Swarm Security Intelligent Dynamic Networking Algorithm Based on Multiple Constraints

Abstract

Abstract To reduce the security risks and guide management pressure of “mountain-type” scenic areas with steep and changeable topography, this paper combines the idea of swarm security intelligence and proposes a swarm security intelligent dynamic networking algorithm based on multiple constraints to ensure the swarm safety of the tour group and relieve the management pressure of tour guide through the dynamic group and the self-discovery after leaving the group. Based on multiple constraints such as signal strength, power consumption and fault probability etc, the algorithm optimizes the network topology in real-time, which can effectively reduce the high false-positive rate o f leaving the group due to node failure. Secondly, the algorithm constructs the Spf constrained fitness function and introduces the ant colony optimization algorithm to avoid the situation that the optimal routing path falls into the local optimal solution. Finally, the algorithm converts the adjacency matrix composed of routing table and node connection signals into areachable matrix to judge whether the member has left the group and reduce the false-negative rate of group loss in the case of multi-node connection. Experimental results show that the algorithm has good stability and robustness in mobile wireless adhoc networks