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.
A. Tripathi and H. Hoang, "Design of a Location-based Publish/Subscribe Service using a Graph-based Computing Model," 2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC), DOI: 10.1109/CIC.2017.00024
IEEE International Conference on Collaboration and Internet Computing (CIC)
This paper presents a graph-based model for building broker architectures in location-based publish-subcribe systems. This work is based on the Beehive parallel programming platform for graph problems.
National Science Foundation
Tripathi, Anand; Hoang, Henry.
Design of a Location-based Publish/Subscribe Service using a Graph-based Computing Model.
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