Delay-Energy Tradeoff in Mobile Cloud Computing: An Experimental Approach (original) (raw)

MOBILE CLOUD COMPUTING: OFFLOADING MOBILE PROCESSING TO THE CLOUD

The current proliferation of mobile systems, such as smart phones, PDA and tablets, has led 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. However, this convergence penalizes the mobile system in computational resources such as processor speed, memory consumption, disk capacity, as well as in weight, size, ergonomics and the user’s most important component, battery life. Therefore, this current trend aims towards the efficient and effective use of its hardware and software components. Hence, energy consumption and response time are major concerns when executing complex algorithms on mobile devices because they require significant resources to solve intricate problems. Current cloud computing environments for performing complex and data intensive computation remotely are likely to be an excellent solution for off-loading computation and dat...

A Review on Energy Efficient Computation Offloading Frameworks for Mobile Cloud Computing

Mobile Cloud Computing is an evolving technology that integrates the concept of cloud computing into the mobile environment. Smartphones are boon in the world of technology but they have certain limitations (e.g. battery life, network bandwidth, storage, energy) when running complex applications which require large computations. Using Cloud Computing in mobile phones, these limitations can be addressed. Certain frameworks have been proposed over the years that can address the issues in mobile cloud computing. These frameworks allow the computation to be offloaded in the cloud environment resulting improvementin the battery life, bandwidth, memory capacity and energy consumption in the smartphones. This paper provides the extensive surveyon the various energy efficient frameworks available to offload the computation from the mobile to the cloud environment. INTRODUCTION Smart Mobile Devices (SMDs) such as smart-phones and tablets Personal Computers (PCs) have become important part of daily life. Nowadays, mobile devices are not only used for voice calls but are efficiently able to run heavy and complicated mobile applications using internet. The volume of data being processed by smartphones and complexity of mobile applications are increasing day by day. However, these SMD has certain limitations such as network bandwidth, battery lifeand storage capacity and processor performance. With the advancement in technology over the years, SMD provide multi-core processors, large memory, bigger and sharper screens, multiple sensors as well as enormous applications. All these together put heavy burden on the battery life of smart phones. Cloud computing (CC) provides a wide variety of computing resources from servers and storage to enterprise applications. Cloud computing is a hosting environment that is immediate, flexible, scalable, secure and available. The computing resources from cloud can be easily and quickly accessed and released after use with very less management effort. The concept of CC can be used in mobile applications running on SMDs to boost up their performance. With the integration and support of CC into the complex mobile applications, the term Mobile Cloud Computing (MCC) arises. MCC provides an infrastructure where the data processing and the data storage of mobile cloud applications occur away from the mobile device and into the cloud and bringing applications and mobile computing to a much broader range of mobile subscribers [1]. One of the key features of MCC is migrating the computation intensive tasks to cloud or servers for their executionand then receiving the results from these servers which is known as Computation Offloading. Mobile Devices take advantage of resource-rich infrastructures by offloading the computation to cloud for saving battery's energy consumption and hence increasing battery lifetime of mobiles. Computation offloading allows SMDs to become more capable. In contrast to traditional client-server architecture, where clients always offloads the computation to the server and are completely dependent on it, the computational offloading migrates programs to servers which are outside of the user's computing environment. The term " surrogate computing " or " cyber foraging " is also used for computation offloading.

Energy Efficiency in Mobile Cloud Computing: Total Offloading Selectively Works. Does Selective Offloading Totally Work?

2011

Many emerging mobile applications nowadays tend to be computation-intensive due to the increasing popularity and convenience of smartphones. Nevertheless, a major obstacle prohibits the direct adoption of such applications and that is battery lifetime. Mobile Cloud Computing (MCC) is a promising solution that suggests the partial processing of applications on the cloud to minimize the overall power consumption at the mobile device. However, this does not necessarily save energy if there is no systematic mechanism for evaluating the effect of offloading the application into the cloud. In this paper, we study the factors affecting the power consumption due to offloading, develop a decision model, and verify its correctness by real implementation on an Android device. The results show that the proposed partitioning scheme successfully results in energy savings at the mobile handset and surpasses the energy efficiency of both fully local and fully remote execution.

Mobility and Execution Time Aware Task Offloading in Mobile Cloud Computing

International Journal of Interactive Mobile Technologies (iJIM)

Nowadays, mobile devices perform almost all tasks that can be performed by a computer but empties the battery and consumes memory. It is not necessary to execute the tasks on mobile devices; instead, it is executed in the far-away cloud. To save battery energy, the tasks are offloaded and hopped through several access points to reach the cloud and executed which increased the execution time of the task. Therefore, to save execution time and energy, the tasks are offloaded to a nearby cloudlet and as the device moves, the cloudlet and mobile device are disconnected. The mobile device is connected to the next cloudlet; while the offloaded tasks are partially executed in the previous cloudlet VM migrates to the new cloudlet. The previous cloudlet examined the remaining execution time of the task. If it is less than the connection time, the task is finished and the result is transferred to the new cloudlet; otherwise, the task is offloaded to the new cloudlet. It is seen that the mobil...

Energy-aware dynamic task offloading and collective task execution in mobile cloud computing

International Journal of Communication Systems, 2019

There is a good opportunity for enlightening the services of the mobile devices by introducing computational offloading using cloud technology. Offloading is a process for managing the complexity of the mobile environment by migrating computational load to the cloud. The mobile devices oblige the quick response for the offloading requests; it is dependent on network connectivity. The cloud services take long setup time irrespective of network connectivity. In this paper, new system architecture for the dynamic task offloading in the mobile cloud environment is proposed. The architecture includes the offloading algorithm that concentrates on energy consumption of the tasks both in the local and remote environment. The proposed algorithm formulates a collective task execution model for minimizing the energy consumption. The architecture concentrates on the network model by considering the task completion time in three different network scenarios. The experimental results show the efficiency of the suggested architecture in reducing the energy consumption and completion time of the tasks.

Cloud-based computation offloading for mobile devices: State of the art, challenges and opportunities

2013 Future Network & Mobile Summit, 2013

Mobile cloud computing is a new rapidly growing field. In addition to the conventional fashion that mobile clients access cloud services as in the well-known client/server model, existing work has proposed to explore cloud functionalities in another perspective - offloading part of the mobile codes to the cloud for remote execution in order to optimize the application performance and energy efficiency of the mobile device. In this position paper, we investigate the state of the art of code offloading for mobile devices, highlight the significant challenges towards a more efficient cloud-based offloading framework, and also point out how existing technologies can provide us opportunities to facilitate the framework implementation.

Accelerating Mobile-Cloud Computing: A Survey

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, we 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. We 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.

Towards the optimization of power and bandwidth consumption in mobile-cloud hybrid applications

2017 Second International Conference on Fog and Mobile Edge Computing (FMEC), 2017

Mobile devices can now support a wide range of applications, many of which demand high computational power. Backed by the virtually unbounded resources of cloud computing, today's mobile-cloud (MC) computing can meet the demands of even the most computationally and resource intensive applications. However, many existing MC hybrid applications are inefficient in terms of achieving objectives like minimizing battery power consumption and network bandwidth usage, which form a tradeoff. To counter this problem we propose a technique that: 1) measures, at run time, how well the MC application meets these two objectives; and 2) allows arbitrary configurations to be applied to the MC application in order to optimize the efficiency tradeoff. Our experimental evaluation considers two MC hybrid applications. We modularized them first, based on computationally-intensive tasks, and then executed them using a simple MC framework while measuring the power and bandwidth consumption at run-time. Analysis of results shows that efficient configurations of the apps can be obtained in terms of minimizing the two objectives. However, there remain challenges such as scalability and automation of the process, which we discuss.

Cloud Computing for Mobile Users: Can Offloading Computation Save Energy

IEEE Computer, 2010

Mobile systems, such as smart phones, have become the primary computing platform for many users. Various studies have identified longer battery lifetime as the most desired feature of such systems. A 2005 study of users in 15 countries 3 found longer battery life to be more important than all other features, including cameras or storage. A survey last year by ChangeWave Research 4 revealed short battery life to be the most disliked characteristic of Apple's iPhone 3GS, while a 2009 Nokia poll showed that battery life was the top concern of music phone users.

Classification of Energy Efficiency in Mobile Cloud Computing

Advances in Information Communication Technology and Computing, 2020

Mobile cloud computing (MCC) is a methodology, which is developed due to the inability of mobile devices to process large of amount of data and utilize less amount of energy as such the computers that can process the large amount data as compared to mobile devices. So in order overcome this problem, MCC came into existence which is used to increase the computation power and utilize energy of mobile devices that is required to process large data; to overcome this issue, there are several techniques that we discuss in this paper and their proposed solution to enhance the computation ability of mobile devices by using less energy. Techniques involve in taking off the data from mobile devices to the cloud server and perform the computation in cloud server, and when the computation of data is completed, then send back that particular data to the mobile devices. Thus, this paper studies about how to reduce the energy consumption of mobile devices by using certain parameters such as bandwidth and execution time.