Mobile cloud computing for computation offloading: Issues and challenges

International audienceDespite the evolution and enhancements that mobile devices have experienced, they are still considered as limited computing devices. Today, users become more demanding and expect to execute computational intensive applications on their smartphone devices. Therefore, Mobile Cloud Computing (MCC) integrates mobile computing and Cloud Computing (CC) in order to extend capabilities of mobile devices using offloading techniques. Computation offloading tackles limitations of Smart Mobile Devices (SMDs) such as limited battery lifetime, limited processing capabilities , and limited storage capacity by offloading the execution and workload to other rich systems with better performance and resources. This paper presents the current offloading frameworks, computation offloading techniques, and analyzes them along with their main critical issues. In addition , it explores different important parameters based on which the frameworks are implemented such as offloading method and level of partitioning. Finally, it summarizes the issues in offloading frameworks in the MCC domain that requires further research

Context-Aware Computation Offloading for Mobile Cloud Computing: Requirements Analysis, Survey and Design Guideline

AbstractAlong with the rise of mobile handheld devices the resource demands of respective applications grow as well. However, mobile devices are still and will always be limited related to performance (e.g., computation, storage and battery life), context adaptation (e.g., intermittent connectivity, scalability and heterogeneity) and security aspects. A prominent solution to overcome these limita- tions is the so-called computation offloading, which is the focus of mobile cloud computing (MCC). However, current approaches fail to address the complexity that results from quickly and constantly changing context conditions in mobile user scenarios and hence developing effective and efficient MCC applications is still challenging. Therefore, this paper first presents a list of re- quirements for MCC applications together with a survey and classification of current solutions. Furthermore, it provides a design guideline for the selection of suitable concepts for different classes of common cloud-augmented mobile applications. Finally, it presents open issues that developers and researchers should be aware of when designing their MCC-approach

Towards Distributed Mobile Computing

In the latest years, we observed an exponential growth of the market of the mobile devices. In this scenario, it assumes a particular relevance the rate at which mobile devices are replaced. According to the International Telecommunicaton Union in fact, smart-phone owners replace their device every 20 months, on average. The side effect of this trend is to deal with the disposal of an increasing amount of electronic devices which, in many cases, arestill working. We believe that it is feasible to recover such an unexploited computational power. Through a change of paradigm in fact, it is possible to achieve a two-fold objective: 1) extend the mobile devices lifetime, 2) enable a new opportunity to speed up mobile applications. In this paper we aim at providing a survey of state-of-art solutions aim at going in the direction of a Distributed Mobile Computing paradigm. We put in evidence the challenges to be addressed in order to implement this paradigm and we propose some possible future improvements

Enhanced mobile computing using cloud resources

Summary in English.Includes bibliographical references.The purpose of this research is to investigate, review and analyse the use of cloud resources for the enhancement of mobile computing. Mobile cloud computing refers to a distributed computing relationship between a resource-constrained mobile device and a remote high-capacity cloud resource. Investigation of prevailing trends has shown that this will be a key technology in the development of future mobile computing systems. This research presents a theoretical analysis framework for mobile cloud computing. This analysis framework is a structured consolidation of the salient considerations identified in recent scientific literature and commercial endeavours. The use of this framework in the analysis of various mobile application domains has elucidated several significant benefits of mobile cloud computing including increases in system performance and efficiency. Based on recent scientific literature and commercial endeavours, various implementation approaches for mobile cloud computing have been identified, categorized and analysed according to their architectural characteristics. This has resulted in a set of advantages and disadvantages for each category of system architecture. Overall, through the development and application of the new analysis framework, this work provides a consolidated review and structured critical analysis of the current research and developments in the field of mobile cloud computing

Multisite adaptive computation offloading for mobile cloud applications

The sheer amount of mobile devices and their fast adaptability have contributed to the proliferation of modern advanced mobile applications. These applications have characteristics such as latency-critical and demand high availability. Also, these kinds of applications often require intensive computation resources and excessive energy consumption for processing, a mobile device has limited computation and energy capacity because of the physical size constraints. The heterogeneous mobile cloud environment consists of different computing resources such as remote cloud servers in faraway data centres, cloudlets whose goal is to bring the cloud closer to the users, and nearby mobile devices that can be utilised to offload mobile tasks. Heterogeneity in mobile devices and the different sites include software, hardware, and technology variations. Resource-constrained mobile devices can leverage the shared resource environment to offload their intensive tasks to conserve battery life and improve the overall application performance. However, with such a loosely coupled and mobile device dominating network, new challenges and problems such as how to seamlessly leverage mobile devices with all the offloading sites, how to simplify deploying runtime environment for serving offloading requests from mobile devices, how to identify which parts of the mobile application to offload and how to decide whether to offload them and how to select the most optimal candidate offloading site among others. To overcome the aforementioned challenges, this research work contributes the design and implementation of MAMoC, a loosely coupled end-to-end mobile computation offloading framework. Mobile applications can be adapted to the client library of the framework while the server components are deployed to the offloading sites for serving offloading requests. The evaluation of the offloading decision engine demonstrates the viability of the proposed solution for managing seamless and transparent offloading in distributed and dynamic mobile cloud environments. All the implemented components of this work are publicly available at the following URL: https://github.com/mamoc-repo

Mobile resource management load balancing strategy

This paper is dealing with mobile resource management that distributes mobile device processes between cloud computing virtual machine and mobile device. Expectation is that mobile device user experience will increase. Load balancing is an important part of mobile resource management. In order to be able to solve load balancing issues, discussion is made how currently available methods can be adapted to our resource manager. In this article, we investigate load balancing procedures, methods and their customization, with a particular attention on mobile and cloud computing requirements. As a result, we expect that important design aspects will become apparent. Profile based load balancing method is recommended, what combines static and dynamic load balancing strategy. Using profile to identify usage scenario of mobile device can lead to increased system responsiveness, thus experience improvement