scholarly journals Mobile devices and computing cloud resources allocation for interactive applications

2017 ◽  
Vol 27 (2) ◽  
pp. 293-307
Author(s):  
Henryk Krawczyk ◽  
Michał Nykiel
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Device ◽  
Heuristic Algorithm ◽  
Energy Cost ◽  
Optimization Problem ◽  
Resources Allocation ◽  
Interactive Applications ◽  
Application Execution ◽  
Cloud Resources

Abstract Using mobile devices such as smartphones or iPads for various interactive applications is currently very common. In the case of complex applications, e.g. chess games, the capabilities of these devices are insufficient to run the application in real time. One of the solutions is to use cloud computing. However, there is an optimization problem of mobile device and cloud resources allocation. An iterative heuristic algorithm for application distribution is proposed. The algorithm minimizes the energy cost of application execution with constrained execution time.

scholarly journals A Karaoke System with Real-Time Media Merging and Sharing Functions for a Cloud-Computing-Integrated Mobile Device

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Her-Tyan Yeh ◽  
Juing-Shian Chiou ◽  
Ting-Jun Zhou
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Mobile Devices ◽  
Mobile Device ◽  
Personal Digital Assistants ◽  
Popular Entertainment ◽  
Work Related ◽  
Cloud Server ◽  
Streaming Technology ◽  
Technology Users

Mobile devices such as personal digital assistants (PDAs), smartphones, and tablets have increased in popularity and are extremely efficient for work-related, social, and entertainment uses. Popular entertainment services have also attracted substantial attention. Thus, relevant industries have exerted considerable efforts in establishing a method by which mobile devices can be used to develop excellent and convenient entertainment services. Because cloud-computing technology is mature and possesses a strong computing processing capacity, integrating this technology into the entertainment service function in mobile devices can reduce the data load on a system and maintain mobile device performances. This study combines cloud computing with a mobile device to design a karaoke system that contains real-time media merging and sharing functions. This system enables users to download music videos (MVs) from their mobile device and sing and record their singing by using the device. They can upload the recorded song to the cloud server where it is merged with real-time media. Subsequently, by employing a media streaming technology, users can store their personal MVs in their mobile device or computer and instantaneously share these videos with others on the Internet. Through this process, people can instantly watch shared videos, enjoy the leisure and entertainment effects of mobile devices, and satisfy their desire for singing.

scholarly journals Optimization of mobile device energy consumption in a fog-based mobile computing offloading mechanism

2021 ◽  
Vol 29 (1) ◽  
pp. 53-62
Author(s):  
Anastasia V. Daraseliya ◽  
Eduard S. Sopin
Keyword(s):  
Energy Consumption ◽  
Response Time ◽  
Mobile Devices ◽  
Mobile Device ◽  
Mobile Applications ◽  
Optimization Problem ◽  
Fog Computing ◽  
Computing System ◽  
Battery Life ◽  
Average Response Time

The offloading of computing tasks to the fog computing system is a promising approach to reduce the response time of resource-greedy real-time mobile applications. Besides the decreasing of the response time, the offloading mechanisms may reduce the energy consumption of mobile devices. In the paper, we focused on the analysis of the energy consumption of mobile devices that use fog computing infrastructure to increase the overall system performance and to improve the battery life. We consider a three-layer computing architecture, which consists of the mobile device itself, a fog node, and a remote cloud. The tasks are processed locally or offloaded according to the threshold-based offloading criterion. We have formulated an optimization problem that minimizes the energy consumption under the constraints on the average response time and the probability that the response time is lower than a certain threshold. We also provide the numerical solution to the optimization problem and discuss the numerical results.

Data Storage Security in Mobile Cloud Computing (MCC) using Improved Blowfish Algorithm

2021 ◽  
pp. 100-111
Author(s):  
Seada Abdu Wakene ◽  
Sisay Muleta Hababa ◽  
Gutema Seboka Daba ◽  
K S Ananda Kumar
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Storage ◽  
Mobile Device ◽  
Data Security ◽  
Mobile Cloud Computing ◽  
Data Access ◽  
Security And Privacy ◽  
Mobile Cloud ◽  
Technical Requirements

Mobile cloud computing (MCC) combines cloud computing and mobile computing to deliver vast computational resources to mobile consumers, network operators, and cloud computing providers. You may access your data from anywhere in the globe using any mobile device that is linked to the Internet. Cloud computing provides access to data in real-time whenever and wherever want. Any conventional mobile device can benefit from MCC's infrastructure, computational capacity, software, and platform services. Network security, web application security, data access, authentication, authorization, data confidentiality, and data breach are all concerns of MCC's security. Because mobile devices lack sufficient storage and processing power, their data storage capacity is limited. Users of mobile devices may inadvertently provide sensitive information over the network or through the application. Therefore, data security is the main concern for mobile device users. The objective of this paper is to find a solution that can enhance technical requirements with relation to user’s data security and privacy in mobile cloud computing. To achieve this improved blowfish encryption algorithm is used to encrypt each user’s data security and where the shared secret key is hash down using message digest called secured hash function. Hashing can increase the integrity and privacy of user data. The proposed algorithm is evaluated with a normal blowfish algorithm and 3DES with different parameters. Improved blowfish algorithm shows better performance than normal blowfish algorithm and 3DES. In this work, we have developed web-based application where the Amazon MySQL RDS database is used for data storage.

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 Low-Energy-Orientated Resource Scheduling in Cloud Computing by Particle Swarm Optimization

2018 ◽  
Vol 36 (2) ◽  
pp. 339-344
Author(s):  
Jia Jia ◽  
Dejun Mu
Keyword(s):  
Cloud Computing ◽  
Particle Swarm Optimization ◽  
Multiobjective Optimization ◽  
Energy Cost ◽  
Optimization Problem ◽  
Particle Swarm ◽  
Resource Scheduling ◽  
Multiobjective Optimization Problem ◽  
Swarm Optimization ◽  
Scheduling Method

In order to reduce the energy cost in cloud computing, this paper represents a novel energy-orientated resource scheduling method based on particle swarm optimization. The energy cost model in cloud computing environment is studied first. The optimization of energy cost is then considered as a multiobjective optimization problem, which generates the Pareto optimization set. To solve this multiobjective optimization problem, the particle swarm optimization is involved. The states of one particle consist of both the allocation plan for servers and the frequency plans on servers. Each particle in this algorithm obtains its Pareto local optimization. After the assembly of local optimizations, the algorithm generates the Pareto global optimization for one server plan. The final solution to our problem is the optimal one among all server plans. Experimental results show the good performance of the proposed method. Comparing with the widely-used Round robin scheduling method, the proposed method requires only 45.5% dynamic energy cost.

Virtualization in Mobile Cloud Computing (VMCC) Environments

2021 ◽  
pp. 404-411
Author(s):  
Raghvendra Kumar ◽  
Prasant Kumar Pattnaik ◽  
Priyanka Pandey
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Mobile Devices ◽  
User Experience ◽  
Mobile Device ◽  
Mobile Cloud Computing ◽  
Personal Computers ◽  
Mobile Cloud ◽  
Cloud Networking

Unfortunately, most of the widely used protocols for remote desktop access on mobile devices have been designed for scenarios involving personal computers. Furthermore, their energy consumption at the mobile device has not been fully characterized. In this chapter, we specially address energy consumption of mobile cloud networking realized through remote desktop technologies. In order to produce repeatable experiments with comparable results, we design a methodology to automate experiments with a mobile device. Furthermore, we develop an application that allows recording touch events and replaying them for a certain number of times. Moreover, we analyze the performance of widely used remote desktop protocols through extensive experiments involving different classes of mobile devices and realistic usage scenarios. We also relate the energy consumption to the different components involved and to the protocol features. Finally, we provide some considerations on aspects related to usability and user experience.

Virtualization in Mobile Cloud Computing (VMCC) Environments

2017 ◽  
pp. 106-114
Author(s):  
Raghvendra Kumar ◽  
Prasant Kumar Pattnaik ◽  
Priyanka Pandey
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Mobile Devices ◽  
User Experience ◽  
Mobile Device ◽  
Mobile Cloud Computing ◽  
Personal Computers ◽  
Mobile Cloud ◽  
Cloud Networking

Unfortunately, most of the widely used protocols for remote desktop access on mobile devices have been designed for scenarios involving personal computers. Furthermore, their energy consumption at the mobile device has not been fully characterized. In this chapter, we specially address energy consumption of mobile cloud networking realized through remote desktop technologies. In order to produce repeatable experiments with comparable results, we design a methodology to automate experiments with a mobile device. Furthermore, we develop an application that allows recording touch events and replaying them for a certain number of times. Moreover, we analyze the performance of widely used remote desktop protocols through extensive experiments involving different classes of mobile devices and realistic usage scenarios. We also relate the energy consumption to the different components involved and to the protocol features. Finally, we provide some considerations on aspects related to usability and user experience.

scholarly journals Energy Saving from Cloud Resources for a Sustainable Green Cloud Computing Environment

2018 ◽  
Author(s):  
Karuppasamy M. ◽  
Balakannan S. P.
Keyword(s):  
Cloud Computing ◽  
Energy Saving ◽  
Energy Cost ◽  
Cloud Services ◽  
Cloud Environment ◽  
Computing Services ◽  
Operational Energy ◽  
Cloud Computing Services ◽  
Green Cloud ◽  
Cloud Resources

Cloud computing services are proliferation. The Cloud computing resources face major pitfall in energy consumes. The prime of energy consumption in cloud computing is by means of client computational devices, server computational devices, network computational devices and power required to cool the IT load. The cloud resources contribute high operational energy cost and emit more carbon emission to the environment. Therefore the cloud services providers need green cloud environment resolution to decrease the operational energy cost along with environmental impact. The most important objective of this effort is to trim down the energy from utilized and unutilized (idle) cloud resources and save the energy in cloud resources efficiently. To achieve the sustainable green cloud environment from an Energy Saving Algorithm used to choose the appropriate virtual services so that the power at the client, server, and network recourses can be reduced.  

scholarly journals Efficient key distribution protocol for mobile devices in cloud environments

2018 ◽  
Vol 7 (2.12) ◽  
pp. 18
Author(s):  
Yoon Su Jeong ◽  
Yong Tae Kim ◽  
Gil Cheol Park
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Device ◽  
Key Distribution ◽  
Data Encryption ◽  
Key Generation ◽  
Cloud Environment ◽  
Efficient Manner ◽  
Computing Services ◽  
Cloud Computing Services

Background/Objectives: Recently, as the fourth industrial revolution has emerged, cloud computing services have been attracting attention for efficient use of Internet-based computing resources. Among the cloud computing services, even if the data processed by the mobile device is encrypted after being stored in the server, the confidential information can be leaked. Therefore, there is a need for the key generation for data encryption and decryption.Methods/Statistical analysis: In this paper, we propose a key distribution protocol that enables mobile devices to securely encrypt and decrypt keys in an efficient manner in a cloud environment. The main purpose of the proposed protocol is to maximize the efficiency and cost reduction of key generation, which can securely transmit and receive data, in a situation where the size of data used in the cloud environment and the storage location are increasing. As a result of the performance evaluation, the proposed method improved the authentication processing time by 4.1% on average compared with the existing protocol, and the average throughput rate of the server per unit time was 6.5%. In addition, the communication delay time between the authentication server and the mobile device improved by 9.3% on average, and the authentication overhead of the server was 11.5% lower than that of the conventional method.Findings: In order to solve this problem, the proposed protocol can solve the security problem of the mobile device because it can receive the authentication through the one - way hash function and the XOR operation using the encrypted data using the session key.Improvements/Applications: In future studies, we will apply the proposed protocol to the actual environment based on the results of this study and compare it with the results obtained from the theoretical studies. 

Dynamic Cloud Resources Allocation

2019 ◽  
Author(s):  
Saad Sultan ◽  
Abdullah Asad ◽  
M. Abubakar ◽  
Suleman Khalid ◽  
Shahab Ahmed ◽  
...  
Keyword(s):  
Resources Allocation ◽  
Cloud Resources
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