A Distributed Challenge Detection System for Resilient Network
The network has become essential to our daily life, with the increase of dependence, challenges to the normal operation of the network bear ever more severe consequences. The challenges include malicious attacks, misconfigurations, faults, and operational overloads. Understanding the challenges is significant to build resilience mechanism. A crucial part of the resilience strategy involves real-time detection of challenges, followed by identification to initiate appropriate remediation. We observed that the state-of-art to challenges detection is insufficient. Our goal is to advocate a new autonomic, distributed challenge detection approach. In this paper, we present a resilient distributed system to identify the challenges that have severe impact on the wired and wireless mesh network (WMN). Our design shows how a challenge (malicious attack) is handled initially by lightweight network monitoring, then progressively applying more heavyweight analysis to identify. The non-malicious challenges could be simulated by our network failure module. In addition, WMN is an interesting domain to consider network resilience, the automatic detection and mitigation is a desirable property of a resilient WMN. We present the guidelines to address the challenge of channel interferences in the WMN. The feasibility of our framework is proved through the experiment. We conclude that our proof-of-concept case study has provided valuable insight into resilient network, which will be useful for further research.
Keywords: Wireless Mesh Network, Network Monitoring, Network Failure, Anomaly Detection, Resilient Network