Fisheye Consistency: Keeping Data in Synch in a Georeplicated World

Conference paper

DOI: 10.1007/978-3-319-26850-7_17

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9466)
Cite this paper as:
Friedman R., Raynal M., Taïani F. (2015) Fisheye Consistency: Keeping Data in Synch in a Georeplicated World. In: Bouajjani A., Fauconnier H. (eds) Networked Systems. NETYS 2015. Lecture Notes in Computer Science, vol 9466. Springer, Cham


Over the last thirty years, numerous consistency conditions for replicated data have been proposed and implemented. Popular examples include linearizability (or atomicity), sequential consistency, causal consistency, and eventual consistency. These conditions are usually defined independently from the computing entities (nodes) that manipulate the replicated data; i.e., they do not take into account how computing entities might be linked to one another, or geographically distributed. To address this lack, as a first contribution, this paper introduces the notion of proximity graph between computing nodes. If two nodes are connected in this graph, their operations must satisfy a strong consistency condition, while the operations invoked by other nodes are allowed to satisfy a weaker condition. The second contribution exploits this graph to provide a generic approach to the hybridization of data consistency conditions within the same system. We illustrate this approach on sequential consistency and causal consistency, and present a model in which all data operations are causally consistent, while operations by neighboring processes in the proximity graph are sequentially consistent. The third contribution of the paper is the design and the proof of a distributed algorithm based on this proximity graph, which combines sequential consistency and causal consistency (the resulting condition is called fisheye consistency). In doing so the paper provides a generic provably correct solution of direct relevance to modern georeplicated systems.


Asynchronous message-passing systems Broadcast Causal consistency Data replication Georeplication Linearizability  Sequential consistency 

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Roy Friedman
    • 1
  • Michel Raynal
    • 2
    • 3
  • Francois Taïani
    • 3
  1. 1.The Technion HaifaHaifaIsrael
  2. 2.Institut Universitaire de FranceParisFrance
  3. 3.IRISAUniversité de Rennes 1Rennes CedexFrance

Personalised recommendations