Construction of Shared OCCA Model Based on Mobile Agent Technology

Author(s): Jun Zhao*, Tingyu Sheng

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 13 , Issue 6 , 2020


Become EABM
Become Reviewer
Call for Editor

Graphical Abstract:


Abstract:

Background: The Open Cloud Computing Alliance (OCCA) strives for more Cloud Computing Service Providers (CCSP) to join the alliance. OCCA only requires CCSP to provide virtual computing resources and does not care about the methods of the underlying implementation, which leads the open-source cloud computing to a larger scale and more efficient. Due to the differences in service modes and service categories, the cloud computing platforms formed by CCSP are heterogeneous. How to implement tasks across platforms and ensure the quality of migration are the key issue for sharing the OCCA platform.

Methods: The Mobile Agent technology based on a domain is introduced. User tasks are encapsulated into Mobile agent packets by domain client, which realizes the migration of user tasks from one platform to another, and makes it possible to interoperate between OCCA virtual machines. To ensure the service quality of OCCA better, a five-layer logical model of R-OCCA with high commercial availability is proposed, which defines the service content of each layer and gives the setting of key parameters. This paper introduces the architectural composition and operational mechanism of the model, which carries out a qualitative analysis of the model, and establishes an experimental prototype to verify the feasibility of the model on the virtual machine platform.

Results: Experiments show that it is feasible to implement Cloud Computing Alliance among cloud computing platforms through Mobile Agent under the existing technical conditions.

Conclusion: To better guarantee the quality of OCCA service, a five-level R-OCCA logic model with strong commercial availability is proposed. The service content of each level is defined and the key parameters are given. From the CCSP income, the rationality of the model set is explained. The feasibility of the model was analyzed. The architectural composition and operational mechanisms of the model are introduced. The performance of the model was also analyzed.

Keywords: Open cloud computing alliance, heterogeneity, mobile agent, architecture, performance analysis, agent transfer protocol.

[1]
J. Wang, Research on load balancing strategy of Cloud Computing Alliance Based on particle swarm optimization algorithm., North China University of Water Resources and Hydropower, 2018.
[2]
Z. Ying, Research on Data Resource Integration Mechanism of Mobile Cloud Computing Alliance., Harbin University of Technology, 2016.
[3]
L. Hua, Research on the Business Model of Mobile Cloud Computing Alliance., Harbin University of Technology, 2016.
[4]
" DiWang, Ah-Hwee Tan, “Mobile humanoid agent with mood awareness for elderly care”, Neur.Netw.(IJCNN) In", 2014 International Joint Conference on, 2014.
[5]
Vu. Quang-Dung, "Nguyen Viet-Ha, and N. Nakajima, "Agent based adaptive connection of mobile devices", In: Computing, Management and Telecommunications (ComManTel), 2014 International Conference on,", 2014
[6]
J. Kaur, and S. Saxena, "Securing mobile agent’s information in ad-hoc network In: Confluence The Next Generation Information Technology Summit (Confluence), 2014 ", 5th International Conference, 2014
[7]
B. Qian, and H.H. Cheng, "A bio-inspired mobile agent-based coalition formation system for multiple modular-robot systems In: Mechatronic and Embedded Systems and Applications (MESA), 2014 IEEE/ASME 10th International Conference on", 2014
[8]
M. Usman, "Agent-enabled anomaly detection in resource constrained wireless sensor networks In: A World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2014 IEEE 15th International Symposium on", 2014
[9]
Y. Jian, and Y. Dengqi, "An agent-based searchable encryption scheme in mobile computing environment In: Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on", 2014
[10]
Z. Zhang, Key Technologies for Modeling and Realizing Cloud Computing Alliance., Yunnan University, 2010.
[11]
M.G.C.A. Cimino, and F. Marcelloni, "Autonomic tracing of production processes with mobile and agent-based computing", Inf. Sci., vol. 181, no. 5, pp. 935-953, 2011.
[http://dx.doi.org/10.1016/j.ins.2010.11.015]
[12]
E. Eugene Levner, "An improved FPTAS for mobile agent routing with time constraints", J. Univers. Comput. Sci., vol. 17, no. 13, pp. 1854-1862, 2011.
[13]
T. Hasegawa, K. Cho, and A. Ohsuga, "Interoperability of mobile agents for ubiquitous applications", Electr. Eng. Jpn., vol. 161, no. 4, pp. 49-59, 2010.
[http://dx.doi.org/10.1002/eej.20388]
[14]
C.H. Liu, Y.F. Chung, T.S. Chen, and S.D. Wang, "Mobile agent application and integration in electronic anamnesis system", J. Med. Syst., vol. 36, no. 3, pp. 1009-1020, 2012.
[http://dx.doi.org/10.1007/s10916-010-9563-3] [PMID: 20703635]


Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 13
ISSUE: 6
Year: 2020
Page: [795 - 803]
Pages: 9
DOI: 10.2174/2352096512666191016120432
Price: $25

Article Metrics

PDF: 11
HTML: 3
EPUB: 1