Energy Driven Avatar Migration in Green Cloudlet Networks

Qiang Fan, Nirwan Ansari, Xiang Sun

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Fully utilizing green energy can remarkably decrease the operational cost of cloudlet providers in provisioning green cloudlet networks (GCNs), which are powered by both green and brown energy. Owing to the spatial and temporal dynamics of energy demands and green energy generation, migrating Avatars (i.e., virtual machines) from green energy deprived cloudlets into green energy over-provisioned cloudlets can reduce the total on-grid energy consumption of GCN. However, Avatar migration itself consumes non-negligible energy consumption. In this letter, we propose the Energy driven AvataR migration (EARN) scheme to reduce the total on-grid energy consumption of GCN by considering the energy consumption of Avatar migrations. The performance of EARN is demonstrated by extensive simulations.

Original languageEnglish (US)
Article number7882633
Pages (from-to)1601-1604
Number of pages4
JournalIEEE Communications Letters
Volume21
Issue number7
DOIs
StatePublished - Jul 2017

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Cloudlet
  • edge computing
  • green energy
  • virtual machine migration

Fingerprint

Dive into the research topics of 'Energy Driven Avatar Migration in Green Cloudlet Networks'. Together they form a unique fingerprint.

Cite this