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Gossip-based aggregation in large dynamic networks (2005)
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| Venue: | ACM TRANS. COMPUT. SYST |
| Citations: | 268 - 41 self |
BibTeX
@ARTICLE{Jelasity05gossip-basedaggregation,
author = {Márk Jelasity and Alberto Montresor and Ozalp Babaoglu},
title = {Gossip-based aggregation in large dynamic networks},
journal = {ACM TRANS. COMPUT. SYST},
year = {2005},
volume = {23},
number = {3},
pages = {219--252}
}
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Abstract
As computer networks increase in size, become more heterogeneous and span greater geographic distances, applications must be designed to cope with the very large scale, poor reliability, and often, with the extreme dynamism of the underlying network. Aggregation is a key functional building block for such applications: it refers to a set of functions that provide components of a distributed system access to global information including network size, average load, average uptime, location and description of hotspots, and so on. Local access to global information is often very useful, if not indispensable for building applications that are robust and adaptive. For example, in an industrial control application, some aggregate value reaching a threshold may trigger the execution of certain actions; a distributed storage system will want to know the total available free space; load-balancing protocols may benefit from knowing the target average load so as to minimize the load they transfer. We propose a gossip-based protocol for computing aggregate values over network components in a fully decentralized fashion. The class of aggregate functions we can compute is very broad and includes many useful special cases such as counting, averages, sums, products, and extremal values. The protocol is suitable for extremely large and highly dynamic systems due to its proactive structure—all nodes receive the aggregate value continuously, thus being able to track
Keyphrases
large dynamic network gossip-based aggregation aggregate value global information dynamic system key functional building block network size gossip-based protocol average load distributed system access storage system building application computer network load-balancing protocol certain action many useful special case total available free space extremal value geographic distance proactive structure industrial control application extreme dynamism large scale network component aggregate function underlying network local access poor reliability target average load
