SDN-assisted Service Placement for the IoT-based Systems in Multiple Edge Servers Environment

Edge computing is proved to be an effective solution for the Internet of Things (IoT)-based systems. Bringing the resources closer to the end devices has improved the performance of the networks and reduced the load on the cloud. On the other hand, edge computing has some constraints related to the amount of the resources available on the edge servers, which is considered to be limited as compared with the cloud. In this paper, we propose Software-Defined Networking (SDN)-based resources allocation and service placement system in the multi-edge networks that serve multiple IoT applications. In this system, the resources of the edge servers are monitored using the proposed Edge Server Application (ESA) to determine the state of the edge server and, therefore, the acceptable services by each server. Benefiting from the information gathered by ESA, the service offloading decision would be taken by the proposed SDN Non-core Application (SNA) in a way that ensures an efficient load distribution and better resources utilization for the edge servers. A Weighted Aggregated Sum Product Assessment Method (WASPAS) was used to determine the best edge server. The proposed system was compared with a non-SDN system and showed improvement in the performance and the utilization of resources of the edge servers. Furthermore, the request handling time was considerably reduced and settled in constant rates for a different number of devices.

Download Full-text

Dynamic Service Placement and Load Distribution in Edge Computing

2020 16th International Conference on Network and Service Management (CNSM) ◽

10.23919/cnsm50824.2020.9269059 ◽

2020 ◽

Author(s):

Adyson Magalhaes Maia ◽

Yacine Ghamri-Doudane ◽

Dario Vieira ◽

Miguel Franklin de Castro

Keyword(s):

Load Distribution ◽

Edge Computing ◽

Service Placement

Download Full-text

ARTIFICIAL INTELLIGENCE AS A SERVICE IN DISTRIBUTED MULTI ACCESS EDGE COMPUTING ON 5G EXTRACTING DATA USING IOT AND INCLUDING AR/VR FOR REAL-TIME REPORTING

INFORMATION TECHNOLOGY IN INDUSTRY ◽

10.17762/itii.v9i1.220 ◽

2021 ◽

Vol 9 (1) ◽

pp. 912-931

Author(s):

Pavan Madduru

Keyword(s):

Cloud Computing ◽

Internet Of Things ◽

Virtual Machines ◽

Smart Cities ◽

Assistive Technologies ◽

Edge Computing ◽

Smart Devices ◽

The Internet ◽

Iot Applications ◽

The Internet Of Things

To meet the growing demand for mobile data traffic and the stringent requirements for Internet of Things (IoT) applications in emerging cities such as smart cities, healthcare, augmented / virtual reality (AR / VR), fifth-generation assistive technologies generation (5G) Suggest and use on the web. As a major emerging 5G technology and a major driver of the Internet of Things, Multiple Access Edge Computing (MEC), which integrates telecommunications and IT services, provides cloud computing capabilities at the edge of an access network. wireless (RAN). By providing maximum compute and storage resources, MEC can reduce end-user latency. Therefore, in this article we will take a closer look at 5G MEC and the Internet of Things. Analyze the main functions of MEC in 5G and IoT environments. It offers several core technologies that enable the use of MEC in 5G and IoT, such as cloud computing, SDN / NFV, information-oriented networks, virtual machines (VMs) and containers, smart devices, shared networks and computing offload. This article also provides an overview of MEC's role in 5G and IoT, a detailed introduction to MEC-enabled 5G and IoT applications, and future perspectives for MEC integration with 5G and IoT. Additionally, this article will take a closer look at the MEC research challenges and unresolved issues around 5G and the Internet of Things. Finally, we propose a use case that MEC uses to obtain advanced intelligence in IoT scenarios.

Download Full-text

DESIGN AND DEVELOPMENT AI-ENABLED EDGE COMPUTING FOR INTELLIGENT-IOT APPLICATIONS

Journal of Trends in Computer Science and Smart Technology - September 2019 ◽

10.36548/jtcsst.2019.2.002 ◽

2019 ◽

Vol 2019 (02) ◽

pp. 84-94 ◽

Cited By ~ 10

Author(s):

Dr. Sivaganesan D.

Keyword(s):

Artificial Intelligence ◽

Internet Of Things ◽

Edge Computing ◽

The Internet ◽

Service Provisioning ◽

Iot Applications ◽

The People ◽

Smart Farming ◽

The Internet Of Things ◽

Day By Day

The advancements in the technologies and the increase in the digital miniaturization day by day are causing devices to become smarter and smarter and the emergence of the internet of things and the cloud has made things even better with insightful suggestions for organization as well as the way the people work and lead their life. The limitations in the cloud paradigm in terms of processing complexity, the latency in the service provisioning and improper resource scheduling, remains as a reason leading to shifting of applications from cloud to edge. More over the emergence of the artificial intelligence in the edge computing has turned out to be center of attention as it improves the speed and the range of the IOT applications. The paper also puts forth the design of the AI-enabled Edge computing for developing a Smart Farming.

Download Full-text

A Multi-Objective Service Placement and Load Distribution in Edge Computing

2019 IEEE Global Communications Conference (GLOBECOM) ◽

10.1109/globecom38437.2019.9014303 ◽

2019 ◽

Author(s):

Adyson M. Maia ◽

Yacine Ghamri-Doudane ◽

Dario Vieira ◽

Miguel F. de Castro

Keyword(s):

Load Distribution ◽

Edge Computing ◽

Multi Objective ◽

Service Placement

Download Full-text

An improved multi-objective genetic algorithm with heuristic initialization for service placement and load distribution in edge computing

Computer Networks ◽

10.1016/j.comnet.2021.108146 ◽

2021 ◽

pp. 108146

Author(s):

Adyson M. Maia ◽

Yacine Ghamri-Doudane ◽

Dario Vieira ◽

Miguel F. de Castro

Keyword(s):

Genetic Algorithm ◽

Load Distribution ◽

Edge Computing ◽

Multi Objective ◽

Service Placement ◽

Multi Objective Genetic Algorithm

Download Full-text

Joint Service Placement and Request Scheduling for Multi-SP Mobile Edge Computing Network

2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) ◽

10.1109/icpads51040.2020.00014 ◽

2020 ◽

Author(s):

Zhengwei Lei ◽

Hongli Xu ◽

Liusheng Huang ◽

Zeyu Meng

Keyword(s):

Edge Computing ◽

Mobile Edge Computing ◽

Service Placement

Download Full-text

Attack Categorisation for IoT Applications in Critical Infrastructures, a Survey

Applied Sciences ◽

10.3390/app11167228 ◽

2021 ◽

Vol 11 (16) ◽

pp. 7228

Author(s):

Edward Staddon ◽

Valeria Loscri ◽

Nathalie Mitton

Keyword(s):

Critical Infrastructure ◽

Attack Detection ◽

Critical Infrastructures ◽

Cyber Attack ◽

Specific System ◽

Iot Applications ◽

War Zone ◽

Clear Vision ◽

The Internet Of Things ◽

Do So

With the ever advancing expansion of the Internet of Things (IoT) into our everyday lives, the number of attack possibilities increases. Furthermore, with the incorporation of the IoT into Critical Infrastructure (CI) hardware and applications, the protection of not only the systems but the citizens themselves has become paramount. To do so, specialists must be able to gain a foothold in the ongoing cyber attack war-zone. By organising the various attacks against their systems, these specialists can not only gain a quick overview of what they might expect but also gain knowledge into the specifications of the attacks based on the categorisation method used. This paper presents a glimpse into the area of IoT Critical Infrastructure security as well as an overview and analysis of attack categorisation methodologies in the context of wireless IoT-based Critical Infrastructure applications. We believe this can be a guide to aid further researchers in their choice of adapted categorisation approaches. Indeed, adapting appropriated categorisation leads to a quicker attack detection, identification, and recovery. It is, thus, paramount to have a clear vision of the threat landscapes of a specific system.

Download Full-text