3D geospatial data are being progressively adopted in urban land administration to represent 3D ownership rights in multistorey buildings. The integrity of urban land administration highly depends on the validity and quality of cadastral data. However, a large portion of research deals with the conceptual principles of internal and external spatial consistencies of 3D cadastral data. This article integrates the principles in practice and develops methods to check the validity of 3D parcels and their relationships in complex ownership settings. To evaluate the methods, this research adopts a case study using an 18-floor multistorey building with 248 lots and three types of common properties. The ownership rights of this building are delineated as polyhedral surface models, including non-2-manifold and non-simple polyhedra, and evaluated by implemented principles. The results reveal that the integrated methods can identify 3D cadastral errors, overlaps and gaps. The developed integrated approach can significantly advance urban land administration, as it facilitates complex 3D cadastral data validation.

The growth of telecommunication technologies, especially 5G, the growing popularity of smart mobile devices, the emergence of smart cities and Internet of Things (IoT), and the easy use of these equipments have led the cloud users to utilize their various services. Real-time applications and the use of big data have caused cloud service providers (CSPs) to move their servers to the edge of the network and in the vicinity of users to maintain the quality of their services. For this purpose, the concept of mobile-edge computing (MEC) was formed. Applications often have heavy computing complexity on mobile devices or require a lot of data to process. Moreover, in order to save energy consumption of the batteries of this equipment, offloading them on the network resources can transfer the computational complexity from the users’ equipment to the network resources. The resource placement (RP) is one of the major challenges in this area. Improper resource topology upsets their load balancing and increases access latency. In the proposed method of this article, the cellular mobile network is divided into smaller areas and using the coral reefs optimization (CRO) algorithm, the optimal placement of resources in each of these areas will be locally performed. The deep$Q$-network (DQN) and Markov game (MG) are used to optimize global RP to reduce global latency and to improve resource load balancing as its two objectives. The results of the experiments show that the proposed method has significantly improved its objectives and server’s energy efficiency, compared to some similar works in this area.