Dynamic load balancing assisted optimized access control mechanism for Edge‐Fog‐Cloud network in Internet of Things environment
Author:
- 4 June 2021
- journal article
- research article
- Published by Wiley in Concurrency and Computation: Practice and Experience
- Vol. 33 (21) , e6440
Abstract
The modern age networks are supposed to be connected, agile, programmable, and load efficient to counter the side‐effects of an imbalanced network such as network congestion, higher transmission cost, low reliability, and so forth. The wide number of electronic devices around us have a great potential to realize the concept of a connected world. Internet of Things (IoT) is an effort of the research community to realize this concept, and cloud computing plays an important role in this realization. However, fog and edge computing are more prominent solutions for small power devices and latency sensitive applications. As IoT sensors generate huge volume of data, and the IoT environment comprises of multiple applications and traffic conditions, a network traffic based dynamic load balancing approach is needed to optimize the overall network performance. This work proposes a layer based Edge‐Fog‐Cloud network architecture to distribute the network traffic load in an IoT environment. In addition to this, a load balancing assisted optimized access control mechanism is discussed to improve the network load conditions further. The proposed mechanism is tested using Amazon web services platform and the achieved results validate the effectiveness of the proposed approach. The simulation results show an average improved CPU utilization rate of 10.13%, 10.01%, 10.82%, 8.78%, and 11.91% in five different experiments conducted.Keywords
This publication has 30 references indexed in Scilit:
- Serving at the Edge: A Scalable IoT Architecture Based on Transparent ComputingIEEE Network, 2017
- The Emergence of Edge ComputingComputer, 2017
- Performance Modeling and Analysis of the EDoS-Shield MitigationArabian Journal for Science and Engineering, 2016
- Edge-Fog cloud: A distributed cloud for Internet of Things computations2016
- IoT-Based Big Data Storage Systems in Cloud Computing: Perspectives and ChallengesIEEE Internet of Things Journal, 2016
- Fog Computing: Helping the Internet of Things Realize Its PotentialComputer, 2016
- Fog and IoT: An Overview of Research OpportunitiesIEEE Internet of Things Journal, 2016
- Edge Computing: Vision and ChallengesIEEE Internet of Things Journal, 2016
- Evaluation of the Impact of EDoS Attacks Against Cloud Computing ServicesArabian Journal for Science and Engineering, 2014
- Internet of Things (IoT): A vision, architectural elements, and future directionsFuture Generation Computer Systems, 2013