scholarly journals Markov decision process-based computation offloading algorithm and resource allocation in time constraint for mobile cloud computing

2020 ◽  
Vol 14 (13) ◽  
pp. 2068-2078
Author(s):  
Zihan Gao ◽  
Wanming Hao ◽  
Ruizhe Zhang ◽  
Shouyi Yang
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Markov Decision Process ◽  
Decision Process ◽  
Mobile Cloud Computing ◽  
Time Constraint ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Markov Decision

High Performance Computing on Mobile Devices

2016 ◽  
pp. 334-348
Author(s):  
Atta ur Rehman Khan ◽  
Abdul Nasir Khan
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
Mobile Devices ◽  
High Performance ◽  
Mobile Cloud Computing ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Computing Technology ◽  
Wide Range ◽  
Performance Computing

Mobile devices are gaining high popularity due to support for a wide range of applications. However, the mobile devices are resource constrained and many applications require high resources. To cater to this issue, the researchers envision usage of mobile cloud computing technology which offers high performance computing, execution of resource intensive applications, and energy efficiency. This chapter highlights importance of mobile devices, high performance applications, and the computing challenges of mobile devices. It also provides a brief introduction to mobile cloud computing technology, its architecture, types of mobile applications, computation offloading process, effective offloading challenges, and high performance computing application on mobile devises that are enabled by mobile cloud computing technology.

An Adaptive Approach Towards Computation Offloading for Mobile Cloud Computing

2019 ◽  
Vol 14 (2) ◽  
pp. 52-73 ◽  
Author(s):  
Archana Kero ◽  
Abhirup Khanna ◽  
Devendra Kumar ◽  
Amit Agarwal
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Adaptive Computation ◽  
Proposed Model ◽  
Environment Variables ◽  
Real Time Information ◽  
Time Information

The widespread acceptability of mobile devices in present times have caused their applications to be increasingly rich in terms of the functionalities they provide to the end users. Such applications might be very prevalent among users but the execution results in dissipating many of the device end resources. Mobile cloud computing (MCC) has a solution to this problem by offloading certain parts of the application to cloud. At the first place, one might find computation offloading quite promising in terms of saving device end resources but eventually may result in being the other way around if performed in a static manner. Frequent changes in device end resources and computing environment variables may lead to a reduction in the efficiency of offloading techniques and even cause a drop in the quality of service for applications involving the use of real-time information. In order to overcome this problem, the authors propose an adaptive computation offloading framework for data stream applications wherein applications are partitioned dynamically followed by being offloaded depending upon the device end parameters, network conditions, and cloud resources. The article also talks about the proposed algorithm that depicts the workflow of the offloading model. The proposed model is simulated using the CloudSim simulator. In the end, the authors illustrate the working of the proposed system along with the simulated results.

Sign in / Sign up

Export Citation Format

Share Document