RetroRenting: An Online Policy for Service Caching at the Edge
V S Ch Lakshmi Narayana, Sharayu Moharir, Nikhil Karamchandani

TL;DR
RetroRenting is an online policy for service caching at the edge that outperforms traditional TTL policies, offering near-optimal performance across various stochastic and adversarial request scenarios.
Contribution
The paper introduces RetroRenting, an online policy that is order-optimal in competitive ratio and performs well under stochastic arrivals, improving upon TTL policies for edge service caching.
Findings
RetroRenting outperforms TTL policies in adversarial and stochastic settings.
RR is order-optimal among deterministic online policies.
Simulations show RR's near-optimal performance with real-world traces.
Abstract
The rapid proliferation of shared edge computing platforms has enabled application service providers to deploy a wide variety of services with stringent latency and high bandwidth requirements. A key advantage of these platforms is that they provide pay-as-you-go flexibility by charging clients in proportion to their resource usage through short-term contracts. This affords the client significant cost-saving opportunities, by dynamically deciding when to host its service on the platform, depending on the changing intensity of requests. A natural policy for our setting is the Time-To-Live (TTL) policy. We show that TTL performs poorly both in the adversarial arrival setting, i.e., in terms of the competitive ratio, and for i.i.d. stochastic arrivals with low arrival rates, irrespective of the value of the TTL timer. We propose an online policy called RetroRenting (RR) and show that…
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Taxonomy
TopicsOptimization and Search Problems · Caching and Content Delivery · IoT and Edge/Fog Computing
