Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems
Journal of Parallel and Distributed Computing
A prediction-based fair replication algorithm in structured P2P systems
ATC'07 Proceedings of the 4th international conference on Autonomic and Trusted Computing
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Flash crowds, which result from the sudden increase in popularity of some online content, are among the most important problems that plague today's Internet. Affected servers are overloaded with requests and quickly become "hot spots." They usually suffer from severe performance failures or stop providing service altogether, as there are scarcely any effective techniques to scalably deliver content under hot spot conditions to all requesting clients. Inthis paper, we propose and evaluate collaborative techniques to detect and proactively avoid the occurrence of hot spots. Using our mechanisms, groups of small- to medium-sized Web servers can team up to withstand unexpected surges of requests in a cost-effective manner. Once a Web server detects a sudden increase in request traffic, it replicateson-the-fly the affected content on other Web servers; subsequent requests are transparently redirected to the copies to offload the primary server. Each server acts both as a primary source for its own content, and as a secondary source for other servers' content in the event of a flash-crowd; scalability and dependability are therefore achieved in a peer-to-peer fashion, with each peer contributing to, and benefiting from, the service. Our proactive hot spot avoidance techniques are implemented as a module for the popular Apache Web server. We have conducted a comprehensive experimental evaluation, which demonstrates that our techniques are effective at dealing with flash crowds and scaling to very high request loads.