Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges (1306.4956v1)

Abstract: Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions.

• The paper presents a comprehensive taxonomy of cloud-based mobile augmentation, categorizing approaches such as distant, proximate, and hybrid solutions.
• The paper analyzes methodologies like application partitioning and virtualized screen outsourcing to overcome mobile limitations such as processing power and battery life.
• The paper highlights open challenges including security risks, energy consumption, and development complexity, guiding future research priorities.

Cloud-Based Augmentation for Mobile Devices: An Overview

The paper "Cloud-Based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges" explores the burgeoning field of Cloud-based Mobile Augmentation (CMA). The authors, Abolfazli et al., provide a comprehensive survey addressing various dimensions of augmenting mobile devices using cloud infrastructures. The work is significant as it scrutinizes the motivations, methodologies, and challenges associated with CMA, offering a valuable taxonomy of current approaches.

Key Components and Taxonomy

Motivation for CMA:

Mobile devices have inherent limitations such as inadequate processing power, limited energy resources, and restricted local storage. The authors argue that these intrinsic deficiencies necessitate augmentation strategies to meet the escalating computational demands of modern mobile applications. Cloud infrastructures offer a viable solution by extending devices' capabilities through remote resources, allowing for the execution of resource-intensive tasks.

CMA Approaches:

The paper categorizes cloud-based resources used for augmentation into four primary types: distant immobile clouds, proximate immobile computing entities, proximate mobile computing entities, and hybrid solutions. This classification is crucial for understanding the trade-offs between latency, computing power, and reliability. While distant clouds offer extensive computational power, proximate entities typically provide reduced latency, and hybrid models seek to blend these benefits.

Methodologies:

Various CMA strategies are dissected, such as CloneCloud, which utilizes application partitioning, and Virtualized Screen techniques that focus on outsourcing the rendering process. These methodologies demonstrate the diversity in technical execution, ranging from thread-level migration to leveraging cloud storage for data safety and expanding device capabilities.

Implications and Challenges

Theoretical and Practical Implications:

The authors emphasize the transformative potential of CMA in mobile computing. By reducing battery consumption and augmenting processing capabilities, CMA enables more complex applications to run effectively on mobile devices. Furthermore, the enhanced data safety and access ubiquity made possible by cloud storage expand the potential applications of mobile devices.

Challenges:

Despite these advantages, numerous challenges impede the widespread adoption of CMA. The authors highlight issues such as energy consumption related to data transmission, security risks associated with cloud storage, and the complexity of application development in a heterogeneous cloud environment. Addressing these challenges requires advancements in wireless communication technologies and more sophisticated cloud service architectures.

Future Directions

Speculating on future advancements, the paper identifies the need for a standard reference architecture for CMA development, seamless application mobility, and improved security mechanisms. These potential developments are crucial for realizing the full potential of CMA technologies in enhancing mobile computing experiences.

Conclusion

The survey presented in this paper offers a nuanced examination of cloud-based mobile augmentation, advancing our understanding of its practical applications and inherent challenges. As mobile computing continues to evolve, the insights provided by this taxonomy and analysis will be instrumental in guiding future research and development in the field. The authors' contributions lay the groundwork for more resilient, efficient, and secure mobile-cloud ecosystems.