DTM: A New Data Transmission Method in Mobile Cloud Computing

Author(s):  
Xue Li ◽  
Qiang Li
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Xiaomin Jin ◽  
Zhongmin Wang ◽  
Wenqiang Hua

Mobile cloud computing (MCC) provides a platform for resource-constrained mobile devices to offload their tasks. MCC has the characteristics of cloud computing and its own features such as mobility and wireless data transmission, which bring new challenges to offloading decision for MCC. However, most existing works on offloading decision assume that mobile cloud environments are stable and only focus on optimizing the consumption of offloaded applications but ignore the consumption caused by offloading decision algorithms themselves. This paper focuses on runtime offloading decision in dynamic mobile cloud environments with the consideration of reducing the offloading decision algorithm’s consumption. A cooperative runtime offloading decision algorithm, which takes advantage of the cooperation of online machine learning and genetic algorithm to make offloading decisions, is proposed to address this problem. Simulations show that the proposed algorithm helps offloaded applications save more energy and time while consuming fewer computing resources.


2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Xin Zheng ◽  
Yu Nan ◽  
Fangsu Wang ◽  
Ruiqing Song ◽  
Gang Zheng ◽  
...  

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.


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Shiyong Li ◽  
Wei Sun ◽  
Yaming Zhang ◽  
Haiou Liu

Mobile cloud computing (MCC) has gained much attention from both academia and industry in recent years. It can support new types of services, such as m-commerce, m-learning, and mobile healthcare, and enrich mobile users’ experience and satisfaction by taking full advantage of cloud computing. In MCC architectures multipath communications can be achieved with multihomed mobile devices, so as to utilize multiple paths for data transmission in parallel. They can achieve better utilization of bandwidth resource, split traffic for load balancing, and enhance reliability, fault tolerance, and robustness for applications. However, little attention has been paid to model the reliability of multipath communications in case of path failure. In this paper we investigate the reliability of concurrent multipath communications in MCC architectures and propose two reliability models when paths are failure. One is for static path failure where the failed paths cannot recover for communication in some delay time. The other is for dynamic path failure where the failed paths can recover in some delay time. Finally, numerical results are given to illustrate the reliability of multipath communications.


Author(s):  
J. Arockia Mary ◽  
P. Xavier Jeba ◽  
P. Mercy

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.


2020 ◽  
Vol 9 (1) ◽  
pp. 1883-1886

In Mobile cloud computing, Energy Efficiency is the Key factors to perform every task with less Energy. The Smart phone users are increasing day by day the data transfer speed is also increase and the energy consumption is also increase. In this paper to maintain the energy efficient for distributed wireless data transmission in Mobile cloud computing is called Distributed Wireless Data Transmission (DWDT). By this method, energy efficient is to be handled by using best intermediate path of data transmission in Mobile Cloud Computing with Energy Efficient. With this methodology the mobile cloud services can be reliability and energy efficiency in wireless data transmission in mobile cloud environment.


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