Scheduling dynamic parallel workload of mobile devices with access guarantees

Antonio Fernández Anta, Dariusz R. Kowalski, Miguel A. Mosteiro, Prudence W.H. Wong

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

We study a dynamic resource-allocation problem that arises in various parallel computing scenarios, such as mobile cloud computing, cloud computing systems, Internet of Things systems, and others. Generically, we model the architecture as client mobile devices and static base stations. Each client "arrives" to the system to upload data to base stations by radio transmissions and then "leaves." The problem, called Station Assignment, is to assign clients to stations so that every client uploads their data under some restrictions, including a target subset of stations, a maximum delay between transmissions, a volume of data to upload, and a maximum bandwidth for each station. We study the solvability of Station Assignment under an adversary that controls the arrival and departure of clients, limited to maximum rate and burstiness of such arrivals. We show upper and lower bounds on the rate and burstiness for various client arrival schedules and protocol classes. To the best of our knowledge, this is the first time that Station Assignment is studied under adversarial arrivals and departures.

Original languageEnglish (US)
Article number10
JournalACM Transactions on Parallel Computing
Volume5
Issue number2
DOIs
Publication statusPublished - Jan 2018
Externally publishedYes

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Keywords

  • Continuous adversarial dynamics
  • Health monitoring systems
  • Internet of things
  • Mobile cloud computing
  • Radio networks
  • Station assignment

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Hardware and Architecture
  • Computer Science Applications
  • Computational Theory and Mathematics

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