Supporting Location-Based Services in a Main-Memory Database

Abstract

With the proliferation of mobile devices and explosive growth of spatio-temporal data, Location-Based Services (LBS) have become an indispensable technology in our daily lives. The key characteristics of the LBS applications include a high rate of time-stamped location updates, and many concurrent historical, present and predictive queries. The commercial providers of LBS must support all three kinds of queries and address the high update rates. While they employ relational databases for this purpose, traditional databases are unable to cope with the growing demands of many LBS systems. Support for spatio-temporal indexes within these databases are limited to R-tree based approaches. Although a number of advanced spatiotemporal indexes have been proposed by the research community, only a few of them support historical queries. These indexing techniques, with support for historical queries, are unable to sustain high update and query throughput typical in LBS.Technological trends involving increasingly large main memory and core footprints offer opportunities to address some of these issues. We present several key ideas to support high performance commercial LBS by exploiting in-memory database techniques. Taking advantage of very large memory available in modern machines, our system maintains the location data and index for the past N days in memory. Older data and index are kept in disk. We propose an in-memory storage organization for high insert performance. We also introduce a novel spatio-temporal index that maintains partial temporal indexes in a versionedgrid structure. The partial temporal indexes are organized as compressed bitmaps. With extensive evaluation, we demonstrate that our system supports high insert and query throughputs and it outperforms the leading LBS system by a significant margin.

Test Model and Coverage Analysis for Location-based Mobile Services

“…Suprio Ray presents an in-memory database technique for location-based service, and introduces a parallel spatiotemporal index to support historical, past and predictive (future) location-based queries [13] [14].…”

D-Grid: An In-Memory Dual Space Grid Index for Moving Object Databases

“…Although (tree based) in-disk indexes can be directly transfered to main memory [5], [24], [33], recent research (e.g. [24], [25], [19]) indicates that a simple, uniform grid might be the best choice for managing moving objects in main memory. Sidlauskas et.…”

“…PGrid solves problems of stale query results and wasted CPU cycles that exist in TwinGrid by careful use of light-weight locking techniques. Ray et al recently proposed PASTIS [19] which decomposes the spatial domain into grid cells and, for each grid cell, maintains a partial temporal index for moving objects that visited the cell. Updates for different grid cells are concurrently processed in separate threads.…”

“…Although many efforts have been devoted towards reducing the burden of updates for tree based indexes [3], [15], [13], [27], [37] and extend them to in-memory environments [11], [9], [24], [33], [34], [19], recent works [32], [24], [25] imply that, with in-memory settings, simple uniform grids are usually more efficient than tree based structures. The reason is that disk I/Os are eliminated for in-memory indexes, consequently, the sophisticated designs that aim to reduce disk I/O costs become cumbersome since they make update operations complicated and time consuming.…”

Seamless Guidance System Combining GPS, BLE Beacon, and NFC Technologies

“…Furthermore, the number of devices is still growing. As wireless technology continues to improve and wireless networks are ever more extensively deployed, the feasibility of developing Location-Based Services (LBS) has attracted growing interest [1]. LBS have many advantages from a user perspective, including convenience, efficiency, and fun.…”