Remote Cloud vs Local Mobile Cloud: A Quantitative Analysis

Muhammad Usman, Ameera Akhtar, Marwa Qaraqe, Fabrizio Granelli

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

The smartphones have evolved a lot during recent years. However, they are still limited in their battery time, computational power and storage space. Mobile Cloud Computing (MCC) has emerged as a promising solution that aims to augment smartphone's capabilities by providing a vast pool of computational power and storage space at cloud data center. In parallel to this, cooperation based computing is a recent concept in MCC that augments smartphone's capabilities by accumulating the computational resources of nearby devices to run a task. In this paper, we discuss different scenarios of computational offloading for a User Equipment (UE) and find an optimal option in terms of its energy consumption and task completion time. In particular, we compare the energy consumption and task completion time of a mobile application for local processing, offloading to a remote cloud and exploiting the cooperation based computing in the local Mobile Cloud (MC).We mark an offloading threshold for different offloading scenarios, so a UE can decide among offloading to a local MC or to a remote cloud, depending upon the size of the task it is offloading.

Original languageEnglish
Article number8648069
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
DOIs
Publication statusPublished - 2018
Event2018 IEEE Global Communications Conference, GLOBECOM 2018 - Abu Dhabi, United Arab Emirates
Duration: 9 Dec 201813 Dec 2018

Keywords

  • 5G networks
  • D2D communication
  • Mobile cloud computing
  • cloud services
  • computational offloading
  • cooperation based computing
  • cooperative networks
  • energy efficiency
  • mobile clouds
  • spectrum efficiency

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