Security Resource Scheduling Algorithm for Intelligent UAV Communication Network Based on Optimized Subgraph Isomorphism and Link Partition

Author:

Han Yanyan12,Yu Jiangping1,Zuo Peiliang1ORCID,Wei Zhanzhen1,Jin Xin1,Dou Kaili1,Guo Chao12ORCID,Xu Haitao3ORCID

Affiliation:

1. Beijing Institute of Electronic Science and Technology, Beijing 100071, China

2. State Key Laboratory of Integrated Service Network Theory and Key Technology, Xi’an 710126, China

3. School of Computer & Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China

Abstract

The resource scheduling problem of UAV communication networks has always been a hot research issue in the current environment. However, most of the current research focuses on meeting the user’s time cost requirements and rarely considers the user’s security requirements in the scheduling process. To solve the problems of low efficiency, more resource fragments, low network reliability, and unbalanced load, this paper improves the virtual network mapping model into a three-layer structure consisting of a security service request layer, virtual network provider layer, and security resource layer, so that it can be applied to the special scenario of security resource scheduling in an unmanned aerial communication network. An intelligent UAV communication network security resource scheduling algorithm based on optimized subgraph isomorphism and link segmentation is proposed. Intelligent UAVs can predict all possible access nodes and intelligently provide network services. The algorithm first improves and enriches the node constraint conditions and evaluation indicators, integrates the node resource attributes and topology attributes, optimizes the sorting process, then calculates the mapping domain in advance, considers the regional comprehensive resource capacity to balance the load, and finally combines the subgraph isomorphism and link segmentation technology to carry out a one-stage mapping scheduling to achieve the security service request in the network and the efficient allocation of network resources required to provide security services. The simulation results of the OMNeT++ show that the proposed algorithm improves the mapping success rate and the long-term average cost-benefit ratio of the UAVs.

Funder

National Natural Science Foundation of China

Open Fund Project of the State Key Laboratory of Integrated Business Network Theory and Key Technologies

Fundamental Research Funds for the Central Universities

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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