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Performance Aspects of Distributed Caches Using TTL-Based Consistency

机译:使用基于TTL的一致性的分布式缓存的性能方面

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Web objects are stored and can be requested from numerous servers, including authoritative "origin" servers and caches. Objects can be modified only by their origin servers and weak consistency with cached copies is maintained by limiting their lifetime durations. Copies fetched from origin servers are received with maximum time-to-live (TTL) that equals their lifetime duration whereas copies obtained through a cache have shorter TTLs since their age (elapsed time since fetched from the origin) is deducted from their lifetime duration. A request served by a cache constitutes a hit if the cache has a fresh copy of the object. Otherwise, the request is considered a miss and is propagated to another server. Performance is measured by the number of requests constituting cache misses. It is evident that the number of cache misses depends on the age of the copies the cache receives. Thus, a cache that sends requests to another cache would suffer more misses than a cache that sends requests directly to an authoritative server. More subtly, the number of misses depends on the particular configuration of higher-level caches, e.g., whether one or more higher-level caches are used. Guided by practices for Web caching, we model and compare different configurations. We also analyze the effect of pre-term refreshes at high-level caches and extended lifetimes at low-level caches and reveal patterns that may seem counter-intuitive at first. Even though TTL-based consistency is very widely used, our work seems to be the first to formally analyze it. Our analysis yields insights and guidelines for improving the performance of Web caches.
机译:Web对象是可以存储的,可以从众多服务器(包括权威的“原始”服务器和缓存)中请求Web对象。只能通过其原始服务器来修改对象,并且通过限制其生存期来保持与缓存副本的弱一致性。从原始服务器获取的副本的最大生存时间(TTL)等于其生存期,而从缓存中获取的副本则具有更短的TTL,因为从它们的生存期中扣除了它们的寿命(从原始设备获取以来经过的时间)。如果高速缓存具有对象的新副本,则由高速缓存服务的请求构成命中。否则,该请求将被视为未命中,并被传播到另一台服务器。通过构成高速缓存未命中的请求数来衡量性能。显然,高速缓存未命中的数量取决于高速缓存接收的副本的期限。因此,与将请求直接发送到权威服务器的缓存相比,将请求发送到另一个缓存的缓存将遭受更多的丢失。更巧妙地,未命中的数量取决于较高级高速缓存的特定配置,例如,是否使用一个或多个较高级高速缓存。在Web缓存实践的指导下,我们对不同的配置进行建模和比较。我们还分析了高级缓存中的预刷新的影响以及低级别缓存中的延长的生存期,并揭示了乍一看似乎违反直觉的模式。即使基于TTL的一致性被广泛使用,我们的工作似乎还是第一个正式分析它的人。我们的分析为提高Web缓存的性能提供了见解和指导方针。

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