Multiple Wide Tables with Vertical Scalability in Multitenant Sensor Cloud Systems

Abstract

Software-as-a-service (SaaS) has emerged as a new computing paradigm to provide reliable software on demand. With such an inspiring motivation, sensor cloud system can benefit from this infrastructure. Generally, sharing database and schema is the most commonly used data storage model in the cloud. However, the data storage of tenants in the cloud is approaching schema null and evolution issues. To address these limitations, this paper proposes multitenant multiple wide tables with vertical scalability by analyzing the features of multitenant data. To solve schema null issue, extended vertical part is used to trim down the amount of schema null values. To reduce probability of schema evolution, wide table is divided into multiple clusters that we called multiple wide tables. This design reaches the balance between tenant customizing and its performance. Besides, the partition and correctness of multiple wide tables with vertical scalability are discussed in detail. The experimental results indicate that the solution of our multiple wide tables with vertical scalability is superior to single wide table, and single wide table with vertical scalability in the aspects of spatial intensity and read performance.