The authors consider distributed mobile networks carrying time-varying heterogeneous traffics. To deal effectively with the mobile and time-varying distributed environment, the deployment of traffic and network performance monitoring techniques is necessary for the identification of traffic changes, network failures, and also for the facilitation of protocol adaptations and topological modifications. Concurrently, the heterogeneous traffic environment necessitates the deployment of hybrid information transport techniques. This chapter discusses the design, analysis, and evaluation of distributed and dynamic techniques which manage the traffic and monitor the network performance effectively, while capturing the dynamics inherent in the mobile heterogeneous environments. Specifically, the design of a monitoring sub-network is sought, where the arising research tasks include: • the adoption of a core sequential algorithm which monitors both the variations in the rates of the information data flows and the dynamics of the network performance. • The identification of the specific operational and performance characteristics of the monitoring systems, when the core algorithm is implemented in a distributed environment; for a given network topology, it is important to identify the minimum size monitoring sub-network for complete “visibility” of data flows and network functions. • Dynamically changing monitoring sub-network architectures, as functions of time-varying network topologies. • The deployment of Artificial Intelligence learning techniques, in the presence of dynamically changing network and information flow environments, to appropriately adapt crucial operational parameters of the data monitoring algorithms.
G-NetMon: A GPU-accelerated Network Performance Monitoring System