Bio-Inspired Scheduling for Factory Automation in the TD-LTE System. Issue 5 (3rd September 2022)

• Record Type: Journal Article
• Authors: Ryu, Won Jae; Satrya, Gandeva Bayu; Shin, Soo Young
• Is Part Of: IETE technical review. Volume 39:Issue 5(2022)
• Page Start: 1189
• Page End: 1207
• Publication Date: 2022-09-03
• Subjects: Evolutionary computation -- Factory automation -- Firefly algorithms -- Genetic algorithms -- Particle swarm optimization -- Scheduling algorithms -- TD-LTE -- Wireless communication; Telecommunication -- Periodicals; Electronics -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/02564602.2021.1994043
• Languages: English
• ISSNs: 0256-4602

Abstract

ABSTRACT: Wireless technology has advantages such as low cost, flexibility, relatively easy installation, and the ability to address routing issues. Consequently, wireless factory automation has received considerable attention recently. However, most wireless technologies in factory automation have adopted unlicensed bandwidth, which can be affected by interference from other users. Long-term evolution adopts a licensed bandwidth; therefore, it can be a solution for factory automation. This paper presents scheduling algorithms in wireless industrial networks for factory automation in wireless sensor networks using the TD-LTE system. To satisfy real-time requirements, scheduling algorithms based on bio-inspired optimization algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO), and firefly algorithm (FA), and dynamic frame configuration (DFC) are proposed to cover more nodes. Furthermore, the performances of these algorithms with and without DFC are evaluated.