scholarly journals MCAF: Developing an Annotation-Based Offloading Framework for Mobile Cloud Computing

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yilian Zhou ◽  
Ligang He ◽  
Bin Wang ◽  
Yi Su ◽  
Hao Chen
Keyword(s):  
Mobile Devices ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Source Code ◽  
Cloud Infrastructure ◽  
Original Source ◽  
Automatic Integration ◽  
Android Applications ◽  
Reduce Energy Consumption ◽  
Cloud Servers

Offloading computation from mobile to remote cloud servers is a promising way to reduce energy consumption and improve the performance of mobile applications. However, a great challenge arises as automatic integration of powerful computing resources in remote cloud infrastructure and the portability of mobile devices. In this paper, we develop a Java annotation-based offloading framework, called MCAF, for android mobile devices. This framework is designed and committed to simplifying the development of android applications enabled with the offload capability. All the developers need to do is to import the SDK library of our MCAF and annotate the computation-intensive methods. MCAF can automatically extract the annotated source code and generate the code that will be run in the Cloud. Moreover, the codes of making the offloading decisions are automatically inserted into the original source code. We also conducted the real experiments to show the applicability of our MCAF.

Heterogeneous and Elastic Computation Framework for Mobile Cloud Computing

2014 ◽  
Vol 24 (07) ◽  
pp. 1013-1037 ◽  
Author(s):  
Chi-Sheng Shih ◽  
Joen Chen ◽  
Yu-Hsin Wang ◽  
Norman Chang
Keyword(s):  
Mobile Devices ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Network Capacity ◽  
Physical Computation ◽  
Imprecise Computation ◽  
Cloud Servers ◽  
Real Time Computing ◽  
And Storage ◽  
Computing Literature

The number and variety of applications for mobile devices continue to grow. However, the resources on mobile devices including computation and storage do not keep pace with the growth. How to incorporate the computation capacity on cloud servers into mobile computing has been desired and challenge issues to resolve. In this work, we design an elastic computation framework to take advantage the heterogeneous computation capacity on cloud servers, which consist of CPUs and GPGPUs, to meet the computation demands of ever growing mobile applications. The computation framework extends OpenCL framework to link remote processors with local mobile applications. The framework is flexible in the sense that the computation can be stopped at any time and gains results, which is called imprecise computation in real-time computing literature. The framework has been evaluated against OpenCL benchmark and physical computation engine for gaming. The results show that the framework supports OpenCL benchmark, RODINIA, without modifying the codes with few exceptions. The elastic computation framework allows the cloud servers to support more mobile clients without sacrificing their QoS requirements. The experiment results also show that IO intensive applications do not perform well when the network capacity is insufficient or unreliable.

scholarly journals Mobile cloud is the infrastructure that facilitates the offloading of storage and computing resources of mobile devices pertaining mobile applications to cloud computing. Mobile devices can run expensive applications using mobile cloud as they can outsour

2018 ◽  
Vol 1 (22) ◽  
pp. 759-772
Author(s):  
Riyadh R. Nuiaa
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Pervasive Computing ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Cloud Infrastructure ◽  
Security Issues ◽  
Secure Channels ◽  
Cloud Users

Mobile cloud is the infrastructure that facilitates the offloading of storage and computing resources of mobile devices pertaining mobile applications to cloud computing. Mobile devices can run expensive applications using mobile cloud as they can outsource services to cloud while providing interface for mobile users. Emerging mobile applications that are expensive can overcome the inherent problems of hand held devices through the concept of mobile cloud computing. The offloading process provide mobiles a rich platform for pervasive computing with on-demand services linked to cloud computing through mobile cloud infrastructure. Thus the mobile cloud computing is an inevitable phenomenon which bring about plethora of pros besides the mobility. The mobile cloud users can perform their resource intensive operations on the fly without time and geographical restrictions. In spite of the advantages it bestows mobile cloud computing has its own security issues. This paper throws light into the security issues and solutions in terms of secure channels transmission in mobile cloud computing. In this paper, we present state-of-the-art of mobile cloud computing besides its security aspects that are to be taken care of for successful mobile cloud computing.

Mobile Cloud Computing

2015 ◽  
pp. 1-23
Author(s):  
Jyoti Grover ◽  
Gaurav Kheterpal
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Storage ◽  
Mobile Applications ◽  
Large Scale ◽  
Mobile Cloud Computing ◽  
Research Area ◽  
Computation Offloading ◽  
Mobile Cloud ◽  
Mobile Environment

Mobile Cloud Computing (MCC) has become an important research area due to rapid growth of mobile applications and emergence of cloud computing. MCC refers to integration of cloud computing into a mobile environment. Cloud providers (e.g. Google, Amazon, and Salesforce) support mobile users by providing the required infrastructure (e.g. servers, networks, and storage), platforms, and software. Mobile devices are rapidly becoming a fundamental part of human lives and these enable users to access various mobile applications through remote servers using wireless networks. Traditional mobile device-based computing, data storage, and large-scale information processing is transferred to “cloud,” and therefore, requirement of mobile devices with high computing capability and resources are reduced. This chapter provides a survey of MCC including its definition, architecture, and applications. The authors discuss the issues in MCC, existing solutions, and approaches. They also touch upon the computation offloading mechanism for MCC.

scholarly journals Mobile Cloud Computing as Competence Intensifier

2019 ◽  
Vol 8 (06) ◽  
pp. 24693-24697
Author(s):  
Neeta P. Sarode ◽  
Dr. J.W. Bakal
Keyword(s):  
Cloud Computing ◽  
Ubiquitous Computing ◽  
Mobile Devices ◽  
Mobile Learning ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Personal Digital Assistants ◽  
Mobile Cloud ◽  
Advantages And Disadvantages ◽  
Actual Existence

Since the arrival of mobile devices, such as Personal Digital Assistants (PDA’s), smartphones, tablets etc., and their amalgamation with cloud computing is bringing up and transforming ubiquitous computing into actual existence. This concept of ubiquitous computing straightens out the way to unusual and experimental applications, in which the mobile devices are integrated and provide assistance to the users. This paper discusses about the concept of mobile cloud computing, identify advantages and disadvantages of collaborating mobile applications with cloud and identify benefits of leveraging mobile learning services on cloud. Mobile cloud computing induces innumerable benefits and overcomes the technical limitations of mobile learning.

scholarly journals On the impact of sampling frequency on software energy measurements

2015 ◽  
Author(s):  
Rubén Saborido ◽  
Venera Arnaoudova ◽  
Giovanni Beltrame ◽  
Foutse Khomh ◽  
Giuliano Antoniol
Keyword(s):  
Energy Consumption ◽  
Mobile Applications ◽  
High Frequency ◽  
Sampling Frequency ◽  
Low Frequencies ◽  
Median Error ◽  
Android Applications ◽  
Reduce Energy Consumption ◽  
The Impact ◽  
Closed Source

Energy consumption is a major concern when developing and evolving mobile applications and researchers are investigating ways to reduce energy consumption. We conjecture that these studies are at the border between hardware and software and we must be careful on how the energy consumption is measured. To the best of our knowledge, no previous work investigates how much energy and power consumption is due to high frequency events missed when sampling at low frequencies such as 10 kHz and verified the error at the precision of method level. In this paper, we propose an approach for accurate measurements of the energy consumption of mobile applications. We apply the proposed approach to assess the energy consumption of 21 mobile, closed source, applications and four open source Android applications. We show that by sampling at 10 kHz one may expect a median error of 8%, however, such error may be as high as 50%.

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 Constraints Based Heuristic Approach for Task Offloading In Mobile Cloud Computing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Raj Kumari, Sakshi Kaushal
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Applications ◽  
Mobile Cloud Computing ◽  
Computation Time ◽  
Mobile Cloud ◽  
Delay Sensitive ◽  
Communication Time ◽  
Delay Tolerant ◽  
Task Offloading

Mobile devices are supporting a wide range of applications irrespective of their configuration. There is a need to make the mobile applications executable on mobile devices without concern of battery life. For optimizing mobile applications computational offloading is highly preferred. It helps to overcome the severity of scarce resources constraint mobile devices. In offloading, which part of the application to be offloaded, on which processor and what is available bandwidth rate are the main crucial issues. As subtasks of mobile applications are interdependent, efficient execution of application requires research of favorable wireless network conditions before to take the offloading decision. Broadly in mobile cloud computing the applications is either delay sensitive or delay tolerant. For delay sensitive applications completion time has the highest priority whereas for delay tolerant type of applications depending on the network conditions decision of offloading can be taken. Sometimes, computation time on a cloud server is less but it consumes high communication time which ultimately gives inefficient offloading results. To address this issue, we have proposed a heuristic based level wise task offloading (HTLO). It includes computation time, communication time and maximum energy available on the mobile device to take the decision of offloading. For simulation study, a mobile application is considered as a directed graph and all the tasks are executed on the basis of their levels. The overall results of the proposed heuristic approach are compared with state-of-the-art K-M LARAC algorithm and results show the improvement in execution time, communication time, mobile device energy consumption and total energy consumption.

scholarly journals A Novel Encryption and Decryption of Data using Mobile Cloud Computing Platform

2021 ◽  
Vol 2 (3) ◽  
pp. 118-122
Author(s):  
Dr. Jennifer S. Raj
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Data Sharing ◽  
Mobile Cloud Computing ◽  
Mobile Cloud ◽  
Security Level ◽  
Computing Platform ◽  
Fine Grain ◽  
Security Proof ◽  
Cloud Servers

As the need for super-fast mobile devices incorporating cloud computing technology continues to be the need of the hour, Mobile Cloud Computing (MCC) serves as the platform for mobile users to share data with others, store information on the cloud and also compute using the data. Over the years, the most widely preferred encryption that has proven to be reliable is Attribute Based Encryption (ABE). However, this encryption methodology requires expensive pairing operation which makes it unsuitable for MCC. As a result of this, MCC remains slow in reaching the crowd due to the challenge of resource-constrained mobile devices. To tackle this resource-constraint we propose a novel method of outsourcing operations to resource-rich cloud servers so that the constraint on resources does not hinder proper functioning of the mobile device. There are a number of advantages when data sharing is incorporated with lightweight fine-grain data sharing methodology. This method has a number of advantages such as CCA security level, resisting decryption key exposure and supporting verifiable outsourced decryption. Simulation results indicate that the performance analysis and concrete security proof is apt for MCC environment.

scholarly journals FEATHER: A Proposed Lightweight Protocol for Mobile Cloud Computing Security

2020 ◽  
Vol 10 (4) ◽  
pp. 6116-6125
Author(s):  
A. Alamer ◽  
B. Soh
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Communication Channel ◽  
Mobile Cloud Computing ◽  
Security Protocol ◽  
Mobile Cloud ◽  
Battery Power ◽  
Cloud Server ◽  
Cloud Servers ◽  
Short Time

Ensuring security for lightweight cryptosystems in mobile cloud computing is challenging. Encryption speed and battery consumption must be maintained while securing mobile devices, the server, and the communication channel. This study proposes a lightweight security protocol called FEATHER which implements MICKEY 2.0 to generate keystream in the cloud server and to perform mobile device decryption and encryption. FEATHER can be used to implement secure parameters and lightweight mechanisms for communication among mobile devices and between them and a cloud server. FEATHER is faster than the existing CLOAK protocol and consumes less battery power. FEATHER also allows more mobile devices to communicate at the same time during very short time periods, maintain security for more applications with minimum computation ability. FEATHER meets mobile cloud computing requirements of speed, identity, and confidentiality assurances, compatibility with mobile devices, and effective communication between cloud servers and mobile devices using an unsafe communication channel.

scholarly journals Research gaps based virtualization in mobile cloud computing

2020 ◽  
Vol 10 (51) ◽  
pp. 212-222
Author(s):  
Boubakeur Annane ◽  
Adel Alti ◽  
Osman Ghazali
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Virtual Machines ◽  
Cloud Services ◽  
Security And Privacy ◽  
Battery Life ◽  
Mobile Cloud ◽  
Sensitive Data ◽  
Cloud Servers

Recently, mobile computing is known as a fast-growing utilization of people's daily life. However, the main is the limited mobile devices’ resources such as processing capability, storage space and battery life. With the development of cloud computing, mobile devices’ resources are improved with the help of cloud services, which resulted an emerged technology named Mobile Cloud Computing (MCC). Although the MCC has several advantages for mobile users, it is also challenged by many critical issues like security and privacy of the mobile user's data that offloaded on the cloud’ servers and processed on the virtual machines (VMs). In virtualization, various investigations showed that malicious users are able to break down the cloud security methods by spreading their VMs in order to alter or violate the user sensitive data that executed on cloud’ VMs. This paper deeply analyzes the recent MCC based virtualization approaches and methods by criticizing them. We found out that no approach protects the data from being stolen while distributed VMs that deployed on different cloud servers exchanging data. Hence, the paper provides practical gaps related to virtualization in MCC and future perspectives.

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