Adaptive Computation Offloading in Mobile Cloud Computing

doi:10.5220/0006348505520557

Adaptive Computation Offloading in Mobile Cloud Computing

2017-01-01

2

OA

AI

V

Vibha Tripathi *

DOI：10.5220/0006348505520557

Original

Original request for help

Save

Abstract

En 中文

Mobile Computing has been in use for a while now. A mobile device is a concise tool with limited computational resources like battery, CPU and memory. Although these resources suffice the immediate traditional needs of its user, as the mobile devices are fast turning into personal computing devices, with the rapid development in Cloud-Based technologies like Machine Learning in the Cloud, Data as a Service, Software as a Service, and so on there is an emergent need to implement iteratively more effective ways to offload mobile computation to the Cloud in an on-demand, adaptable and opportunistic way. The major issue in implementing this requirement lies in the very fact that mobile devices are location and context sensitive, limited in battery capacity and need to be constantly reconnecting with their provider's Base Transceivers while still providing efficient response time to its user. In this paper, we survey this issue and a few proposed solutions in this area and in the end; propose a model for adaptive computation offloading.

Keywords:

Mobile Cloud Computing

Computation Offloading

Data as a Service (DaaS)

Platform as a Service (PaaS)

Software as a Service (SaaS)

Infrastructure as a Service (IaaS)

Machine Learning

Artificial Intelligence

Augmented Reality

Internet of Things (IoT)

Nash Equilibrium

Adaptive Computation Offloading in Mobile Cloud Computing

Abstract

Journal

Organization