Detecting job interference in large distributed multi-agent systems — A formal approach
Wenjie Lin, Michael A. McGrath, Ingy Ramzy, Ten‐Hwang Lai, David Lee · Integrated Network Management · 2013
This work is on formal modeling, analysis and detection of job interference in large distributed multi-agent systems. Such an analysis usually requires an examination of all the global system states-often impossible due to the well-known state space explosion. We obtain a sufficient condition so that job interference can be detected by observations of individual system component without the knowledge of global system states. Given that the job interference can be detected locally, we propose a guided random walk algorithm for detecting interference. We apply it to Kansei, a large and distributed wireless sensor network system with multi-agents. Ten job interference traces are identified; they have not been detected before by manual analysis and system operations. We further diagnose the detected interference for a correction of system design.