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Probabilistic Caching as Mixed Strategies in Spatially-Coupled Edge Caching

Authors: Jie Gao; Lian Zhao; Limin Sun;

Probabilistic Caching as Mixed Strategies in Spatially-Coupled Edge Caching

Abstract

The problem of probabilistic caching in a network with multiple edge nodes and user nodes is studied. Files with different lengths, caches with different sizes, and spatial coupling through overlapping service areas are considered. The connection between caching probabilities and strategy-mixing probabilities in a mixed strategy is characterized. It is found that a given set of caching probabilities for an edge node can correspond to more than one mixed strategies. Through this characterization, caching probabilities can be decomposed into pure caching strategies and corresponding strategy-mixing probabilities. Moreover, the best-response caching strategy of an EN is studied and obtained based on the spatial-coupling discounted file preference level. The impact of information availability and request scenario on the best-response strategy is analyzed. Numeric examples demonstrate the best-response strategy and the decomposition of the caching probabilities into pure strategies and strategy-mixing probabilities.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
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