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Multi-Objective Decision-Making for Mobile Cloud Offloading: A Survey
Author(s) -
Huaming Wu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2791504
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Running very complex applications on mobile devices is still challenging since they are constrained by limited resources, such as memory capacity, network bandwidth, processor speed, and battery power. Mobile Cloud Computing (MCC) is a combination of cloud computing and mobile internet, which could effectively alleviate the resource constraints of mobile devices. How to efficiently offload computation intensive parts of mobile applications from mobile devices to capable cloud servers is one of the keys. In mobile environments, the resource heterogeneity of mobile devices and cloud services, the interruption of heterogeneous wireless networks, the complexity of mobile applications, and the characteristic of transferring a large amount of data, are the major bottlenecks that have prevented this technology from being widely used. This paper takes these constraints into an account at the same time and explores methods of multi-objective decision making for timeand energy-aware task offloading for MCC. It is designed to ensure the right computational tasks are executed in the right way, at the right time and place.

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