Causality tracking in causal message-logging protocols

  • Authors:

  • Lorenzo Alvisi;Karan Bhatia;Keith Marzullo

  • Affiliations:

  • The University of Texas at Austin, Department of Computer Sciences, Austin, Texas;Entropia Inc., La Jolla, California;University of California, San Diego, Department of Computer Science and Engineering, La Jolla, CA

  • Venue:
  • Distributed Computing
  • Year:
  • 2002

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Abstract

Casual message-logging protocols have several attractive properties: they introduce no blocking, send no additional messages over those sent by the application, and never create orphans. Causal message logging, however, does require the casual effects of the deliveries of messages to be tracked. The information concerning causality tracking is piggybacked on application messages, and the amount of such information can become large.In this paper we study the cost of tracking causality in causal message-logging protocols. One can track causality as accurately as possible, but to do so requires piggybacking a considerable amount of additional information. One can reduce the amount of piggybacked information on each message by reducing the accuracy of causality tracking. But then, causal message logging may piggyback the reduced amount of information on more messages.We specify six different methods of tracking causality, each representing a natural choice based on the specification of causal message logging. We describe how these six methods can be implemented and compare them in terms of how large of a piggyback load they impose. This load depends on the application that is using causal message logging. We characterize some applications for which a given method has the smallest piggyback load, and study using simulation the size of the piggyback load for two different models of applications.