Analyzing energy behavior of spatial access methods for memory-resident data

The proliferation of mobile and pervasive computing devices has brought energy constraints into the limelight, together with performance considerations. Energy-conscious design is important at all levels of the system architecture, and the software has a key role to play in conserving the battery energy on these devices. With the increasing popularity of spatial database applications, and their anticipated deployment on mobile devices (such as road atlases and GPS based applications), it is critical to examine the energy implications of spatial data storage and access methods for memory resident datasets. While there has been extensive prior research on spatial access methods on resource-rich environments, this is, perhaps, the first study to examine their suitability for resource-constrained environments. Using a detailed cycle-accurate energy estimation framework and four different datasets, this paper examines the pros and cons of three previously proposed spatial indexing alternatives from both the energy and performance angles. The results from this study can be beneficial to the design and implementation of embedded spatial databases, accelerating their deployment on numerous mobile devices.