Skip to Main content Skip to Navigation
New interface
Reports (Research report)

Cache Policies for Linear Utility Maximization

Abstract : Cache policies to minimize the content retrieval cost have been studied through competitive analysis when the miss costs are additive and the sequence of content requests is arbitrary. More recently, a cache utility maximization problem has been introduced, where contents have stationary popularities and utilities are strictly concave in the hit rates. This paper bridges the two formulations, considering linear costs and content popularities. We show that minimizing the retrieval cost corresponds to solving an online knapsack problem, and we propose new dynamic policies inspired by simulated annealing, including DynqLRU, a variant of qLRU. For such policies we prove asymptotic convergence to the optimum under the characteristic time approximation. In a real scenario, popularities vary over time and their estimation is very difficult. DynqLRU does not require popularity estimation, and our realistic, trace-driven evaluation shows that it significantly outperforms state-of-the-art policies, with up to 45% cost reduction.
Document type :
Reports (Research report)
Complete list of metadata

Cited literature [37 references]  Display  Hide  Download
Contributor : Giovanni Neglia Connect in order to contact the contributor
Submitted on : Tuesday, January 31, 2017 - 6:59:59 PM
Last modification on : Wednesday, October 26, 2022 - 8:15:09 AM
Long-term archiving on: : Monday, May 1, 2017 - 5:18:25 PM


Files produced by the author(s)


  • HAL Id : hal-01442693, version 2


Giovanni Neglia, Damiano Carra, Pietro Michiardi. Cache Policies for Linear Utility Maximization. [Research Report] RR-9010, Inria Sophia Antipolis. 2017. ⟨hal-01442693v2⟩



Record views


Files downloads