scholarly journals Mobile Cloud Computing: Offloading Mobile Processing to the Cloud

2016 ◽  
Vol 9 (1) ◽  
pp. 90
Author(s):  
Sanjay P. Ahuja ◽  
Jesus Zambrano
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Mobile Devices ◽  
Response Times ◽  
Mobile Apps ◽  
Mobile Systems ◽  
Battery Life ◽  
Data Intensive ◽  
Computing Platforms ◽  
Computational Resources

<p class="zhengwen">The current proliferation of mobile systems, such as smart phones and tablets, has let to their adoption as the primary computing platforms for many users. This trend suggests that designers will continue to aim towards the convergence of functionality on a single mobile device (such as phone + mp3 player + camera + Web browser + GPS + mobile apps + sensors). However, this conjunction penalizes the mobile system both with respect to computational resources such as processor speed, memory consumption, disk capacity, and in weight, size, ergonomics and the component most important to users, battery life. Therefore, energy consumption and response time are major concerns when executing complex algorithms on mobile devices because they require significant resources to solve intricate problems.</p><p>Offloading mobile processing is an excellent solution to augment mobile capabilities by migrating computation to powerful infrastructures. Current cloud computing environments for performing complex and data intensive computation remotely are likely to be an excellent solution for offloading computation and data processing from mobile devices restricted by reduced resources. This research uses cloud computing as processing platform for intensive-computation workloads while measuring energy consumption and response times on a Samsung Galaxy S5 Android mobile phone running Android 4.1OS.</p>

Accelerating Mobile-Cloud Computing

2015 ◽  
pp. 1933-1955
Author(s):  
Tolga Soyata ◽  
He Ba ◽  
Wendi Heinzelman ◽  
Minseok Kwon ◽  
Jiye Shi
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
High Speed ◽  
Mobile Cloud Computing ◽  
Response Times ◽  
State Of The Art ◽  
The State ◽  
Mobile Cloud ◽  
Computational Resources ◽  
Traditional Approaches

With the recent advances in cloud computing and the capabilities of mobile devices, the state-of-the-art of mobile computing is at an inflection point, where compute-intensive applications can now run on today's mobile devices with limited computational capabilities. This is achieved by using the communications capabilities of mobile devices to establish high-speed connections to vast computational resources located in the cloud. While the execution scheme based on this mobile-cloud collaboration opens the door to many applications that can tolerate response times on the order of seconds and minutes, it proves to be an inadequate platform for running applications demanding real-time response within a fraction of a second. In this chapter, the authors describe the state-of-the-art in mobile-cloud computing as well as the challenges faced by traditional approaches in terms of their latency and energy efficiency. They also introduce the use of cloudlets as an approach for extending the utility of mobile-cloud computing by providing compute and storage resources accessible at the edge of the network, both for end processing of applications as well as for managing the distribution of applications to other distributed compute resources.

scholarly journals Approaches to Address the Operational Limitations of MANETs through Ad Hoc Mobile Cloud Computing Paradigm

2020 ◽  
Vol 14 (09) ◽  
pp. 153
Author(s):  
Muralidhar Kurni ◽  
Madhavi K
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Ad Hoc ◽  
Mobile User ◽  
Battery Life ◽  
Computing Platform ◽  
Computing Paradigm ◽  
Cloud Computing Service ◽  
Mobile Ad Hoc ◽  
Computing Platforms

Mobile Ad hoc Networks (MANETs) are getting essential to wireless communications because of the growing popularity of mobile devices. However, mobile devices face several challenges in their resources (eg., battery life, storage, and bandwidth) and communication (e.g., mobility and, security). Limited resources considerably impede the improvement of service qualities. MCC permits resources in cloud computing platforms to be used to overcome the dearth of native resources in mobile devices. However, this hinders a mobile user from taking part in a cloud computing service if a connection to the cloud computing platform is both unobtainable or too dear to afford. Therefore, an initial solution will be to use resources from nearby devices instantly. Such a paradigm is known as mobile ad hoc cloud computing where each mobile device can use the services and resources of its neighbor devices. This paper shortly explains the contributions done by us to overcome the three vital operational limitations of mobile devices namely connectivity, storage and, processing capability through the Mobile Ad Hoc Cloud Computing Paradigm. The potential promise of the proposed approaches is evaluated through simulations. Our proposals, taken together intend to increase the operational efficiency of MANETs.

Accelerating Mobile-Cloud Computing

2013 ◽  
pp. 175-197 ◽  
Author(s):  
Tolga Soyata ◽  
He Ba ◽  
Wendi Heinzelman ◽  
Minseok Kwon ◽  
Jiye Shi
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
High Speed ◽  
Mobile Cloud Computing ◽  
Response Times ◽  
State Of The Art ◽  
The State ◽  
Mobile Cloud ◽  
Computational Resources ◽  
Traditional Approaches

With the recent advances in cloud computing and the capabilities of mobile devices, the state-of-the-art of mobile computing is at an inflection point, where compute-intensive applications can now run on today’s mobile devices with limited computational capabilities. This is achieved by using the communications capabilities of mobile devices to establish high-speed connections to vast computational resources located in the cloud. While the execution scheme based on this mobile-cloud collaboration opens the door to many applications that can tolerate response times on the order of seconds and minutes, it proves to be an inadequate platform for running applications demanding real-time response within a fraction of a second. In this chapter, the authors describe the state-of-the-art in mobile-cloud computing as well as the challenges faced by traditional approaches in terms of their latency and energy efficiency. They also introduce the use of cloudlets as an approach for extending the utility of mobile-cloud computing by providing compute and storage resources accessible at the edge of the network, both for end processing of applications as well as for managing the distribution of applications to other distributed compute resources.

Cloud and Mobile

2016 ◽  
pp. 1-20 ◽  
Author(s):  
Antonio Miguel Rosado da Cruz ◽  
Sara Paiva
Keyword(s):  
Cloud Computing ◽  
Mobile Computing ◽  
Mobile Devices ◽  
Mobile Apps ◽  
Mobile Technologies ◽  
Future Research ◽  
Mobile Cloud ◽  
Research Projects ◽  
Research Directions ◽  
Future Research Directions

Mobile computing and Cloud computing are two of the most growing technologies in number of users, practitioners and research projects. This chapter surveys mobile technologies and applications, along with cloud computing technologies and applications, presenting their evolution and characteristics. Then, building on mobile devices limitations and mobile apps increasing need of resources, and on the cloud computing ability to overcome those limitations, the chapter presents mobile cloud computing, and characterizes it by addressing approaches to augment mobile devices capabilities. The chapter is settled after some views about future research directions and some concluding remarks.

scholarly journals PATCH-BASED ADAPTIVE IMAGE AND VIDEO WATERMARKING SCHEMES ON HANDHELD MOBILE DEVICES

2021 ◽  
Vol XLIV-2/W1-2021 ◽  
pp. 47-53
Author(s):  
M. N. Favorskaya ◽  
V. V. Buryachenko
Keyword(s):  
Mobile Devices ◽  
Video Watermarking ◽  
Battery Life ◽  
Proxy Server ◽  
Still Images ◽  
Watermark Embedding ◽  
Daily Energy ◽  
Multi Level ◽  
Computational Resources ◽  
Watermarking Scheme

Abstract. Mobile devices provide a huge amount of multimedia information sending to the members of social groups every day. Sometimes it is required to authorize the sending information using the limited computational resources of smartphones, tablets or laptops. The hardest problem is with smartphones, which have the limited daily energy and battery life. There are two scenarios for using mobile watermarking techniques. The first scenario is to implement the embedding and extraction schemes using proxy server. In this case, the watermarking scheme does not differ from conventional techniques, including the advanced ones based on adaptive paradigms, deep learning, multi-level protection, and so on. The main issue is to hide the embedding and extracting information from the proxy server. The second scenario is to provide a pseudo-optimized algorithm respect to robustness, imperceptibility and capacity using limited mobile resources. In this paper, we develop the second approach as a light version of adaptive image and video watermarking schemes. We propose a simple approach for creating a patch-based set for watermark embedding using texture estimates in still images and texture/motion estimates in frames that are highly likely to be I-frames in MPEG notation. We embed one or more watermarks using relevant large-sized patches according to two main criteria: high texturing in still images and high texturing/non-significant motion in videos. The experimental results confirm the robustness of our approach with minimal computational costs.

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

scholarly journals Providing acceleration for mobile gaming as a service

2021 ◽  
Author(s):  
◽  
Jiaqi Wen
Keyword(s):  
Mobile Devices ◽  
Mobile Applications ◽  
Multimedia Applications ◽  
Mobile Systems ◽  
Smart Devices ◽  
Battery Life ◽  
Tracking Accuracy ◽  
Localization Accuracy ◽  
Mobile Gaming ◽  
Interaction Approach

<p>In recent years, the mobile gaming industry has made rapid progress. Developers are now producing numerous mobile games with increasingly immersive graphics. However, these resource-hungry applications inevitably keep pushing well beyond the hardware limits of mobile devices. The limitations causes two main challenging issues for mobile game players. First, limited computational capabilities of smart devices are preventing rich multimedia applications from running smoothly. Second, the minuscule touchscreens impede the players from smoothly interacting with devices as they can do with PCs.   This thesis aims to address the two issues. Specifically, we implement two systems, one for the application accelerations via offloading and the other for alternative interaction approach for mobile gaming. We identify and describe the the challenging issues when developing the systems and describe our corresponding solutions.  Regarding the first system, it is well recognized the performance of GPUs on mobile devices is the bottleneck of rich multimedia mobile applications such as 3D games and virtual reality. Previous attempts to tackle the issue mainly mirgate GPU computation to servers residing in remote datacenters. However, the costly network delay is especially undesirable for highly-interactive multimedia applications since a crisp response time is critical for user experience. In this thesis, we propose GBooster, a system that accelerates GPU-intensive mobile applications by transparently offloading GPU tasks onto neighboring multimedia devices such as SmartTV and Gaming Consoles. Specifically, GBooster intercepts and redirects system graphics calls by utilizing the Dynamic Linker Hooking technique, which requires no modification of the apps and mobile systems. Besides, GBooster intelligently switches between the low-power Bluetooth and the high-bandwidth WiFi interface to reduce energy consumption of network transmissions. We implemented the GBooster on the Android system and evauluate its performance. The results demonstrate that GBooster can boost applications' frame rates by up to {85\%}. In terms of power consumption, GBooster can achieve {70\%} energy saving compared with local execution.   Second, we investigate the potential of built-in mobile device sensors to provide an alternative interaction approach for mobile gaming. We propose UbiTouch, a novel system that extends smartphones with virtual touchpads on desktops using built-in smartphone sensors. It senses a user's finger movement with a proximity and ambient light sensor whose raw sensory data from underlying hardware are strongly dependent on the finger's locations. UbiTouch maps the raw data into the finger's positions by utilizing Curvilinear Component Analysis and improve tracking accuracy via a particle filter. We have evaluate our system in three scenarios with different lighting conditions by five users. The results show that UbiTouch achieves centimetre-level localization accuracy and poses no significant impact on the battery life. We envisage that UbiTouch could support applications such as text-writing and drawing.</p>

scholarly journals Selective Offloading by Exploiting ARIMA-BP for Energy Optimization in Mobile Edge Computing Networks

Algorithms ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 48 ◽  
Author(s):  
Ming Zhao ◽  
Ke Zhou
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Mobile Devices ◽  
Energy Optimization ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Innovative Technique ◽  
Simulation Results ◽  
Bp Model

Mobile Edge Computing (MEC) is an innovative technique, which can provide cloud-computing near mobile devices on the edge of networks. Based on the MEC architecture, this paper proposes an ARIMA-BP-based Selective Offloading (ABSO) strategy, which minimizes the energy consumption of mobile devices while meeting the delay requirements. In ABSO, we exploit an ARIMA-BP model for estimating computation capacity of the edge cloud, and then design a Selective Offloading Algorithm for obtaining offloading strategy. Simulation results reveal that the ABSO can apparently decrease the energy consumption of mobile devices in comparison with other offloading methods.

scholarly journals A Survey on Mobile Cloud Computing: Mobile Computing + Cloud Computing (MCC = MC + CC)

2018 ◽  
Vol 19 (4) ◽  
pp. 309-337 ◽  
Author(s):  
Rama Subbareddy Somula ◽  
Sasikala R
Keyword(s):  
Cloud Computing ◽  
Mobile Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Security And Privacy ◽  
Battery Life ◽  
Mobile Cloud ◽  
Cloud Technology ◽  
Remote Server ◽  
Power Battery

In recent years, the mobile devices become popular for communication and running advanced real time applications such as face reorganization and online games. Although, mobile devices advanced for providing significant benefits for mobile users. But still, these devices suffers with limited recourses such as computation power, battery and storage space due to the portable size. However, The Cloud Technology overcome the limitations of mobile computing with better performance and recourses. The cloud technology provides enough computing recourses to run mobile applications as storage computing power on cloud platform. Therefore, the novel technology called mobile cloud computing (MCC) is introduced by integrating two technologies (Mobile Computing, Cloud Computing) in order to overcome the limitations(such as Battery life, Storage capacity, Processing capacity) of Mobile Devices by offloading application to recourse rich Remote server. This paper presents an overview of MCC, the advantages of MCC, the related concepts and the technology beyond various offloading frameworks, the architecture of the MCC, Cloudlet technology, security and privacy issues and limitations of mobile cloud computing. Finally, we conclude with feature research directions in MCC.

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.

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