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Title: Corona: A High Performance Publish-Subscribe System for the World Wide Web
Authors: Ramasubramanian, Venugopalan
Peterson, Ryan
Sirer, Emin Gun
Keywords: computer science
technical report
Issue Date: 29-Nov-2005
Publisher: 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 naive polling for update detection leads to poor performance and limits scalability, as clients do not detect updates quickly and servers face high loads imposed by active polling. This paper describes Corona, a publish-subscribe system for the Web that 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 them quickly to the clients. A distributed optimization engine ensures that Corona achieves the best update performance without exceeding load limits on content servers. Large scale simulations and measurements from Planet-Lab deployment, described in this paper, demonstrate that Corona achieves orders of magnitude improvement in update performance at a modest cost.
Appears in Collections:Computing and Information Science Technical Reports

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