A learning technique for VM allocation to resolve geospatial queries

Abstract

© Springer Nature Singapore Pte Ltd. 2019 Provisioning of virtual machines for efficient geospatial query management on cloud is an interesting and challenging work. The aim of this paper is to distribute workloads of different types of spatial queries into suitable virtual machine efficiently. To increase the effectiveness of the system serving geospatial queries, we use real-time geospatial query pattern learning methodology. This methodology is used to train the application specific properties, and the system will learn which type of the geospatial query should be allocated to what type of virtual machine automatically. The learning methodology gives knowledge about the resource required ..