scholarly journals A Study on Task Scheduling in Mobile Cloud Computing

2018 ◽  
pp. 244-246
Author(s):  
J. Arockia Mary ◽  
P. Xavier Jeba ◽  
P. Mercy
Keyword(s):  
Cloud Computing ◽  
Mobile Device ◽  
Data Transmission ◽  
Mobile Applications ◽  
Quality Of Experience ◽  
Mobile Cloud Computing ◽  
Limited Resource ◽  
Mobile Cloud ◽  
Task Dependency

In mobile device, the resources such as computation, storage, power are limited. Quality of Experience (QoE) of user in these limited resource mobile device is not satisfied. Mobile cloud computing is a new computation paradigm to increase Quality of Service (QoS) of mobile applications by scheduling the offloaded tasks into the cloud. The scheduling of tasks is done in four architectures of mobile cloud computing. Two types of scheduling are done with lot of constraints such as data transmission, task dependency and cost etc. Different scheduling techniques are developed to improve the QoE of mobile users.

A Novel Application Offloading Algorithm and an Optimized Application Servers Placement for Mobile Cloud Computing

2015 ◽  
Vol 6 (4) ◽  
pp. 19-38
Author(s):  
Amal Ellouze ◽  
Maurice Gagnaire
Keyword(s):  
Cloud Computing ◽  
Quality Of Experience ◽  
Mobile Cloud Computing ◽  
Energy Savings ◽  
Mobile Cloud ◽  
Mobile Terminals ◽  
Application Servers ◽  
Application Offloading ◽  
Computing Capacity

An application's offloading algorithm to over go the limitations of mobile terminals, namely their lack of computing capacity and limited battery autonomy is introduced. The proposed Mobile Application's Offloading algorithm enables to shift applicative jobs from mobile handsets to remote servers. The novelty of MAO consists in considering the Quality of Experience as an additional decision test before proceeding to application offloading. Based on various traffic scenarios, researchers study the efficiency of the MAO algorithm and show its performance in terms of rejected jobs and energy savings. First, the researchers consider the case where the application servers were placed systematically at the antenna's site. For a more realistic context of Mobile Cloud Computing, they extend the analysis by considering the case where the remote servers can be placed at different splitting points of the infrastructure. They assess by means of closed-forms fitting functions the performance of the MAO algorithm. Authors end this article with proposing an optimized applications servers placement.

A Survey of Mobile Cloud Computing for Extending Energy of Mobile Devices

2014 ◽  
Vol 573 ◽  
pp. 549-555
Author(s):  
P. Thanapal ◽  
M.A. Saleem Durai
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Mobile Devices ◽  
Present State ◽  
Mobile Device ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Mobile Cloud

Mobile cloud computing will wear down gaining quality among users, the researchers predicts these troubles by execution of mobile applications on application suppliers external to the mobile device. During this paper, we have a tendency to gift a wide survey of mobile cloud computing, whereas prominence the particular considerations in mobile cloud computing square measure as follows. (a) Highlights the present state in Application of cloud computing usage in real time world. (b) Identifies the problems in testing bandwidth and (c) provides a optimizing of the offloading that saves energy

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.

Security Management in Mobile Cloud Computing

2018 ◽  
pp. 1027-1043
Author(s):  
Basudeo Singh ◽  
Jasmine K.S.
Keyword(s):  
Cloud Computing ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Computing Technology ◽  
Security Issue ◽  
Security Strategy ◽  
Cloud Systems ◽  
Security Issues ◽  
Pros And Cons

Mobile cloud computing is a technique or model in which mobile applications are built, powered and hosted using cloud computing technology. In Mobile Cloud computing we can store information regarding sender, data and receiver on cloud through mobile application. As we store more and more information on cloud by client, security issue will arise. This chapter presents a review on the mobile cloud computing concepts as well as security issues and vulnerabilities affecting Cloud Systems and the possible solutions available to such issues within the context of cloud computing. It also describes the pros and cons of the existing security strategy and also introduces the existing issues in cloud computing such as data integrity, data segregation, and security.

Recent Advances Delivered in Mobile Cloud Computing's Security and Management Challenges

2020 ◽  
pp. 21-43
Author(s):  
Christos Stergiou ◽  
Kostas E. Psannis
Keyword(s):  
Cloud Computing ◽  
Mobile Device ◽  
Mobile Cloud Computing ◽  
New Method ◽  
Encryption Algorithm ◽  
Mobile Cloud ◽  
Cloud Environment ◽  
Computational Power ◽  
Access To Data ◽  
Aes Encryption Algorithm

Mobile cloud computing provides an opportunity to restrict the usage of huge hardware infrastructure and to provide access to data, applications, and computational power from every place and in any time with the use of a mobile device. Furthermore, MCC offers a number of possibilities but additionally creates several challenges and issues that need to be addressed as well. Through this work, the authors try to define the most important issues and challenges in the field of MCC technology by illustrating the most significant works related to MCC during recent years. Regarding the huge benefits offered by the MCC technology, the authors try to achieve a more safe and trusted environment for MCC users in order to operate the functions and transfer, edit, and manage data and applications, proposing a new method based on the existing AES encryption algorithm, which is, according to the study, the most relevant encryption algorithm to a cloud environment. Concluding, the authors suggest as a future plan to focus on finding new ways to achieve a better integration MCC with other technologies.

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.

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.

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