Design of a Location-based Publish/Subscribe Service using a Graph-based Computing Model

Abstract

We present here the initial results of our investigation of a system architecture for location-based publish/subscribe services utilizing a graph-based model for managing data and computations. This architecture is implemented on a cluster computer using the facilities and the computation model provided by the Beehive framework which supports a transactional model of parallel computing on dynamic graph data structures. We implemented a Museum Visitor Service as an example of a location-based publish/subscribe system to study and evaluate the performance this approach. This service includes features utilizing location-based publish/subscribe functions for supporting coordination and collaboration among members in a social group visiting the museum. We implemented a testbed system for this service and evaluated its performance on a cluster computer. Our work also illustrates that weaker consistency models for transactions can be utilized in such services to achieve higher performance and scalability.