DiSCO: A Distributed Semantic Cache Overlay for Location-Based Services

Location-based services (LBS) have gained tremendous popularity with millions of simultaneous users daily. LBS handle very large data volumes and face enormous query loads. Both the data and the queries possess high locality: spatial data is distributed very unevenly around the globe, query load is different throughout the day, and users often search for similar things in the same places. This causes high load peaks at the data tier of LBS, which may seriously degrade performance. To cope with these load peaks, we present DiSCO, a distributed semantic cache overlay for LBS. DiSCO exploits the spatial, temporal and semantic locality in the queries of LBS and distributes frequently accessed data over many nodes. Based on the Content-Addressable Network (CAN) peer-to-peer approach, DiSCO achieves high scalability by partitioning data using spatial proximity. Our evaluation shows that DiSCO significantly reduces queries to the underlying data tier.