Cross-layer Design For Wireless Ad Hoc Sensor Networks

Cross-layer design is an efficient approach to enhance energy efficiency and Quality of Service (QoS) in wireless ad hoc sensor networks. This dissertation will focus on the cross-layer issues and approaches. It will also discuss the latency-aware and energy efficiency tadeoffs and the packets transmission in the rear part of the dissertation.

Firstly, we will analyze the cross-layer design for wireless sensor networks based on the virtual MIMO techniques. We will coordinate the physical layer, the MAC layer and the network layer for cross-layer evaluation. Performance analysis and simulation results show that throughput and packet loss ratio will have different performances compared with only considering the MIMO scheme in the physical layer as the increase of the number of transmitters.

Secondly, we will discuss the bottom-up optimization for cross-layer design. We used the fuzzy logic system (FLS) to coordinate the physical layer, the data-link layer and the application layer for cross-layer design. Simulation results show that the cross-layer design can reduce the average delay, increase the throughput and extend the network lifetime. The network performance parameters could also keep stability after the cross-layer optimization.

Thirdly, we extended the FLS application in cross-layer design from Type-1 to Type-2. We demonstrated that type-2 fuzzy membership function (MF), i.e., the Gaussian MFs with uncertain variance is most appropriate to model BER and MAC layer service time. We used the forecasted transmission delay to adjust the transmission power, and it showed that the interval type-2 FLS performed much better than a type-1 FLS, and FLSs performed better than back-prop NN in terms of energy consumption, average delay and throughput. Also, we obtained the performance bound based on the actual transmission delay.

Finally, we applied a image as the real service in WSNs. We considered cross-layer design for image transmission in WSNs. We combined the application layer, the MAC layer and the physical layer together. According to analysis and simulation, there were tradeoffs between QoS and energy consumption for both high priority service and low priority service. Application level QoS was applied to evaluate the cross-layer design for WSNs.

Two other works were discussed in this dissertation. One is the latency-aware and energy efficiency tradeoffs for wireless sensor networks. Latency and energy efficiency are two important parameters to evaluate the WSNs. The FLS is applied to the nodes selection. In contrast with the cases that only consider one descriptor, the FLS application can manage the delay/energy tradeoffs to meet the network performance requirements. Another work discussed is "Packets Transmission in wireless sensor networks: interference, energy and delay-aware approach". In the WSN, the interference will affect the packets transmission. We proposed FLS in the optimization of SIR threshold selection. Average delay and distance of a node to the source node are selected as antecedents for the FLS. The output of FLS provided adjusting factors for the SIR threshold. Simulation results showed the fuzzy optimization could achieve a better network efficiency, reduce the average delay and extend the network lifetime.