and proposes a multi-agent load balancing distribution based on deep reinforcement learning DTOMALB, a distributed task allocation algorithm, can perform a reasonable offload method for this scenario to improve user experience and balance resource utilization. Simulations show that the algorithm has a certain adaptability compared to the traditional algorithm in the scenario of multi-user single cell, and reduces the complexity of the algorithm compared to the centralized algorithm, and reduces the average response delay of the overall user. And balance the load of each edge computing server, improve the robustness and scalability of the system.

scholarly journals Analysis of Security Issues of Edge Computing Based Internet of Things Applications

2020 ◽  
Author(s):  
Shamim Muhammad ◽  
Inderveer Chana ◽  
Supriya Thilakanathan
Keyword(s):  
Internet Of Things ◽  
Edge Computing ◽  
The Internet ◽  
Security Vulnerabilities ◽  
Computing Power ◽  
Security Issues ◽  
Computing Paradigm ◽  
Improved Performance ◽  
The Internet Of Things ◽  
Common Security

Edge computing is a technology that allows resources to be processed or executed close to the edge of the internet. The interconnected network of devices in the Internet of Things has led to an increased amount of data, increasing internet traffic usage every year. Also, edge computing is driving applications and computing power away from the integrated points to areas close to users, leading to improved performance of the application. Despite the explosive growth of the edge computing paradigm, there are common security vulnerabilities associated with the Internet of Things applications. This paper will evaluate and analyze some of the most common security issues that pose a serious threat to the edge computing paradigm.

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.

scholarly journals A systematic Study of Security Challenges and Infrastructures for Internet of Things

2018 ◽  
Vol 7 (4.36) ◽  
pp. 700
Author(s):  
N. Koteswara Rao ◽  
Gandharba Swain
Keyword(s):  
Internet Of Things ◽  
Secure Communication ◽  
Smart Cities ◽  
Security Requirements ◽  
The Internet ◽  
Security Challenges ◽  
Authentication And Authorization ◽  
New Applications ◽  
Privacy And Anonymity ◽  
The Internet Of Things

The proliferation of smart objects with capability of sensing, processing and communication has grown in recent years. In this scenario, the Internet of Things (IoT) connects these objects to the Internet and provides communication with users and devices. IoT enables a huge amount of new applications, with which academics and industries can benefit, such as smart cities, health care and automation. In this environment, compose of constrained devices, the widespread adoption of this paradigm depends of security requirements like secure communication between devices, privacy and anonymity of its users. This paper presents the main security challenges and solutions to provide authentication and authorization on the Internet of Things. 

A Location-Aware Architecture for an IoT-Based Smart Museum

2020 ◽  
pp. 413-432
Author(s):  
Giuseppe Del Fiore ◽  
Luca Mainetti ◽  
Vincenzo Mighali ◽  
Luigi Patrono ◽  
Stefano Alletto ◽  
...  
Keyword(s):  
Internet Of Things ◽  
User Experience ◽  
Image Recognition ◽  
Innovation Process ◽  
Modern Society ◽  
The Internet ◽  
Indoor Location ◽  
Location Aware ◽  
Art And Culture ◽  
The Internet Of Things

The Internet of Things, whose main goal is to automatically predict users' desires, can find very interesting opportunities in the art and culture field, as the tourism is one of the main driving engines of the modern society. Currently, the innovation process in this field is growing at a slower pace, so the cultural heritage is a prerogative of a restricted category of users. To address this issue, a significant technological improvement is necessary in the culture-dedicated locations, which do not usually allow the installation of hardware infrastructures. In this paper, we design and validate a no-invasive indoor location-aware architecture able to enhance the user experience in a museum. The system relies on the user's smartphone and a wearable device (with image recognition and localization capabilities) to automatically deliver personalized cultural contents related to the observed artworks. The proposal was validated in the MUST museum in Lecce (Italy).

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