2021/12/17 by Ashley Barnes, Barnes, Ashley, Matthew Hole +1
Business, Management and Accounting · Computer Science · #Advanced Queuing Theory Analysis #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #Network Traffic and Congestion Control #Networking and Internet Architecture (cs.NI) #cs.NI
paper · pdf · doi:10.48550/arxiv.2112.09330
Submitted to IEEE Transaction on Networks and Service Management on the 02/12/2021
arxiv created 2021/12/17 · openalex publication_date 2021/12/17 · arxiv updated 2021/12/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Network tomography has been used as an approach to the Node Failure Localisation problem, whereby misbehaving subsets of nodes in a network are to be determined. Typically approaches in the literature assume a statically routed network, permitting linear algebraic arguments. In this work, a load balancing, dynamically routed network is studied, necessitating a stochastic representation of network dynamics. A network model was developed, permitting a novel application of Markov Chain Monte Carlo (MCMC) inference to the Node Failure Localisation (NFL) problem, and the assessment of monitor placement choices. Two nuanced monitor placement algorithms, including one designed for the NFL problem by Ma et al. 2014 were tested, with the published algorithm performing significantly better.