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Journal Articles Computer Networks Year : 2017

Fair throughput allocation in Information-Centric Networks

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Abstract

Cache networks are the cornerstones of today's Internet, helping it to scale by an extensive use of Content Delivery Networks (CDN). Benefiting from CDN's successful insights, ubiquitous caching through Information-Centric Networks (ICN) is increasingly regarded as a premier future Internet architecture contestant. However, the use of in-network caches seems to cause an issue in the fairness of resource sharing among contents. Indeed, in legacy communication networks, link buffers were the principal resources to be shared. Under max-min flow-wise fair bandwidth sharing [14], content throughput was not tied to content popularity. Including caches in this ecosystem raises new issues since common cache management policies such as probabilistic Least Recently Used (p-LRU) or even more, Least Frequently Used (LFU), may seem detrimental to low popularity objects, even though they significantly decrease the overall link load [3]. In this paper, we demonstrate that globally achieving LFU is a first stage of content-wise fairness. Indeed, any investigated content-wise α-fair throughput allocation permanently stores the most popular contents in network caches by ensuring them a cache hit ratio of 1. As ICN caching traditionally pursues LFU objectives, content-wise fairness specifics remain only a matter of fair bandwidth sharing, keeping the cache management intact.
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Dates and versions

hal-01590684 , version 1 (20-09-2017)

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Thomas Bonald, Léonce Mekinda, Luca Muscariello. Fair throughput allocation in Information-Centric Networks. Computer Networks, 2017, 125, pp.122 - 131. ⟨10.1016/j.comnet.2017.05.019⟩. ⟨hal-01590684⟩
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