TY - JOUR
T1 - Delta
T2 - Scalable data dissemination under capacity constraints
AU - Karanasos, Konstantinos
AU - Katsifodimos, Asterios
AU - Manolescu, Ioana
PY - 2013
Y1 - 2013
N2 - In content-based publish-subscribe (pub/sub) systems, users express their interests as queries over a stream of publications. Scaling up content-based pub/sub to very large numbers of subscriptions is challenging: users are interested in low latency, that is, getting subscription results fast, while the pub/sub system provider is mostly interested in scaling, i.e., being able to serve large numbers of subscribers, with low computational resources utilization. We present a novel approach for scalable content-based pub/sub in the presence of constraints on the available CPU and network resources, implemented within our pub/sub system Delta. We achieve scalability by off-loading some subscriptions from the pub/sub server, and leveraging view-based query rewriting to feed these subscriptions from the data accumulated in others1. Our main contribution is a novel algorithm for organizing views in a multi-level dissemination network, exploiting view-based rewriting and powerful linear programming capabilities to scale to many views, respect capacity constraints, and minimize latency. The efficiency and effectiveness of our algorithm are confirmed through extensive experiments and a large deployment in a WAN.
AB - In content-based publish-subscribe (pub/sub) systems, users express their interests as queries over a stream of publications. Scaling up content-based pub/sub to very large numbers of subscriptions is challenging: users are interested in low latency, that is, getting subscription results fast, while the pub/sub system provider is mostly interested in scaling, i.e., being able to serve large numbers of subscribers, with low computational resources utilization. We present a novel approach for scalable content-based pub/sub in the presence of constraints on the available CPU and network resources, implemented within our pub/sub system Delta. We achieve scalability by off-loading some subscriptions from the pub/sub server, and leveraging view-based query rewriting to feed these subscriptions from the data accumulated in others1. Our main contribution is a novel algorithm for organizing views in a multi-level dissemination network, exploiting view-based rewriting and powerful linear programming capabilities to scale to many views, respect capacity constraints, and minimize latency. The efficiency and effectiveness of our algorithm are confirmed through extensive experiments and a large deployment in a WAN.
UR - http://www.scopus.com/inward/record.url?scp=84897001759&partnerID=8YFLogxK
U2 - 10.14778/2732240.2732241
DO - 10.14778/2732240.2732241
M3 - Article
AN - SCOPUS:84897001759
VL - 7
SP - 217
EP - 228
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 4
ER -