Editing Consistency model (section)

==== Continuous consistency ====

Continuous consistency introduced by Yu and Vahdat (2000).<ref name="Continuous">{{cite journal
 | author1 = Yu, Haifeng
 | author2 = Amin Vahdat
 |   title = Design and evaluation of a continuous consistency model for replicated services.
 |    date = 2000
 | journal = Proceedings of the 4th Conference on Symposium on Operating System Design & Implementation
 |  volume = 4
 |   pages = 21
}}</ref> In this model, the consistency semantics of an application is described by using conits in the application. Since the consistency requirements can differ based on application semantics, Yu and Vahdat (2000)<ref name="Continuous"/> believe that a predefined uniform consistency model may not be an appropriate approach. The application should specify the consistency requirements that satisfy the application semantics. In this model, an application specifies each consistency requirement as a conit (abbreviation of consistency units). A conit can be a physical or logical consistency and is used to measure the consistency. Tanenbaum et al., 2007<ref name="Replica"/> describes the notion of a conit by giving an example.

There are three inconsistencies that can be tolerated by applications.

; Deviation in numerical values:<ref name="Continuous"/> Numerical deviation bounds the difference between the conit value and the relative value of the last update. A weight can be assigned to the writes which defines the importance of the writes in a specific application. The total weights of unseen writes for a conit can be defined as a numerical deviation in an application. There are two different types of numerical deviation; absolute and relative numerical deviation.
; Deviation in ordering:<ref name="Continuous"/> Ordering deviation is the discrepancy between the local order of writes in a replica and their relative ordering in the eventual final image. 
; Deviation in staleness between replicas:<ref name="Continuous"/> Staleness deviation defines the validity of the oldest write by bounding the difference between the current time and the time of the oldest write on a conit not seen locally. Each server has a local queue of uncertain write that is required an actual order to be determined and applied on a conit. The maximal length of uncertain writes queue is the bound of ordering deviation. When the number of writes exceeds the limit, instead of accepting new submitted write, the server will attempt to commit uncertain writes by communicating with other servers based on the order that writes should be executed.

If all three deviation bounds are set to zero, the continuous consistency model is the strong consistency.