DocumentCode
180524
Title
A Taxonomy of Offloading in Mobile Cloud Computing
Author
Hyun Jung La ; Soo Dong Kim
Author_Institution
Dept. of Comput. Sci., Soongsil Univ., Seoul, South Korea
fYear
2014
fDate
17-19 Nov. 2014
Firstpage
147
Lastpage
153
Abstract
Mobile computing provides benefits of mobility, convenience and convergence. However, they have limited resources for computation, memory, networking, and battery. An effective approach to remedying the constraints is to offload resource-intensive components of a mobile app to a resource-abundant server and run it, called offloading and more generally Mobile Cloud Computing. There are a number of different approaches to offloading, and they result in different gains on benefit. In this paper, we propose a comprehensive taxonomy of offloading schemes and an assessment on the schemes. We first propose five criteria for classifying offloading schemes and define a taxonomy using the criteria. And, we choose a subset of practically configurable offloading schemes out of 32 schemes in the table. Then, we characterize the resulting offloading schemes by using key quality gains with offloading, Time Efficiency, Resource Consumption, and Adaptability to Load Evolution. Using the proposed taxonomy and guidelines, we present a case study of designing an off loadable mobile app and assess the applicability of the proposed taxonomy and guidelines.
Keywords
cloud computing; mobile computing; mobility management (mobile radio); smart phones; adaptability-to-load evolution; battery; computation; convenience; convergence; memory; mobile app; mobile cloud computing; mobility; networking; offloading scheme classification; offloading taxonomy; resource consumption; resource-abundant server; resource-intensive components; smartphones; time efficiency; Guidelines; Media; Mobile communication; Mobile handsets; Runtime; Servers; Taxonomy; Guidelines; Mobile Cloud Computing; Offloading Scheme; Quality Gains; Taxonomy;
fLanguage
English
Publisher
ieee
Conference_Titel
Service-Oriented Computing and Applications (SOCA), 2014 IEEE 7th International Conference on
Conference_Location
Matsue
Type
conf
DOI
10.1109/SOCA.2014.22
Filename
6978603
Link To Document