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Title:JetStream: Achieving Predictable Gossip Dissemination by Leveraging Social Networks Principles
Author(s):Patel, Jay A.; Gupta, Indranil; Contractor, Noshir
Subject(s):computer science
Abstract:Gossip protocols provide probabilistic reliability and scalability, but their inherent randomness may lead to high variation in (received) message overheads at different nodes. This paper presents techniques that leverages simple social networks principles to enable nodes to select gossip targets intelligently. These simple heuristics achieve a more uniform message overhead at each node, while at the same time reducing the latency of gossip spread (by up to 25%) and also lowering the system-wide gossip network traffic. We experimentally compare our system, called JetStream, against canonical gossip as well as gossip on the Chord overlay. Intuitively, JetStream seeks to make gossip spread more deterministic and predictable, while still inheriting its scale and reliability. JetStream also provides an added benefit by reducing overall network bandwidth utilization if there is a low amount of sustained gossip injection.
Issue Date:2006-03
Genre:Technical Report
Type:Text
URI:http://hdl.handle.net/2142/11169
Other Identifier(s):UIUCDCS-R-2006-2698
Rights Information:You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the University of Illinois at Urbana-Champaign Computer Science Department under terms that include this permission. All other rights are reserved by the author(s).
Date Available in IDEALS:2009-04-20


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