Lightweight Boolean Network Tomography Based on Partition of Managed Networks

Boolean network tomography is a promising technique to achieve fault management in networks where the existing IP-based troubleshooting mechanism cannot be used. Aiming to apply Boolean network tomography to fault management, a variety of heuristic methods for configuring monitoring trails and paths have been proposed to localize link failures in managed networks. However, these existing heuristic methods must be executed in a centralized server that administers the entire managed network and the methods present scalability problems when applied to large-scale managed networks. Thus, this paper proposes a novel scheme for achieving lightweight Boolean network tomography in a decentralized manner. The proposed scheme partitions the managed network into multiple management areas and localizes link failures independently within each area. This paper also proposes a heuristic network partition method with the aim of efficiently implementing the proposed scheme. The effectiveness of the proposed scheme is verified using typical fault management scenarios where all single-link failures and all dual-link failures are localized by the least number of monitoring paths on predetermined routes. Simulation results show that the proposed scheme can greatly reduce the computational load on the fault management server when Boolean network tomography is deployed in large-scale managed networks. Furthermore, the degradation of optimality in the proposed scheme can be mitigated in comparison with a centralized scheme that utilizes heuristics to reduce the computational load on the centralized server.