Optimality of a Network Monitoring Agent and Validation in a Real Probe

Abstract

The evolution of commodity hardware makes it possible to use this type of equipment to implement traffic monitoring systems. A preliminary empirical evaluation of a network traffic probe based on Linux indicates that the system performance has significant losses as the network rate increases. To assess this issue, we consider a model with two tandem queues and a moving server. In this system, we formulate a three-dimensional Markov Decision Process in continuous time. The goal of the proposed model is to determine the position of the server in each time slot so as to optimize the system performance which is measured in terms of throughput. We first formulate an equivalent discrete-time Markov Decision Process and we propose a numerical method to characterize the solution of our problem in a general setting. The solution we obtain in this problem has been tested for a wide range of scenarios and, in all the instances, we observe that the optimality is close to a threshold type policy. We also consider a real probe and we validate the good performance of threshold policies in real applications.

Smart Preventive Maintenance of Hybrid Networks and IoT Systems Using Software Sensing and Future State Prediction

“…Besides the industrial process, employment of intelligent agents to verify on a continuous basis the load of different components in a communication network has also been implemented. The goal is to determine the best operational status of a server in each time slot, based on Markov chain models, as well as to optimize the system's performance, which is measured in terms of throughput [24]. However, modern communication networks now rely on optical fiber, which is immune to e.m. interferences, but the optical fiber is also part of the reliability chain, so it also needs monitoring in terms of its operational status.…”

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