iDiSC: A New Approach to IoT-Data-Intensive Service Components Deployment in Edge-Cloud-Hybrid System

IEEE Access

Yucong Duan¹  Shih-Chia Huang²  Zhihui Lu³  Songtao Tang³  Jie Wu³  Xiaowei Chen³  Qifeng Tang⁴ 

[1] College of Information Science and Technology, Hainan University, Haikou, China;Department of Electronic Engineering, National Taipei University of Technology, Taipei, Taiwan;School of Computer Science, Fudan University, Shanghai, China;Shanghai Data Exchange Corporation, Shanghai, China;

关键词: Service deployment;    edge computing;    cloud computing;    Internet of Things (IoT);    data-intensive service;    big data;   

DOI  :  10.1109/ACCESS.2019.2915020

来源: DOAJ

【 摘 要 】

With the rapid development of big data technology and the Internet, the requirements of human activities for data are getting higher and higher, and the increasing data volume has a high demand for data processing. The paradigm of the Internet of Things (IoT) has become a key component for edge-cloud-hybrid systems. In the edge environment, multiple IoT-data-intensive services will form a service combination. Due to the data transmission between different service components, there is a huge transmission delay in the process of IoT data transmission, which will affect the performance of the entire system. Therefore, by regarding the reduction of transmission delay as our optimization goal, we put forward iDiSC: a new heuristic approach for IoT-data-intensive service component deployment in the edge-cloud-hybrid system. We also design the iDiSC model, then we optimize the model to select the optimal deployment scenario with the minimum guaranteed latency. Through a series of experiments, compared to the genetic algorithm and the simulated annealing algorithm, the experimental results show that the iDiSC algorithm has higher efficiency and performance for the problem of data-intensive service component deployment problem in the edge-cloud-hybrid environment.

【 授权许可】

Unknown