FIMPA: A Fixed Identity Mapping Prediction Algorithm in Edge Computing Environment

• Main Authors: Shuo Zhang, Yaping Liu, Shudong Li, Zhiyuan Tan, Xiaomeng Zhao, Junjie Zhou
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Edge computing; LISP; mapping resolution; prediction; recommendation
• Online Access: https://ieeexplore.ieee.org/document/8957574/

Edge computing is a research hotspot that extends cloud computing to the edge of the network. Due to the recent developments in computation, storage and network technology for end devices, edge networks have become more powerful, making it possible to integrate locator/identity separation protocol (LISP) into these networks. Accordingly, in this paper, we introduce LISP into edge routers at the edge network, focusing primarily on the delay problem of mapping resolution and cache updating in LISP with the help of edge computing. To solve this delay problem, we first analyze the communication process of the locator/identity separation network and consider using the prediction method to underpin this research. In order to achieve a good prediction result, we propose and implement a Fixed Identity Mapping Prediction Algorithm (FIMPA) based on collaborative filtering, and further verify the effectiveness of the proposed algorithm through experiments on real-world data.