NSDI '06 — Abstract
Pp. 15–28 of the Proceedings
Corona: A High Performance Publish-Subscribe System for the World
Wide Web
Venugopalan Ramasubramanian, Ryan Peterson, and Emin Gün Sirer,
Cornell University
Abstract
Despite the abundance of frequently changing information, the Web
lacks a publish-subscribe interface for delivering updates to
clients. The use of naïve polling for detecting updates leads to
poor performance and limited scalability as clients do not detect
updates quickly and servers face high loads imposed by active
polling. This paper describes a novel publish-subscribe system
for the Web called Corona, which provides high performance and
scalability through optimal resource allocation. Users register
interest in Web pages through existing instant messaging services.
Corona monitors the subscribed Web pages, detects updates
efficiently by allocating polling load among cooperating peers, and
disseminates updates quickly to users. Allocation of resources
for polling is driven by a distributed optimization engine that
achieves the best update performance without exceeding load limits
on content servers. Large-scale simulations and measurements from
PlanetLab deployment demonstrate that Corona achieves orders of
magnitude improvement in update performance at a modest cost.
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