An Improved Hybrid Swarm Intelligence for Scheduling IoT Application Tasks in the Cloud-Reference-Cited by-同舟云学术

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An Improved Hybrid Swarm Intelligence for Scheduling IoT Application Tasks in the Cloud

Published:2022-09 Issue:9 Volume:18 Page:6264-6272
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Attiya Ibrahim¹^ORCID,Elaziz Mohamed Abd¹^ORCID,Abualigah Laith²^ORCID,Nguyen Tu N.³^ORCID,El-Latif Ahmed A. Abd⁴^ORCID

Affiliation:

1. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt

2. Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan

3. Department of Computer Science, Kennesaw State University, Marietta, GA, USA

4. EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/9795344/09705055.pdf?arnumber=9705055

Reference30 articles.

1. Harris hawks optimization: Algorithm and applications

2. Computation Partitioning for Mobile Cloud Computing in a Big Data Environment

3. Optimization of Composite Cloud Service Processing with Virtual Machines

4. Job Scheduling in Cloud Computing Using a Modified Harris Hawks Optimization and Simulated Annealing Algorithm

5. An efficient symbiotic organisms search algorithm with chaotic optimization strategy for multi-objective task scheduling problems in cloud computing environment;abdullahi;J Netw Comput Appl,2019

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