On Data-Driven Network Performance Modeling for Mobile Cloud Computing

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Computationally intensive mobile apps may be migrated to a cloud infrastructure for faster remote execution. Decreased execution time and lower energy consumption at the mobile device are the expected benefits when offloading the application to the cloud. The migration decision can be taken based on a continuous-time Markov model that considers network quality, cloud and mobile device capabilities, as well as migration costs, as we have shown in previous work. One of the influencing dynamic characteristics is the network performance. In this work, we focus on characterizing network performance under node mobility in terms of throughput and latency. Our final goal is to derive a mobile performance model that goes beyond an on-off network model. The analysis is based on performance measurements taken on a train while commuting. By clustering the measurement data, we derive a realistic network model.
Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
PublisherIEEE
Number of pages5
DOIs
Publication statusPublished - 2018

Fields of science

  • 202038 Telecommunications
  • 102 Computer Sciences
  • 102002 Augmented reality
  • 102006 Computer supported cooperative work (CSCW)
  • 102013 Human-computer interaction
  • 102015 Information systems
  • 102021 Pervasive computing
  • 102025 Distributed systems
  • 102027 Web engineering

JKU Focus areas

  • Computation in Informatics and Mathematics

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