Multi-granularity Decomposition of Componentized Network Applications Based on Weighted Graph Clustering

Authors

  • Ziliang Wang State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  • Fanqin Zhou State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  • Lei Feng State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  • Wenjing Li State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  • Tingting Zhang China Mobile Research Institute, Beijing, 100053, China
  • Sheng Wang China Mobile Research Institute, Beijing, 100053, China
  • Ying Li China Mobile Research Institute, Beijing, 100053, China

DOI:

https://doi.org/10.13052/jwe1540-9589.21312

Keywords:

componentized network application, weighted graph clustering, density peak clustering, multi-granularity task decomposition

Abstract

With the development of mobile communication and network technology, smart network applications are experiencing explosive growth. These applications may consume different types of resources extensively, thus calling for the resource contribution from multiple nodes available in probably different network domains to meet the service quality requirements. Task decomposition is to set the functional components in an application in several groups to form subtasks, which can then be processed in different nodes. This paper focuses on the models and methods that decompose network applications composed of interdependent components into subtasks in different granularity. The proposed model characterizes factors that have important effects on the decomposition, such as dependency level, expected traffic, bandwidth, transmission delay between components, as well as node resources required by the components, and a density peak clustering (DPC) -based decomposition algorithm is proposed to achieve the multi-granularity decomposition. Simulation results validate the effect of the proposed approach on reducing the expected execution delay and balancing the computing resource demands of subtasks.

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Author Biographies

Ziliang Wang, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

Ziliang Wang received his Bachelor of Engineering degree from Beijing University of Posts and telecommunications in 2017. He is currently studying for a master’s degree in network management centre, School of computer science, Beijing University of Posts and telecommunications.

Fanqin Zhou, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

Fanqin Zhou, received his Ph.D. degree in automation from the Beijing University of Posts and Telecommunications (BUPT), China, in 2019. He is currently a Postdoctoral Fellow with the State Key Laboratory of Networking and Switching Technology in BUPT. His current research interests include network slicing and resource management of mobile edge networks.

Lei Feng, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

Lei Feng, received his B.Eng. and Ph.D. degrees in Communication and Information Systems from Beijing University of Posts and Telecommunications (BUPT) in 2009 and 2015. He is an Associate Professor at present in State Key Laboratory of Networking and Switching Technology, BUPT. His research interests are resources management in wireless network and smart grid.

Wenjing Li, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

Wenjing Li, is currently a professor at BUPT and serves as a director in the Key Laboratory of Network Management Research Centre. Meanwhile, she is the leader of TC7/WG1 in the China Communications Standards Association (CCSA). Her research interests are intelligent network management, knowledge-driven management and control of B5G/6G networks. Prof. Li is hosting the China first 6G research project, and published more than 120 papers in prestigious journals (e.g., IEEE Transactions, IEEE IoT-J) and conferences (e.g. INFOCOM, ICC, PODC).

Tingting Zhang, China Mobile Research Institute, Beijing, 100053, China

Tingting Zhang, received the Master of computer applications degree from University of Chinese Academy of Sciences in 2011. She is currently working in China Mobile Research Institution as a Technical Director. Her current research interests include network virtualization, cloud computing, edge computing, ubiquitous computing and etc.

Sheng Wang, China Mobile Research Institute, Beijing, 100053, China

Sheng Wang, received the Master of Engineering degree from Beijing institute of technology in 2010. He is currently working in China Mobile Research Institution as a Technical Director. His current research interests include NFV/SDN, ubiquitous computing, heterogeneous computing and cloud-network convergence, etc.

Ying Li, China Mobile Research Institute, Beijing, 100053, China

Ying Li, received the Master of Engineering degree from Beijing University of Posts and Telecommunications in 2017. She is currently working in China Mobile Research Institution as a project manager.

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Published

2022-03-22

How to Cite

Wang, Z. ., Zhou, F. ., Feng, . L. ., Li, W. ., Zhang, T. ., Wang, S. ., & Li, Y. . (2022). Multi-granularity Decomposition of Componentized Network Applications Based on Weighted Graph Clustering. Journal of Web Engineering, 21(03), 815–844. https://doi.org/10.13052/jwe1540-9589.21312

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