Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
144 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Caching with Time Domain Buffer Sharing (1804.02797v1)

Published 9 Apr 2018 in cs.IT and math.IT

Abstract: In this paper, storage efficient caching based on time domain buffer sharing is considered. The caching policy allows a user to determine whether and how long it should cache a content item according to the prediction of its random request time, also referred to as the request delay information (RDI). In particular, the aim is to maximize the caching gain for communications while limiting its storage cost. To achieve this goal, a queueing theoretic model for caching with infinite buffers is first formulated, in which Little's law is adopted to obtain the tradeoff between the hit ratio and the average buffer consumption. When there exist multiple content classes with different RDIs, the storage efficiency is further optimized by carefully allocating the storage cost. For more practical finite-buffer caching, a $G/GI/L/0$ queue model is formulated, in which a diffusion approximation and Erlang-B formula are adopted to determine the buffer overflow probability and the corresponding hit ratio. The optimal hit ratio is shown to be limited by the demand probability and buffer size for large and small buffers respectively. In practice, a user may exploit probabilistic caching with random maximum caching time and arithmetic caching without any need for content arrival statistics to efficiently harvest content files in air.

Citations (18)

Summary

We haven't generated a summary for this paper yet.