Online Partial Service Hosting at the Edge

TL;DR

This paper introduces an online policy for partially hosting services at the edge, optimizing costs by dynamically adjusting the fraction of service hosted based on request patterns and rent costs.

Contribution

It proposes the $ ext{ extalpha}$-RetroRenting ($ ext{ extalpha}$-RR) policy for partial service hosting and provides theoretical bounds on its performance compared to an optimal offline solution.

Findings

$ ext{ extalpha}$-RR achieves near-optimal cost efficiency in various scenarios.

Partial hosting significantly reduces costs compared to full hosting.

Numerical results validate the effectiveness of the proposed policy.

Abstract

We consider the problem of service hosting where an application provider can dynamically rent edge computing resources and serve user requests from the edge to deliver a better quality of service. A key novelty of this work is that we allow the service to be hosted partially at the edge which enables a fraction of the user query to be served by the edge. We model the total cost for (partially) hosting a service at the edge as a combination of the latency in serving requests, the bandwidth consumption, and the time-varying cost for renting edge resources. We propose an online policy called $\alpha$-RetroRenting ($\alpha$-RR) which dynamically determines the fraction of the service to be hosted at the edge in any time-slot, based on the history of the request arrivals and the rent cost sequence. As our main result, we derive an upper bound on $\alpha$-RR's competitive ratio with respect to the offline optimal policy that knows the entire request arrival and rent cost sequence in advance. We conduct extensive numerical evaluations to compare the performance of $\alpha$-RR with various benchmarks for synthetic and trace-based request arrival and rent cost processes, and find several parameter regimes where $\alpha$-RR's ability to store the service partially greatly improves cost-efficiency.