Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
An adaptive mobile cloud computing framework using a call graph based model
Date
2016-04-01
Author
Kaya, Mahir
Koçyiğit, Altan
Eren, Pekin Erhan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
207
views
0
downloads
Cite This
The use of mobile applications and their functionality are increasing day by day but mobile devices are still inferior to ordinary computers in terms of memory and processor capacity. Furthermore, the rapid depletion of the mobile devices' energy is still a major problem. Performance and energy shortcomings of mobile devices can be improved by using surrogate or cloud computing technologies. In particular, computation and memory intensive real time applications would be efficiently run by utilizing the resources of a remote server. In this paper, a novel offloading framework based on the Inversion of Control mechanism is developed to overcome the shortcomings and limitations of the current offloading approaches published in the literature. The proposed offloading framework reduces the burden on programmers. It implements application partitioning and code offloading via remote proxy classes and seamlessly provides callback functionality. In an application, it is possible to migrate different combinations of application components to remote servers. Some of these combinations can be productive and others can be counterproductive for offloading. In order to decide on components to be offloaded, a call graph model based on the collaboration of application's classes is developed. An offloading decision algorithm is presented to determine the classes to be offloaded by finding the best application partitioning in the graph. The framework and the graph model are evaluated by several experiments. Experimental results show that the proposed graph model fits well to the application partitioning problem. It has also been shown that offloading the optimal combination of components to remote servers can considerably reduce the execution time and energy consumption of mobile devices.
Subject Keywords
Code offloading
,
Distribution transparency
,
Inversion of Control
,
Graph partitioning
,
Mobile cloud computing
URI
https://hdl.handle.net/11511/32299
Journal
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
DOI
https://doi.org/10.1016/j.jnca.2016.02.013
Collections
Graduate School of Informatics, Article
Suggestions
OpenMETU
Core
A Mobile Computing Framework Based on Adaptive Mobile Code Offloading
Kaya, Mahir; Koçyiğit, Altan; Eren, Pekin Erhan (2014-08-29)
Smartphones are not capable of competing against their desktop counterparts or servers in terms of CPU speed, battery, memory and storage. However, a mobile device can transparently use cloud resources by employing an offloading mechanism. Offloading enables mobile devices to run computation intensive applications such as object recognition, Optical Character Recognition (OCR) and augmented reality. In this paper, an Inversion of Control (IoC) based offloading technique is proposed in order to overcome shor...
A Self-Cloning Agents Based Model for High-Performance Mobile-Cloud Computing
Angın, Pelin; Jin, Zhongjun (2015-07-02)
The rise of the mobile-cloud computing paradigm in recent years has enabled mobile devices with processing power and battery life limitations to achieve complex tasks in real-time. While mobile-cloud computing is promising to overcome the limitations of mobile devices for real-time computing, the lack of frameworks compatible with standard technologies and techniques for dynamic performance estimation and program component relocation makes it harder to adopt mobile-cloud computing at large. Most of the avai...
An Optimal application partitioning and computational offloading framework for mobile cloud computing
Kaya, Mahir; Koçyiğit, Altan; Department of Information Systems (2016)
The use of mobile applications is increasing every day and they offer more functionality on mobile devices. However, these devices are inferior to server computers in terms of memory and processor capacity. Furthermore, rapid depletion of mobile devices’ energy resources is still a major problem. Performance and energy shortcomings of mobile devices can be improved by using surrogate or cloud computing technologies. In this thesis, an offloading framework is proposed to improve the performance and efficienc...
An agent-based optimization framework for mobile-cloud computing
Angın, Pelin (2013-01-01)
The proliferation of cloud computing resources in the recent years offers a way for mobile devices with limited resources to achieve computationally intensive tasks in real-time. The mobile-cloud computing paradigm, which involves collaboration between mobile and cloud resources, is expected to become increasingly popular in mobile application development. Dynamic partitioning of applications between mobile and cloud platforms based on resource availability is crucial in achieving the best performance for a...
A Software quality model for android applications
Şimşek, Merve Vildan; Betin Can, Aysu; Department of Information Systems (2016)
Nowadays mobile devices have become increasingly widespread. It causes mobile applications number to grow dramatically. As the popularity of these systems is predicted to continue its increase in the near future, the importance of the quality of mobile applications increases. The aim of this study is to present a quality model for Android applications. We chose applications developed for Android Operating System as our target because of its prevalence in the mobile market. To achieve the aim of the study, w...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. Kaya, A. Koçyiğit, and P. E. Eren, “An adaptive mobile cloud computing framework using a call graph based model,”
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
, pp. 12–35, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32299.