Title :
PUBSUB: An efficient publish/subscribe system
Author :
Mishra, Tania Banerjee ; Sahni, Shashank
Author_Institution :
Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
PUBSUB is a versatile, efficient, and scalable publish/subscribe system. This paper describes the architecture of PUBSUB together with some of its current capabilities. A version of PUBSUB optimized for event processing was benchmarked against the publish/subscribe systems BE-Tree and Siena, which also are optimized for event processing. PUBSUB processes events faster than Siena and BE-tree. On our tests, the speedup of the fastest version of PUBSUB relative to Siena was 98% on an average. The speedup range relative to BE-Tree was from 1.23 to 1.48 and averaged 1.36 on the uniform tests and PUBSUB was comparable to BE-tree on the Zipf tests. The faster times in PUBSUB were a result of very efficient data structures used in PUBSUB to store the subscriptions, and the fast matching algorithms developed to match events to subscriptions.
Keywords :
data structures; fault trees; message passing; middleware; BE-tree; PUBSUB; data structures; event processing; matching algorithms; scalable publish/subscribe system; Abstracts; Artificial intelligence; Bismuth; Data structures; Indexes; Single photon emission computed tomography; Subscriptions; Boolean expressions; Content based publish/subscribe; efficient subscription matching;
Conference_Titel :
Computers and Communications (ISCC), 2013 IEEE Symposium on
Conference_Location :
Split
DOI :
10.1109/ISCC.2013.6755014