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The Internet of Things (IoT) is the concept of everyday objects that make us live in the era of the IoT. The spatial characteristics of things around us can be considered the reins of the IoT operability. In other words, the spatial variation of a thing can be the core of the IoT reaction. For example, the spatial variation in crop indicates the requirement and characteristic of agriculture production. Also, the spatial variation of a human movement can alarm the security and monitoring systems. This issue agitates the contemplating of the ''Internet of Spatial Things (IoST)'' concept. For the first time, this paper draws an inspiration towards the perspective vision of the IoST, which is concerned with revise IoT with the spatial perspective. The IoST concept is argued by the presentation of its definition and architectural components. Besides, the IoST layers are discussed in details. Furthermore, a new proposed reference model of the IoST is proposed. Finally, the new trends and open issues regarding the IoST are aroused. INDEX TERMS Internet of Things (IoT), Internet of Spatial Things (IoST), spatial, framework.

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Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre -including this research content -immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

Purpose The purpose of this paper is to present a comparison between two well-known Lévy-based meta-heuristics called cuckoo search (CS) and flower pollination algorithm (FPA). Design/methodology/approach Both the algorithms (Lévy-based meta-heuristics called CS and Flower Pollination) are tested on selected benchmarks from CEC 2017. In addition, this study discussed all CS and FPA comparisons that were included implicitly in other works. Findings The experimental results show that CS is superior in global convergence to the optimal solution, while FPA outperforms CS in terms of time complexity. Originality/value This paper compares the working flow and significance of FPA and CS which seems to have many similarities in order to help the researchers deeply understand the differences between both algorithms. The experimental results are clearly shown to solve the global optimization problem.