A coordinates-based hierarchical computing framework towards spatial data processing

Abstract

The vehicle-based mobile base station (VMBS) has been developed by NTT a few years ago, which plays an important role in reconstructing an emergency communication network by integrating with mobile edge computing to support the cloud service for data pre-processing tasks. Spatial data processing refers to characteristics, such as fast-changing, massive, and potentially infinite. Considering the capacities of network bandwidth and storage of VMBS, new challenging issues have emerged such as how to quantify information loss and how to optimize data processing in the paradigm of mobile edge computing. To address these two challenges, we design a coordinates-based hierarchical computing framework for spatial data processing, named HierCom. Using HierCom, the optimal position of VMBS can be selected to decrease the transmission delay, thereby reducing information loss in the data processing in an edge computing environment. Furthermore, we also propose a near least neighbor-based algorithm to optimize the information loss. Finally, simulations on the real-world dataset show that the information loss of our method is reduced by 27% compared with the baseline method.