The preemptive resource allocation problem

Kanthi Sarpatwar, Baruch Schieber, Hadas Shachnai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We revisit a classical scheduling model to incorporate modern trends in data center networks and cloud services. Addressing some key challenges in the allocation of shared resources to user requests (jobs) in such settings, we consider the following variants of the classic resource allocation problem (RAP). The input to our problems is a set J of jobs and a set M of homogeneous hosts, each has an available amount of some resource. A job is associated with a release time, a due date, a weight and a given length, as well as its resource requirement. A feasible schedule is an allocation of the resource to a subset of the jobs, satisfying the job release times/due dates as well as the resource constraints. A crucial distinction between classic RAP and our problems is that we allow preemption and migration of jobs, motivated by virtualization techniques. We consider two natural objectives: throughput maximization (MaxT), which seeks a maximum weight subset of the jobs that can be feasibly scheduled on the hosts in M, and resource minimization (MinR), that is finding the minimum number of (homogeneous) hosts needed to feasibly schedule all jobs. Both problems are known to be NP-hard. We first present an Ω(1)-approximation algorithm for MaxT instances where time-windows form a laminar family of intervals. We then extend the algorithm to handle instances with arbitrary time-windows, assuming there is sufficient slack for each job to be completed. For MinR we study a more general setting with d resources and derive an O(log d)-approximation for any fixed d ≥ 1, under the assumption that time-windows are not too small. This assumption can be removed leading to a slightly worse ratio of O(log dlog T), where T is the maximum due date of any job.

Original languageEnglish (US)
Title of host publication39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2019
EditorsArkadev Chattopadhyay, Paul Gastin
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959771313
DOIs
StatePublished - Dec 2019
Event39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2019 - Bombay, India
Duration: Dec 11 2019Dec 13 2019

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume150
ISSN (Print)1868-8969

Conference

Conference39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS 2019
CountryIndia
CityBombay
Period12/11/1912/13/19

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • Approximation Algorithms
  • Machine Scheduling
  • Resource Allocation
  • Vector Packing

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