Online Algorithms for Location-Aware Task Offloading in Two-Tiered Mobile Cloud Environments

2014 ◽  
Author(s):  
Qiufen Xia ◽  
Weifa Liang ◽  
Zichuan Xu ◽  
Bingbing Zhou
Keyword(s):  
Online Algorithms ◽  
Mobile Cloud ◽  
Location Aware ◽  
Cloud Environments ◽  
Task Offloading

scholarly journals Cooperative Runtime Offloading Decision Algorithm for Mobile Cloud Computing

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Xiaomin Jin ◽  
Zhongmin Wang ◽  
Wenqiang Hua
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Data Transmission ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Wireless Data ◽  
Decision Algorithm ◽  
Wireless Data Transmission ◽  
Cloud Environments ◽  
New Challenges

Mobile cloud computing (MCC) provides a platform for resource-constrained mobile devices to offload their tasks. MCC has the characteristics of cloud computing and its own features such as mobility and wireless data transmission, which bring new challenges to offloading decision for MCC. However, most existing works on offloading decision assume that mobile cloud environments are stable and only focus on optimizing the consumption of offloaded applications but ignore the consumption caused by offloading decision algorithms themselves. This paper focuses on runtime offloading decision in dynamic mobile cloud environments with the consideration of reducing the offloading decision algorithm’s consumption. A cooperative runtime offloading decision algorithm, which takes advantage of the cooperation of online machine learning and genetic algorithm to make offloading decisions, is proposed to address this problem. Simulations show that the proposed algorithm helps offloaded applications save more energy and time while consuming fewer computing resources.

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