Performance Analysis and Deployment Techniques forWireless Sensor Networks

Recently, wireless sensor network (WSN) has become a promising technology with a wide range of applications such as supply chain monitoring and environment surveillance. It is typically composed of multiple tiny devices equipped with limited sensing, computing and wireless communication capabilities. Design of such networks presents several technique challenges while dealing with various requirements and diverse constraints. Performance analysis and deployment techniquesare required to provide insight on design parameters and system behaviors. Based on network calculus, a deterministic analysis method is presented for evaluating the worst-case delay and buffer cost of sensor networks. To this end,traffic splitting and multiplexing models are proposed and their delay and buffer bounds are derived. These models can be used in combination to characterize complex traffic flowing scenarios. Furthermore, the method integrates a variable duty cycle to allow the sensor nodes to operate at low rates thus saving power. In an attempt to balance traffic load and improve resource utilization and performance,traffic splitting mechanisms are introduced for sensor networks with general topologies. To provide reliable data delivery in sensor networks, retransmission has been one of the most popular schemes. We propose an analytical method to evaluate the maximum data transmission delay and energy consumption of two types of retransmission schemes: hop-by-hop retransmission and end-to-end retransmission.In order to validate the tightness of the bounds obtained by the analysis method, the simulation results and analytical results are compared with various input traffic loads. The results show that the analytic bounds are correct and tight. Stochastic network calculus has been developed as a useful tool for Qualityof Service (QoS) analysis of wireless networks. We propose a stochastic servicecurve model for the Rayleigh fading channel and then provide formulas to derive the probabilistic delay and backlog bounds in the cases of deterministic and stochastic arrival curves. The simulation results verify that the tightness of the bounds are good. Moreover, a detailed mechanism for bandwidth estimation of random wireless channels is developed. The bandwidth is derived from the measurement of statistical backlogs based on probe packet trains. It is expressed by statistical service curves that are allowed to violate a service guarantee with a certain probability. The theoretic foun