An Optimized IoT-enabled Big Data Analytics Architecture for Edge-Cloud Computing

Muhammad Babar, Mian Ahmad Jan, Xiangjian He, Muhammad Usman Tariq, Spyridon Mastorakis, Ryan Alturki

Research output: Journal PublicationArticlepeer-review

1 Citation (Scopus)

Abstract

The awareness of edge computing is attaining eminence and is largely acknowledged with the rise of Internet of Things (IoT). Edge-enabled solutions offer efficient computing and control at the network edge to resolve the scalability and latency-related concerns. Though, it comes to be challenging for edge computing to tackle diverse applications of IoT as they produce massive heterogeneous data. The IoT-enabled frameworks for Big Data analytics face numerous challenges in their existing structural design, for instance, the high volume of data storage and processing, data heterogeneity, and processing time among others. Moreover, the existing proposals lack effective parallel data loading and robust mechanisms for handling communication overhead. To address these challenges, we propose an optimized IoT-enabled big data analytics architecture for edge-cloud computing using machine learning. In the proposed scheme, an edge intelligence module is introduced to process and store the big data efficiently at the edges of the network with the integration of cloud technology. The proposed scheme is composed of two layers: IoT-edge and Cloud-processing. The data injection and storage is carried out with an optimized MapReduce parallel algorithm. Optimized Yet Another Resource Negotiator (YARN) is used for efficiently managing the cluster. The proposed data design is experimentally simulated with an authentic dataset using Apache Spark. The comparative analysis is decorated with existing proposals and traditional mechanisms. The results justify the efficiency of our proposed work.

Original languageEnglish
JournalIEEE Internet of Things Journal
DOIs
Publication statusPublished - 14 Mar 2022
Externally publishedYes

Keywords

  • Backpropagation (BP) Neural Network
  • Big Data
  • Big Data Analytics
  • Computer architecture
  • Distributed databases
  • Edge Computing
  • Edge computing
  • Internet of Things
  • Internet of Things (IoT)
  • Loading
  • Machine Learning
  • Proposals
  • Yet Another Resource Negotiator (YARN).

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'An Optimized IoT-enabled Big Data Analytics Architecture for Edge-Cloud Computing'. Together they form a unique fingerprint.

Cite this