A knowledge-based multi-criteria collaborative filtering approach for discovering services in mobile cloud computing platforms

2018 ◽  
Vol 54 (1) ◽  
pp. 179-203 ◽  
Author(s):  
Luis Omar Colombo-Mendoza ◽  
Rafael Valencia-García ◽  
Ricardo Colomo-Palacios ◽  
Giner Alor-Hernández
Keyword(s):  
Cloud Computing ◽  
Collaborative Filtering ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Knowledge Based ◽  
Computing Platforms ◽  
Filtering Approach

scholarly journals Multilayer Architecture Model for Mobile Cloud Computing Paradigm

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Higinio Mora ◽  
Francisco J. Mora Gimeno ◽  
María Teresa Signes-Pont ◽  
Bruno Volckaert
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Comprehensive Model ◽  
Architecture Model ◽  
Network Layers ◽  
Computing Paradigm ◽  
Multilayer Architecture ◽  
Computing Platforms ◽  
Cloud Servers

Mobile Cloud Computing is one of today's more disruptive paradigms of computation due to its effects on the performance of mobile computing and the development of Internet of Things. It is able to enhance the capabilities of devices by outsourcing the workload to external computing platforms deployed along the network, such as cloud servers, cloudlets, or other edge platforms. The research described in this work presents a computational model of a multilayer architecture for increasing the performance of devices using the Mobile Cloud Computing paradigm. The main novelty of this work lies in defining a comprehensive model where all the available computing platforms along the network layers are involved to perform the outsourcing of the application workload. This proposal provides a generalization of the Mobile Cloud Computing paradigm which allows handling the complexity of scheduling tasks in such complex scenarios. The behaviour of the model and its ability of generalization of the paradigm are exemplified through simulations. The results show higher flexibility for making offloading decisions.

A Mobile-Terminal-Oriented and Mobile-Cloud-Computing-Based Localized Scheduling Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 2111-2114
Author(s):  
Rui Xiang Liu ◽  
Yu Hong Zhang ◽  
Yan Tang
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Scheduling Algorithm ◽  
Mobile Terminal ◽  
Mobile Internet ◽  
Mobile Cloud ◽  
Computing Platform ◽  
Computing Platforms ◽  
Distributed Cloud

Mobile Cloud Computing utilizes cloud computing in the mobile internet. It takes the advantage of portability of mobile devices, and uses cloud computing to make up mobile devices' shortcomings, i.e., the capabilities of computation and storage. With the advent of cloud computing, more and more IT companies establish their own cloud computing platforms by using Hadoop, which gradually makes Hadoop a distributed cloud computing platform. By considering important attributes of mobile devices, e.g., low computation workload, high concurrency, and high real-time demand, we propose in this paper a local scheduling algorithm which is based on Hadoop mobile cloud computing, and we analyze the influence of response time and throughput on the system utility.

mMedia: An Efficient Transmission Policy for Multimedia Applications using Mobile Cloud Computing

2019 ◽  
Vol 9 (1) ◽  
pp. 32-42 ◽  
Author(s):  
Rajesh Kumar Verma ◽  
Chhabi Rani Panigrahi ◽  
Bibudhendu Pati ◽  
Joy Lal Sarkar
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Optimization Technique ◽  
Multimedia Applications ◽  
Mobile Cloud ◽  
The People ◽  
Rich Media ◽  
Time Average ◽  
Audio Video ◽  
Efficient Transmission

Background & Objective: Multimedia aggregates various types of media such as audio, video, images, animations, etc., to form a rich media content which produces an everlasting effect in the minds of the people. Methods: In order to process multimedia applications using mobile devices, we encounter a big challenge as these devices have limited resources and power. To address these limitations, in this work, we have proposed an efficient approach named as mMedia, wherein multimedia applications will utilize the multi cloud environment using Mobile Cloud Computing (MCC), for faster processing. The proposed approach selects the best available network. The authors have also considered using the Lyapunov optimization technique for efficient transmission between the mobile device and the cloud. Results: The simulation results indicate that mMedia can be useful for various multimedia applications by considering the energy delay tradeoff decision. Conclusion: The results have been compared alongside the base algorithm SALSA on the basis of different parameters like time average queue backlog, delay and time average utility and indicate that the mMedia outperforms in all the aspects.

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