소프트웨어 공학 : 모바일 클라우드 컴퓨팅을 위한 QoS 안정화 기법 = Software Engineering : Methods for Stabilizing QoS in Mobile Cloud Computing

다국어 초록 (Multilingual Abstract)

Mobile devices have limited computing power and resources. Since mobile devices are equipped with rich network connectivity, an approach to subscribe cloud services can effectively remedy the problem, which is called Mobile Cloud Computing (MCC). Most works on MCC depend on a method to offload functional components at runtime. However, these works only consider the limited verion of offloading to a pre-defined, designated node. Moveover, there is the limitation of managing services subscribed by applications. To provide a comprehensive and practical solution for MCC, in this paper, we propose a self-stabilizing process and its management-related methods. The proposed process is based on an autonomic computing paradigm and works with diverse quality remedy actions such as migration or replicating services. And, we devise a pratical offloading mechanism which is still in an initial stage of the study. The proposed offloading mechanism is based on our proposed MCC meta-model. By adopting the self-stabilization process for MCC, many of the technical issues are effectively resolved, and mobile cloud environments can maintain consistent levels of quality in autonomous manner.

참고문헌 (Reference)

1 H. Ludwig, "Web Service Level Agreement (WSLA) Language Specification, Version 1.0"

2 G.H. Forman, "The Challenges of Mobile Computing" 27 (27): 38-47, 1994

3 M. Satyanarayanan, "The Case for VM-Based Cloudlets in Mobile Computing" 8 (8): 14-23, 2009

4 Lee, J.Y., "Software Approaches to Assuring High Scalability in Cloud Computing" 300-306, 2010

5 P.K. Balan, "Simplifying Cyber Foraging for Mobile Devices" 272-285, 2007

6 Y. Natchetoi, "Service-Oriented Architecture for Mobile Applications" 27-32, 2008

7 S. Kalasapur, "Scavenger: Transparent Development of Efficient Cyber Foraging Applications" 217-226, 2010

8 K. Yang, "On Effective Offloading Services for Resource-Constrained Mobile Devices Running Heavier Mobile Internet Applications" 46 (46): 56-63, 2008

9 M. Fernando, "Mobile Cloud Computing: A Survey" 29 : 84-106, 2013

10 Harrington, P., "Machine Learning in Action" Manning Publication 2012

11 E.Cuervo, "MAUI: Making Smarphones Last Longer with Code Offloaded" 49-62, 2010

12 Cormen, T.H., "Introduction to Algorithms, Third Edition" The MIT Press 2009

13 F. Gillett, "Future View: The New tech Ecosystems of Cloud, Cloud Services, And Cloud Computing" Forrester Research 2008

14 S.H. Hung, "Executing Mobile Applications on the Cloud: Framework and Issues" 63 (63): 573-587, 2012

15 B.G. Chun, "Dynamically Partitioning Applications between Weak Devices and Clouds" 2010

16 E. Gamma, "Design patterns: elements of reusable object-oriented software" Addison-Wesley 1995

17 X. Li, "Deploying Mobile Computation in Cloud Service, Proc. 1st Int’l Conf. on Cloud Computing (CloudCom 2009)" 5931 : 301-311, 2009

18 Witten, I.H., "Data Mining: Practical Machine Learning Tools and Techniques, Third Edition" Morgan Kaufmann 2011

19 K. Kumar, "Cloud Computing for Mobile Users: Can Offloading Computation Save Energy?" 43 (43): 51-56, 2010

20 B.G. Chun, "CloneCloud: Elastic Execution between Mobile Device and Cloud" 301-314, 2011

21 B. König-Ries, "Challenges in Mobile Application Development" 52 (52): 69-71, 2009

22 J. Flinn, "Balancing Performance, Energy, and Quality in Pervasive Computing" 217-226, 2002

23 S. Malek, "An Architecture-driven Software Mobility Framework" 83 : 972-989, 2010

24 S. Han, "An Adaptable Software Architecture based on Mobile Components in Pervasive Computing" 309-311, 2005

25 L. Guan, "A Survey of Research on Mobile Cloud Computing" 387-392, 2011

26 M. Sharifi, "A Survey and Taxonomy of Cyber Foraging of Mobile Devices" 2007

27 Lee, J.Y., "A Practical Framework for Self-Stabilization in Service-based Mobile Ecosystem"

28 Y. Ye, "A Framework for QoS and Power Management in a Service Cloud environment with Mobile Devices" 236-343, 2010