Internet of Things (IoT) is the interconnection of any object with any other objects that are connected to the Internet. IoT can enhance the experience of customers, increase efficiency and productivity, reduce costs, explore more business opportunities, and improve mobility and agility. Due to these advantages, there has been tremendous growth in applications based on IoT across various domains (e.g., manufacturing, smart cities, smart homes, transportation, healthcare, education, supply chain management) in the past decade.

Due to the massive data generated in the wide range of applications based on IoT, several challenges such as data storage, data processing, resource management, etc. are obstructing the full potential of IoT. Big data analytics can be integrated with IoT to handle a large amount of data. Businesses can gain valuable insights from the data with the help of big data analytics. The task of big data analytics for IoT can be made simpler by extracting the most prominent features from the data generated by IoT devices, optimizing the load balancing in the network, optimizing the resource allocation, etc. Even though many researchers are working on the aforementioned issues, they are still open research problems. Metaheuristic algorithms can provide an optimal solution especially for problems with imperfect or incomplete data, or when the computational capacity is limited. These properties of metaheuristic algorithms make them an ideal solution to the aforementioned open research issues in big data for IoT applications. Examples of metaheuristic algorithms are evolutionary algorithms, nature-inspired algorithms, bio-inspired algorithms, physics-based algorithms, and swarm-based algorithms.

The aim of this Special Issue is to bring together original research focusing on the application of metaheuristic algorithms for big data analytics in IoT-based applications. Review articles discussing the state of the art are also welcome.

Potential topics include but are not limited to the following:

• Metaheuristic algorithm-based big data analytics techniques and models for IoT applications
• Metaheuristic algorithm-based big data analytics for resource allocation in IoT
• Metaheuristic algorithm-based big data analytics for load balancing in IoT-based applications
• Metaheuristic algorithm-based big data analytics for edge computing in IoT-based applications
• Metaheuristic algorithm-based big data analytics for Internet of Medical Things (IoMT)
• Metaheuristic algorithm-based big data analytics for manufacturing and production
• Deep data analytic mechanisms
• Metaheuristic algorithm-based big data analytics for E-commerce
• Metaheuristic algorithm-based big data analytics for supply chain management