> For the complete documentation index, see [llms.txt](https://ret2basic.gitbook.io/ctfnote/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ret2basic.gitbook.io/ctfnote/computer-science/distributed-systems/consistency-and-replication/client-centric-consistency.md).

# Client-centric Consistency

Monotonic Reads + Monotonic Writes + Read Your Writes + Writes Follow Reads

## Data-centric vs. Client-centric

* **Data-centric consistency models** aim at providing a system-wide consistent view on a **data store**.
  * An important **assumption** is that concurrent processes may be **simultaneously** updating the data store, and that it is necessary to provide consistency in the face of such concurrency.
* **Client-centric consistency models** provide guarantees for **a single client** concerning the consistency of accesses to a data store by that client.
  * No guarantees are given concerning concurrent accesses by **different clients**.
  * It assumes **no simultaneous updates** to the data store or they

    can be relatively easily resolved

## Notations

* Let $$x\_i$$ and $$x\_j$$ be the **versions** of data item $$x$$.
* Version $$x\_i$$ is the result of a series of write operations, which is denoted as the **write set** $$WS(x\_i)$$.
* $$WS(x\_i;x\_j)$$ means $$x\_j$$ **follows from** $$x\_i$$ ($$x\_j$$ is obtained from $$x\_i$$ plus some write operations). 
* $$WS(x\_i|x\_j)$$ means **we do not know if** $$x\_j$$ **follows from** $$x\_i$$.

## Model 1: Monotonic Reads

> If a process reads the value of a data item $$x$$, any successive read operation on $$x$$ by that process will always return that same value or a more recent value.

* **In other words, monotonic-read consistency guarantees that once a process has seen a value of** $$x$$**, it will never see an older version of** $$x$$**.**
* **Use case: distributed email database**
  * A user reads his email in San Francisco.
  * He later flies to New York and opens his mailbox again.
  * The messages that were in the mailbox in San Francisco

    will also be in the mailbox when it is opened in New York.
* **Important: study the example in Textbook Section 7.3 Figure 7.16.**

## Model 2: Monotonic Writes

> A write operation by a process on a data item $$x$$ is completed before any successive write operations on $$x$$ by the same process.

* **Monotonic-write consistency guarantees that write operations by the same process are propagated in the correct order to all copies of the data store.**
* If we have two successive operations $$W\_k(x\_i)$$ and $$W\_k(x\_j)$$ by process $$P\_k$$, then, regardless where $$W\_k(x\_j)$$ takes place, we also have $$WS(x\_i;x\_j)$$.
* **Use case: software library**
  * Each update replaces one or more functions, leading to a **next version**.
  * Monotonic-write consistency guarantee that if an update is performed on a copy of the library, **all preceding updates will be performed first**.
  * The resulting library is indeed the **most recent version** and includes all updates that have led to previous versions of the library.
* **Important: study the example in Textbook Section 7.3 Figure 7.17.**

## Model 3: Read Your Writes

> The effect of a write operation by a process on data item $$x$$ will always be seen by a successive read operation on $$x$$ by the same process.

* **In other words, a write operation is always completed before a successive read operation by the same process, no matter where that read operation takes place.**
* **Use case: Web documents**
  * A user updates a Web document using an editor.
  * He then checks the result from a Web browser.
  * Read-your-writes consistency guarantees that the browser’s or the server’s cache is invalidated when the page is updated.
  * So he can see the updated file instead of cached copy of the original file.
* **Important: study the example in Textbook Section 7.3 Figure 7.18.**

## Model 4: Writes Follow Reads

> A write operation by a process on a data item $$x$$ following a previous read operation on $$x$$ by the same process is guaranteed to take place on the same or a more recent value of $$x$$ that was read.

* **In other words, any successive write operation by a process on a data item** $$x$$ **will be performed on a copy of** $$x$$ **that is up to date with the value most recently read by that process.**
* **Use case: network newsgroup**
  * A user first reads an article $$A$$.
  * Then she reacts by posting a response $$B$$.
  * By requiring writes-follow-reads consistency, B will be written to any copy of the newsgroup only after A has been written as well.
  * Users see a posting of a reaction to an article only after they have seen the original article.
* **Important: study the example in Textbook Section 7.3 Figure 7.19.**