Meta algorithms for hierarchical Web caches

Abstract

Abstract-Large scale hierarchical caches for web content have been deployed widely in an attempt to reduce delivery delays and bandwidth consumption and also to improve the scalability of content dissemination through the world wide web. Irrespectively of the specific replacement algorithm employed in each cache, a de facto characteristic of contemporary hierarchical caches is that a hit for a document at an ¢ -level cache leads to the caching of the document in all intermediate caches (levels) on the path towards the leaf cache that received the initial request. This paper presents various algorithms that revise this standard behavior and attempt to be more selective in choosing the caches that get to store a local copy of the requested document. As these algorithms operate independently of the actual replacement algorithm running in each individual cache, they are referred to as meta algorithms. Three new meta algorithms are proposed and compared against the de facto one and a recently proposed one by H. Che, Y. Tung, and Z. Wang [1] by means of synthetic and trace-driven simulations. The best of the new meta algorithms appears to be able to lead to improved performance under most simulated scenarios, especially under a low availability of storage. The latter observation makes the presented meta algorithms particularly favorable for the handling of large data objects such as stored music files or short video clips. Additionally, a simple load balancing algorithm that is based on the concept of meta algorithms is proposed and evaluated. The algorithm is shown to be able to provide for an effective balancing of load thus possibly addressing the recently discovered "filtering-effect" in hierarchical web caches (C. Williamson [2]).

Management of scalable video streaming in information centric networking

“…By using LCD, duplicate data can be reduce on the request path. LCD is proposed in [13] for web caching. Progressive caching [14] extended the LCD to cache popular chunks only.…”

“…According to this scheme, every router caches every Data chunk that passes through it. This scheme Leave copy down This scheme was proposed in [13]. In this scheme, whenever cache hit occurs in a router, it gives a copy of the Data to the one hop down node.…”

WAVE: Popularity-based and collaborative in-network caching for content-oriented networks

“…There have been many studies to distribute files efficiently in web caches and CDNs [13], [14], [15], [16], [17]. However, they have limitations to be applied in content-oriented networks directly.…”

“…However, they have limitations to be applied in content-oriented networks directly. For instance, [13], [14], [15], [16] assume the specific topologies such as a tree or hierarchical structure. [17] assumes an explicit coordination between caches, which incurs the substantial communication and maintenance overheads.…”

“…If the requested content is cached at a C-router along the path (or discovered by content routing), the chunk will be transferred from the C-router, and the chunk request will not be forwarded towards the original server [16], [17]. 1 WAVE can be extended to support a single cache or an uncooperative cache scenario [18], which will be investigated in our future work.…”