A Lightweight Distributed Framework for Computational Offloading in Mobile Cloud Computing
June 8, 2015 Editor 0
by Muhammad Shiraz, Abdullah Gani, Raja Wasim Ahmad, Syed Adeel Ali Shah, Ahmad Karim, Zulkanain Abdul Rahman
The latest developments in mobile computing technology have enabled intensive applications on the modern Smartphones. However, such applications are still constrained by limitations in processing potentials, storage capacity and battery lifetime of the Smart Mobile Devices (SMDs). Therefore, Mobile Cloud Computing (MCC) leverages the application processing services of computational clouds for mitigating resources limitations in SMDs. Currently, a number of computational offloading frameworks are proposed for MCC wherein the intensive components of the application are outsourced to computational clouds. Nevertheless, such frameworks focus on runtime partitioning of the application for computational offloading, which is time consuming and resources intensive. The resource constraint nature of SMDs require lightweight procedures for leveraging computational clouds. Therefore, this paper presents a lightweight framework which focuses on minimizing additional resources utilization in computational offloading for MCC. The framework employs features of centralized monitoring, high availability and on demand access services of computational clouds for computational offloading. As a result, the turnaround time and execution cost of the application are reduced. The framework is evaluated by testing prototype application in the real MCC environment. The lightweight nature of the proposed framework is validated by employing computational offloading for the proposed framework and the latest existing frameworks. Analysis shows that by employing the proposed framework for computational offloading, the size of data transmission is reduced by 91%, energy consumption cost is minimized by 81% and turnaround time of the application is decreased by 83.5% as compared to the existing offloading frameworks. Hence, the proposed framework minimizes additional resources utilization and therefore offers lightweight solution for computational offloading in MCC.
Go to Source
- Mobile health targets women, yet many don’t have mobile phones
- Today’s mobile device is tomorrow’s smart-home controller
- Is more IT always better for business?
- The Ubuntu Edge maybe dead, but Ubuntu Mobile lives on
- Need speed for big data? Think in-memory data management
- Apple/Samsung: The Verdict on Innovation
Tags: Mobile cloud computing
Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework Driving innovation, leadership and change at Groote Schuur Hospital, Cape Town, South Africa.
Subscribe to our stories
- Can Africa’s tech start-up scene rise to the next level? November 20, 2017
- Chocolate innovation: Sweet tooth hackers solve cocoa farmers’ challenges November 20, 2017
- A new generation of CEOs: Running a business in West Africa as a woman November 20, 2017
- Is crowdfunding the silver bullet to expanding innovation in the developing world? November 20, 2017
- Towards building an Entrepreneurship Ecosystem- Global Entrepreneurship Week and Freetown Pitch Night-The Role and Significance of the Freetown Pitch Night November 20, 2017