1 research outputs found
Network Performance Estimator with Applications to Route Selection for IoT Multimedia Applications
Estimating the performance of multimedia traffic is important in numerous
contexts, including routing and forwarding, QoS provisioning, and adaptive
video streaming. This paper proposes a network performance estimator which aims
at providing, in quasi real-time, network performance estimates for IoT
multimedia traffic in IEEE 802.11 multihop wireless networks. To our knowledge,
the proposed multimedia-aware performance estimator, or MAPE, is the first
deterministic simulation-based estimator that provides real-time per-flow
throughput, packet loss and delay estimates while considering inter-flow
interference and multi-rate flows, typical of multimedia traffic. Our
experimental results indicate that MAPE is able to provide network performance
estimates that can be used by IoT multimedia services, notably to inform
real-time route selection in IoT video transmission, at a fraction of the
execution time when compared to stochastic network simulators. When compared to
existing deterministic simulators, MAPE yields higher accuracy at comparable
execution times due to its ability to consider multi-rate flows.Comment: 16 pages, 11 figures, 2 tables and 1 algorith