Self-adjusting Advertisement of Cache Indicators with Bandwidth Constraints
Itamar Cohen, Gil Einziger, Gabriel Scalosub

TL;DR
This paper introduces a self-adjusting algorithm for cache advertisement strategies that optimizes access cost and bandwidth without prior knowledge, adapting to various parameters and workloads.
Contribution
It presents a novel adaptive algorithm that dynamically selects cache advertisement policies without requiring prior configuration or workload knowledge.
Findings
Achieves near-optimal cost comparable to the best static configuration
Works effectively across multiple cache policies and real workloads
Does not require prior information about cache or workload parameters
Abstract
Cache advertisements reduce the access cost by allowing users to skip the cache when it does not contain their datum. Such advertisements are used in multiple networked domains such as 5G networks, wide area networks, and information-centric networking. The selection of an advertisement strategy exposes a trade-off between the access cost and bandwidth consumption. Still, existing works mostly apply a trial-and-error approach for selecting the best strategy, as the rigorous foundations required for optimizing such decisions is lacking. Our work shows that the desired advertisement policy depends on numerous parameters such as the cache policy, the workload, the cache size, and the available bandwidth. In particular, we show that there is no ideal single configuration. Therefore, we design an adaptive, self-adjusting algorithm that periodically selects an advertisement policy. Our…
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