Modeling and Managing Energy Efficiency Data Center by a Live Migration Mechanism in Mobile Cloud Computing Environments

2012 ◽  
Vol 10 (8) ◽  
pp. 1855-1861
Author(s):  
Dawei Sun ◽  
Guiran Chang ◽  
Dongqi Wang ◽  
Dong Chen ◽  
Xingwei Wang
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Data Center ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Live Migration ◽  
Migration Mechanism ◽  
Computing Environments ◽  
Efficiency Data

scholarly journals A Data Transmission Strategy with Energy Minimization Based on Optimal Stopping Theory in Mobile Cloud Computing

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Xin Zheng ◽  
Yu Nan ◽  
Fangsu Wang ◽  
Ruiqing Song ◽  
Gang Zheng ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Optimal Stopping ◽  
Data Transmission ◽  
Mobile Cloud Computing ◽  
Rapid Development ◽  
Average Energy ◽  
Mobile Cloud ◽  
Mobile Terminals ◽  
Optimal Stopping Theory

Considering the widespread use of mobile devices and the increased performance requirements of mobile users, shifting the complex computing and storage requirements of mobile terminals to the cloud is an effective way to solve the limitation of mobile terminals, which has led to the rapid development of mobile cloud computing. How to reduce and balance the energy consumption of mobile terminals and clouds in data transmission, as well as improve energy efficiency and user experience, is one of the problems that green cloud computing needs to solve. This paper focuses on energy optimization in the data transmission process of mobile cloud computing. Considering that the data generation rate is variable, because of the instability of the wireless connection, combined with the transmission delay requirement, a strategy based on the optimal stopping theory to minimize the average transmission energy of the unit data is proposed. By constructing a data transmission queue model with multiple applications, an admission rule that is superior to the top candidates is proposed by using secretary problem of selecting candidates with the lowest average absolute ranking. Then, it is proved that the rule has the best candidate. Finally, experimental results show that the proposed optimization strategy has lower average energy per unit of data, higher energy efficiency, and better average scheduling period.

scholarly journals A Trust-Based Agent Learning Model for Service Composition in Mobile Cloud Computing Environments

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 34207-34226 ◽  
Author(s):  
Wenjuan Li ◽  
Jian Cao ◽  
Keyong Hu ◽  
Jie Xu ◽  
Rajkumar Buyya
Keyword(s):  
Cloud Computing ◽  
Service Composition ◽  
Mobile Cloud Computing ◽  
Learning Model ◽  
Mobile Cloud ◽  
Agent Learning ◽  
Computing Environments

scholarly journals Protecting Data on Mobile Cloud Computing

2019 ◽  
Vol 8 (11) ◽  
pp. 3453-3459
Keyword(s):  
Cloud Computing ◽  
Mobile Computing ◽  
Mobile Devices ◽  
Data Center ◽  
Mobile Cloud Computing ◽  
Third Party ◽  
Battery Life ◽  
Mobile Cloud ◽  
Cloud Data Center ◽  
Cloud Data

Mobile Cloud Computing is a combination of general Cloud Computing and Mobile Computing in which we have to access resources from the remote cloud data center with the help of mobile electronics and peripherals like mobile smartphones, laptops, gadgets, etc. via Cellular Technology or Wireless Communication. Mobile devices have lots of resource constraints like storage capacity, processing speed, and battery life. Hence through simple mobile computing software and programming, we cannot manipulate on mobile devices of cloud data center information. Because of such kinds of difficulty, we have to process information or data through external mobile devices. Accessing and processing of data with the help of Trusted Third Party Agency (TPA) outside the cloud data center and mobile devices have lots of security challenges. To make cloud data secure over outside resources, lots of terminologies and theory are put forward by various researchers. In this paper, we will analyze their theory and its limitations and offer our security algorithm proposal. In this thesis article, we analyze the security framework for storing data on Cloud Server by Mobile and limitation of this process. Also, we review the theory of how data can be secure our data on cloud administrators

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