GA-based resource augmentation negotation for energy-optimised mobile ad-hoc cloud

Elhadj Benkhelifa, Thomas Welsh, Loai Tawalbeh, Abdallah Khreishah, Yaser Jararweh, Mahmoud Al-Ayyoub

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

10 Scopus citations

Abstract

Mobile and cloud computing are two areas which are rapidly expanding in terms of use case and functionality. An ad-hoc mobile cloud can be constructed upon local devices, where devices work together and share resources, aspects such as energy and costs may be minimised. This paper builds on previous work which proposed an end-to-end system whereby user applications may be profiled for their resource consumption locally and then if augmentation is required, they may negotiate with a local mobile ad-hoc cloud for optimum energy and resource utilisation. The contribution of this paper focuses upon a novel and adapted Genetic Algorithm approach to resource negotiation in order to further enable energy-optimised resource augmentation for Mobile Ad-hoc clouds.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages110-116
Number of pages7
ISBN (Electronic)9781509017546
DOIs
StatePublished - May 19 2016
Event4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2016 - Oxford, United Kingdom
Duration: Mar 29 2016Apr 1 2016

Publication series

NameProceedings - 2016 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2016

Other

Other4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2016
Country/TerritoryUnited Kingdom
CityOxford
Period3/29/164/1/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Computer Science Applications
  • Control and Systems Engineering

Keywords

  • Energy Optimisation
  • Genetic Algorithms
  • Mobile Cloud
  • Negotation
  • Resource Augmentation

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