Table 14.

Categorizing the state-of-the-art in shopping system applications.

Study	Attributes
Zhang et al. [26]	Main concept: Designing a validation method for isolated machinery pieces to monitor the state of recyclable resources in real time.
	Case study: Reassembly and maintenance of AER.
	App domain: Domain of worker load, energy area, and cost area.
	Advantage: The remanufacturing sector, in particular for AER, is developing sustainably and producing cleaner products.
	Disadvantage: -
	Simulation/Implementation: -
	Dataset: -
	Future work: Concentrate on the mathematical-physical interaction between AS and MS models, as well as improve the approach for solving the RTPS challenge with more goals and realistic restrictions.
Wang et al. [37]	Main concept: Provide a comprehensive EC-IIoT architecture to improve real-time scheduling capabilities.
	Case study: Collaboration company in Xi’an.
	App domain: Edge computing.
	Advantage: Establishing the framework of the EC-IIoT-based DFJS-RS, which enables the capture and treatment of massive amounts of data quickly and efficiently.
	Disadvantage: The scarcity of case studies.
	Simulation/Implementation: -
	Dataset: -
	Future work: By placing edge computing nodes on the network’s edge, you can improve the network’s dependability and real-time performance. Industrial wireless networks will also be evaluated for secure transmission.
Al-Turjman et al. [38]	Main concept: Simple search and convergence to the optimal solution.
	Case study: a cloud environment.
	App domain: Wireless area network (WAN), 3G, and 4G networks.
	Advantage: High-quality services in terms of throughput and low latency.
	Disadvantage: -
	Simulation/Implementation: -
	Dataset: -
	Future work: The suggested system can operate as a middleware among cloud and edge computing resources, allowing for efficient IoT task scheduling collaboration between the edge and the cloud.