While CPU caches are usually entirely managed by hardware, a variety of software manages other caches. The main memory page, which is an example of the hard drive, is managed by the operating system. In the case of Lesecaches, a data item must have been retrieved at least once from its storage location to allow subsequent reading operations of the data element to improve performance, since it can be retrieved from the cache (faster) and not from the location of the data. For writing cards, it is possible to achieve an improvement in performance when writing a data item when the data element is first written, because the data element is immediately stored in the cache, which delays the transfer of the data element into the memory at a later date or as a background process. Unlike the strict buffer, a hiding process must be consistent with a cache consistency protocol (potentially distributed) to maintain consistency between the cache and the location of the data. On the other hand, in the case of the buffer, search engines often provide websites that they have indexed from their cache. Google, for example, provides a „Cached“ link in addition to each search result. This can be useful if a web server cannot temporarily or permanently access websites. A cache consists of a pool of entrances. Each input is associated with data that is a copy of the same data in a backup storage. Each entry also has a day indicating the identity of the data in the backup memory, which is a copy of the entry. Tagging allows simultaneous cache-oriented algorithms to operate in multiple layers without differential interference. It is recommended to use the Cache-Contracts approach: it requires fewer code plates and offers a default cache buffer.
The „Least Frequent Recently Used“ (LFRU) cache replacement scheme combines the benefits of LFU and LRU schemes. LFRU is suitable for „network“ cache applications, such.B as IcN (information network), content distribution networks (CDNs) and distributed networks in general. In LFRU, the cache is divided into two partitions called preferred and non-preferred partitions. The preferred partition can be defined as a protected partition. If the content is very popular, it is moved to the preferred partition. Replacing the preferred score is as follows: LFRU removes the content from the unprivileged score, moves the content from a preferred score to an unprivileged score, and inserts new content into the preferred score. In the above procedure, the LRU is used for preferred partition and an LFU (ALFU) diagram approached for the non-preferred partition, hence the abbreviation LFRU. The basic idea is to filter locally popular content with ALFU and put popular content on one of the preferred scores.
Since no data is returned to the analyzer during the writing process, writing errors must be decided if the data is loaded into the cache.