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.

scholarly journals Joint optimization of computing ratio and access points’ density for mixed mobile edge/cloud computing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Tianqi Jing ◽  
Shiwen He ◽  
Fei Yu ◽  
Yongming Huang ◽  
Luxi Yang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Coverage Probability ◽  
Optimization Problem ◽  
Mobile Cloud Computing ◽  
Low Complexity ◽  
Mixed Integer ◽  
Joint Optimization ◽  
Mobile Cloud ◽  
Convex Problem

AbstractCooperation between the mobile edge computing (MEC) and the mobile cloud computing (MCC) in offloading computing could improve quality of service (QoS) of user equipments (UEs) with computation-intensive tasks. In this paper, in order to minimize the expect charge, we focus on the problem of how to offload the computation-intensive task from the resource-scarce UE to access point’s (AP) and the cloud, and the density allocation of APs’ at mobile edge. We consider three offloading computing modes and focus on the coverage probability of each mode and corresponding ergodic rates. The resulting optimization problem is a mixed-integer and non-convex problem in the objective function and constraints. We propose a low-complexity suboptimal algorithm called Iteration of Convex Optimization and Nonlinear Programming (ICONP) to solve it. Numerical results verify the better performance of our proposed algorithm. Optimal computing ratios and APs’ density allocation contribute to the charge saving.

QoS in the Mobile Cloud Computing Environment

2014 ◽  
pp. 200-217 ◽  
Author(s):  
Zhefu Shi ◽  
Cory Beard
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Mobile Cloud Computing ◽  
Current Status ◽  
Mobile Cloud ◽  
Loss Ratio ◽  
Important Research ◽  
Mobile Environment ◽  
Research Problems

Mobile Cloud Computing (MCC) integrates cloud computing into the mobile environment and overcomes obstacles related to performance (e.g., bandwidth, throughput) and environment (e.g., heterogeneity, scalability, and availability). Quality of Service (QoS), such as end-to-end delay, packet loss ratio, etc., is vital for MCC applications. In this chapter, several important approaches for performance evaluation in MCC are introduced. These approaches, such as Markov Processes, Scheduling, and Game Theory, are the most popular methodologies in current research about performance evaluation in MCC. QoS is special in MCC compared to other environments. Important QoS problems with details in MCC and corresponding designs and solutions are explained. This chapter covers the most important research problems and current status related to performance evaluation and QoS in MCC.

Transporting the Cloud

2014 ◽  
pp. 135-156
Author(s):  
Claudio Estevez
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Transport Layer ◽  
Mobile Cloud ◽  
Transport Protocols ◽  
End User ◽  
Advantages And Disadvantages ◽  
Processing Power ◽  
And Storage

Cloud computing is consistently proving to be the dominant architecture of the future, and mobile technology is the catalyst. By having the processing power and storage remotely accessible, the main focus of the terminal is now related to connectivity and user-interface. The success of cloud-based applications greatly depends on the throughput experienced by the end user, which is why transport protocols play a key role in mobile cloud computing. This chapter discusses the main issues encountered in cloud networks that affect connection-oriented transport protocols. These issues include, but are not limited to, large delay connections, bandwidth variations, power consumption, and high segment loss rates. To reduce these adverse effects, a set of proposed solutions are presented; furthermore, the advantages and disadvantages are discussed. Finally, suggestions are made for future mobile cloud computing transport-layer designs that address different aspects of the network, such as transparency, congestion-intensity estimation, and quality-of-service integration.

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.

A Mobile Cloud Middleware to Support Mobility and Cloud Interoperability

2016 ◽  
Vol 7 (1) ◽  
pp. 41-58 ◽  
Author(s):  
Khadija Akherfi ◽  
Hamid Harroud ◽  
Michael Gerndt
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Storage ◽  
Mobile Cloud Computing ◽  
Relevant Information ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Computing Power ◽  
Cloud Interoperability

With the recent advances in cloud computing and the improvement in the capabilities of mobile devices in terms of speed, storage, and computing power, Mobile Cloud Computing (MCC) is emerging as one of important branches of cloud computing. MCC is an extension of cloud computing with the support of mobility. In this paper, the authors first present the specific concerns and key challenges in mobile cloud computing. They then discuss the different approaches to tackle the main issues in MCC that have been introduced so far, and finally focus on describing the proposed overall architecture of a middleware that will contribute to providing mobile users data storage and processing services based on their mobile devices capabilities, availability, and usage. A prototype of the middleware is developed and three scenarios are described to demonstrate how the middleware performs in adapting the provision of cloud web services by transforming SOAP messages to REST and XML format to JSON, in optimizing the results by extracting relevant information, and in improving the availability by caching. Initial analysis shows that the mobile cloud middleware improves the quality of service for mobiles, and provides lightweight responses for mobile cloud services.

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