Window‐LRFU: a cache replacement policy subsumes the LRU and window‐LFU policies

Abstract

SUMMARYReplacement algorithms have been widely used as key technologies for cache management in areas such as file systems or database management. A replacement algorithm determines which page to be evicted when the cache is full and a new page is referenced. Because replacement policies considering only recency or frequency such as LRU (Least Recently Used) and LFU (Least Frequently Used) do not perform well, replacement polices that take both recency and frequency into account have been intensively studied. As a classical replacement policy, LRFU (Least Recently/Frequently Used) policy subsumes the LRU and LFU policy. However, because LFU is not able to adapt to the change of page accessing pattern and it is hard to select a suitable λ for each certain trace, LRFU cannot always guarantee a good performance. In this paper, we propose a Window-LRFU policy, to subsume the LRU and Window-LFU policies. Experimental results show that the Window-LRFU policy outperforms LRFU and has at least competitive performance than other classical algorithms.

Estimating Video Popularity From Past Request Arrival Times in a VoD System

“…While the LFU method captures long-term popularity of objects, it responds poorly to changes in user demand as it does not emphasize recent history over earlier reports. Since LFU cannot distinguish between requests that occurred recently with requests that occurred significantly earlier, it can incorrectly identify many ''has-beens'' as popular objects because of their high request count in the past [20], [22]. For example, when the LFU method is used, earlier episode of a drama series that is no longer popular might remain in the cache for a long time.…”

“…Also, when carrying out the content pre-placement or cache replacement, content providers may have certain preferences over short-term versus long-term popularity, depending on the schedule with which they introduce new videos into the library and the sizes of their servers. For example, if small caches are used to handle errors in demand prediction, then a cache replacement policy such as the LRU is preferred [22]. On the other hand, the LFU policy is shown to work well for proxy caching environments that are aimed to offload the demand in central VoD servers [22], [24].…”

“…For example, if small caches are used to handle errors in demand prediction, then a cache replacement policy such as the LRU is preferred [22]. On the other hand, the LFU policy is shown to work well for proxy caching environments that are aimed to offload the demand in central VoD servers [22], [24]. Both LFU and LRU popularity estimation methods have less flexibility to adjust to varying requirements.…”