Abstract
In this article, we introduce the
online service with delay
problem. In this problem, there are
n
points in a metric space that issue service requests over time, and there is a server that serves these requests. The goal is to minimize the sum of distance traveled by the server and the total delay (or a penalty function thereof) in serving the requests. This problem models the fundamental tradeoff between batching requests to improve locality and reducing delay to improve response time, which has many applications in operations management, operating systems, logistics, supply chain management, and scheduling.
Our main result is to show a poly-logarithmic competitive ratio for the online service with delay problem. This result is obtained by an algorithm that we call the
preemptive service algorithm
. The salient feature of this algorithm is a process called preemptive service, which uses a novel combination of (recursive) time forwarding and spatial exploration on a metric space. We also generalize our results to
k
> 1 servers and obtain stronger results for special metrics such as uniform and star metrics that correspond to (weighted) paging problems.
Funder
Israel Science Foundation
NSF
Publisher
Association for Computing Machinery (ACM)
Subject
Mathematics (miscellaneous)
Cited by
2 articles.
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1. The k-Server with Preferences Problem;Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures;2022-07-11
2. A Fine-Grain Batching-Based Task Allocation Algorithm for Spatial Crowdsourcing;ISPRS International Journal of Geo-Information;2022-03-17