Tight Lower Bounds for Distributional Paging

Distributional paging asks for a polynomial-time eviction rule that competes with the optimal online policy OPT when requests come from a known stochastic source. Two algorithms proposed by Lund, Phillips, and Reingold [FOCS, 1994] are canonical. Their randomized dominating distribution algorithm, designed for Markov sources, draws the page to evict from any distribution over the cache obeying a family of pairwise linear inequalities; their deterministic median algorithm, designed for sources whose inter-arrival times are independent across pages, discards the cached page with the largest lower median of its conditional next-request time. The original guarantees were 4 and 5; Pabbaraju and Vakilian [ICALP 2025] recently sharpened them to 2 and 4. We show that neither sharpened constant admits further improvement in its respective source model. For Markov paging, we give two complementary factor-2 lower-bound constructions, each with an explicit polynomial-time dominating selector. A directed-cycle family has ratio 2k/(k + 1), while a recurrent four-page family with cache size three has ratio 2 − 4ε/3. Our second shows that the median algorithm fails to be c-competitive whenever c < 4 in the independent inter-arrival model. These are separate results for distinct stochastic models. Since each lower bound matches the corresponding upper bound, the two competitive ratios are 2 and 4 in their respective settings. The strongest bounds previously were 1.5907 and 1.511. The two lower bounds use different mechanisms. For the dominating distribution algorithm, the directed cycle exposes the half-mass mechanism in its cleanest form: half of the eviction mass is forced onto the page returning last, while a bad selector places the remaining half on the page returning first. The four-page construction turns the same extreme-point choice into a recurrent cascade across two slowly switching blocks. For the median algorithm, we build independent renewal processes that repeatedly mislead the median rule: the page with the latest median is nevertheless likely to be requested early, forcing a cascade of bad evictions, while a simple online policy can be made to pay arbitrarily close to one quarter as much.

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Publication Details

Journal
Rutgers University Community Repository (Rutgers University)
Published
2026-10-08
DOI
https://doi.org/10.7282/00000688
Primary Topic
Optimization and Search Problems
Type
preprint
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Tight Lower Bounds for Distributional Paging

Ali Vakilian
Rutgers University Community Repository (Rutgers University)
Optimization and Search Problems
preprint

Tight Lower Bounds for Distributional Paging

Ali Vakilian
preprint en

Abstract

Distributional paging asks for a polynomial-time eviction rule that competes with the optimal online policy OPT when requests come from a known stochastic source. Two algorithms proposed by Lund, Phillips, and Reingold [FOCS, 1994] are canonical. Their randomized dominating distribution algorithm, designed for Markov sources, draws the page to evict from any distribution over the cache obeying a family of pairwise linear inequalities; their deterministic median algorithm, designed for sources whose inter-arrival times are independent across pages, discards the cached page with the largest lower median of its conditional next-request time. The original guarantees were 4 and 5; Pabbaraju and Vakilian [ICALP 2025] recently sharpened them to 2 and 4. We show that neither sharpened constant admits further improvement in its respective source model. For Markov paging, we give two complementary factor-2 lower-bound constructions, each with an explicit polynomial-time dominating selector. A directed-cycle family has ratio 2k/(k + 1), while a recurrent four-page family with cache size three has ratio 2 − 4ε/3. Our second shows that the median algorithm fails to be c-competitive whenever c < 4 in the independent inter-arrival model. These are separate results for distinct stochastic models. Since each lower bound matches the corresponding upper bound, the two competitive ratios are 2 and 4 in their respective settings. The strongest bounds previously were 1.5907 and 1.511. The two lower bounds use different mechanisms. For the dominating distribution algorithm, the directed cycle exposes the half-mass mechanism in its cleanest form: half of the eviction mass is forced onto the page returning last, while a bad selector places the remaining half on the page returning first. The four-page construction turns the same extreme-point choice into a recurrent cascade across two slowly switching blocks. For the median algorithm, we build independent renewal processes that repeatedly mislead the median rule: the page with the latest median is nevertheless likely to be requested early, forcing a cascade of bad evictions, while a simple online policy can be made to pay arbitrarily close to one quarter as much.

Rutgers University Community Repository (Rutgers University)
Rutgers, The State University of New Jersey (US)
Optimization and Search Problems
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