A Design for Application of Mobile Agent Technology to MicroService Architecture
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33093
A Design for Application of Mobile Agent Technology to MicroService Architecture

Authors: Masayuki Higashino, Toshiya Kawato, Takao Kawamura

Abstract:

A monolithic service is based on the N-tier architecture in many cases. In order to divide a monolithic service into microservices, it is necessary to redefine a model as a new microservice by extracting and merging existing models across layers. Refactoring a monolithic service into microservices requires advanced technical capabilities, and it is a difficult way. This paper proposes a design and concept to ease the migration of a monolithic service to microservices using the mobile agent technology. Our proposed approach, mobile agents-based design and concept, enables to ease dividing and merging services.

Keywords: Mobile agent, microservice, web service, distributed system.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1315705

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1080

References:


[1] I. Nadareishvili, R. Mitra, M. McLarty, and M. Amundsen, Microservice Architecture: Aligning Principles, Practices, and Culture. O’Reilly Media, Inc., 2016.
[2] J. Lewis and M. Fowler. (2014) Microservices: a definition of this new architectural term. (Online). Available: http://martinfowler.com/articles/ microservices.html
[3] S. Edlich. (2017) Nosql databases. (Online). Available: http:// nosql-database.org/
[4] E. Evans, Domain-Driven Design: Tackling Complexity in the Heart of Software. Addison-Wesley Professional, 2003.
[5] Mobile Agent System Interoperability Facilities Specification, Object Management Group, Inc., 1997.
[6] FIPA Agent Management Specification (SC00023K), Foundation for Intelligent Physical Agents, 2004.
[7] A. Fuggetta, G. P. Picco, and G. Vigna, “Understanding code mobility,” IEEE Transactions on Software Engineering, vol. 24, pp. 342–361, 1998.
[8] L. Lamport, “The part-time parliament,” ACM Transactions on Computer Systems, vol. 16, no. 2, pp. 133–169, 1998.
[9] A. Paschke, “Provalets: Component-based mobile agents as microservices for rule-based data access, processing and analytics,” Business & Information Systems Engineering, vol. 58, no. 5, pp. 329–340, 2016.
[10] I. M. D. Pratistha and A. Zaslavsky, “Fluid: Supporting a transportable and adaptive web service,” in Proceedings of the 2004 ACM Symposium on Applied Computing, 2004, pp. 1600–1606.
[11] D. Pratistha, A. Zaslavsky, S. Cuce, and M. Dick, “Performance based cost models for improving web service efficiency through dynamic relocation,” in Proceedings of the 6th International Conference on E-Commerce and Web Technologies, 2005, pp. 248–257.
[12] P. Wang, Z. Ding, C. Jiang, M. Zhou, and Y. Zheng, “Automatic web service composition based on uncertainty execution effects,” IEEE Transactions on Services Computing, vol. 9, no. 4, pp. 551–565, 2016.
[13] A. Immonen and D. Pakkala, “A survey of methods and approaches for reliable dynamic service compositions,” Service Oriented Computing and Applications, vol. 8, no. 2, pp. 129–158, 2014.
[14] G. Toffetti, S. Brunner, M. Bl¨ochlinger, F. Dudouet, and A. Edmonds, “An architecture for self-managing microservices,” in Proceedings of the 1st International Workshop on Automated Incident Management in Cloud, 2015, pp. 19–24.
[15] G. Karagiannis, A. Jamakovic, A. Edmonds, C. Parada, T. Metsch, D. Pichon, M. Corici, S. Ruffino, A. Gomes, P. S. Crosta, and T. M. Bohnert, “Mobile cloud networking: Virtualisation of cellular networks,” in Proceedings of the 21st International Conference on Telecommunications, 2014, pp. 410–415.
[16] D. Ardagna, G. Casale, M. Ciavotta, J. F. P´erez, and W. Wang, “Quality-of-service in cloud computing: modeling techniques and their applications,” Journal of Internet Services and Applications, vol. 5, no. 1, pp. 1–17, 2014.
[17] B. Wei, C. Lin, and X. Kong, “Dependability modeling and analysis for the virtual data center of cloud computing,” in 2011 IEEE International Conference on High Performance Computing and Communications, 2011, pp. 784–789.
[18] M. Melo, P. Maciel, J. Araujo, R. Matos, and C. Arajo, “Availability study on cloud computing environments: Live migration as a rejuvenation mechanism,” in Proceedings of the 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2013, pp. 1–6.
[19] A. V. Kish, “Efficient partitioning and allocation of data for workflow compositions,” Ph.D. dissertation, University of South Carolina, 2016.
[20] Microsoft Corporation. (2017) Azure cosmos db. (Online). Available: https://azure.microsoft.com/en-us/services/cosmos-db/