Dimensioning wireless sensor networks requires formal methods to guarantee network performance and cost in any conditions. Based on network calculus, this paper presents a deterministic analysis method for evaluating the worst-case performance and buffer cost of sensor networks. To this end, we introduce three general traffic flow operators and derive their delay and buffer bounds. These operators are general because they can be used in combination to model any complex traffic flowing scenarios in sensor networks. Furthermore, our method integrates variable duty cycle to allow the sensor nodes to operate at lower rates thus saving power. Moreover, it incorporates traffic splitting mechanisms in order to balance network workload and nodes' buffers. To show how our method applies to real applications, we conduct a case study on a fresh food tracking application, which monitors the food freshness in realtime. The experimental results demonstrate that our method can be either used to perform network planning before deployment, or to conduct network reconfiguration after deployment.
Abstract-Deterministic network calculus (DNC) is not suitable for deriving performance guarantees for wireless networks due to their inherently random behaviors. In this paper, we develop a method for Quality of Service (QoS) analysis of wireless channels subject to Rayleigh fading based on stochastic network calculus. We provide closed-form stochastic service curve for the Rayleigh fading channel. With this service curve, we derive stochastic delay and backlog bounds. Simulation results verify that the bounds are reasonably tight. Moreover, through numerical experiments, we show the method is not only capable of deriving stochastic performance bounds, but also can provide guidelines for designing transmission strategies in wireless networks.
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