Concerning the coverage overlapping areas and blind spots caused by random deployment of nodes in three-dimensional directional heterogeneous network, a Particle Swarm Optimization (PSO) based coverage optimization algorithm for three-dimensional directional heterogeneous network, namely PSOTDH, was proposed. Through involving the concepts of three-dimensional overlapping centroid, three-dimensional effective centroid and three-dimensional boundary centroid, three-dimensional overlapping area, and three-dimensional boundary nodes were optimized in a new three-dimensional directed perception model by using PSO. The sensing directions of the nodes were changed by PSOTDH, which made the distribution of three-dimensional overlapping centroids, three-dimensional effective centroids and three-dimensional boundary centroids more uniform, and achieved the purpose of improving coverage. Simulation results show that the proposed algorithm can improve coverage rate by about 27.82% after 25 iterations, which means the proposed algorithm can improve the coverage rate quickly and effectively.

The routing scheme is one of the key factors which influence the lifetime of Wireless Sensor Network (WSN). The network can be paralyzed easily as a result of large energy consumption of key nodes by heavy communication. To solve the problem of energy consumption of key nodes in WSNs, a new ant colony routing algorithm on Dynamic Adjustment of Forward Angle based on Residual Energy (DAFARE) was proposed. Firstly, the nodes chose the next-hop node according to residual energy and distance in the range of initial forward angle; secondly, the forward angle was adjusted dynamically in the view of residual energy of nodes within the scope of forward angle; finally, early death of key nodes was avoided successfully. The simulation suggested that the effective life could be improved approximately 50% by DAFARE, compared with ant colony optimization algorithm based on Function of Multi-object Evaluation and Positive-Negative Feedback (FMEPNF). The experimental results show that, the network energy consumption of DAFARE can be balanced effectively, the lifetime is prolonged, and the coverage of WSN is guaranteed.

According to the IEEE 802.15.4 slotted Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) algorithm, a network analysis model using analysis method of two-dimensional Markov chain was proposed. Not only the sleep mode of IEEE 802.15.4 agreement but also the condition where the backoff window reached the maximum value before the Number of Backoff (NB) were especially considered in the model. On this basis, combined with M/G/1/K queuing theory, the throughput expression was derived, and the packet arrival rate effect on the throughput was analyzed under unsaturated network. Using the simulation platform Network Simulator Version2 (NS2), the experimental results show that the theoretical analysis fits well with the simulation result, and the network throughput is described accurately. Then the effectiveness of the analytical model is validated.

Concerning the impact on network performance of the mobile nodes and the constantly changing data transmission rate, the authors proposed a new backoff scheme for IEEE802.15.4, which used Probability Judgment based on Network Load and Exponentially Weighted Moving Average (PJNL_EWMA) method. According to a realtime monitoring of current network status by probability judgment of network load, this method dynamically adjusted backoff exponent by EWMA when Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) began. Compared with the IEEE802.15.4 standard protocol and MBS (Memorized Backoff Scheme)+EWMA algorithm, the simulation experiments on NS2 platform show that the PJNL_EWMA algorithm not only improves the throughput of the network, but also reduces the packet loss rate and the collision ratio, significantly improving the network performance.

To solve the detection problem of selfish behavior in IEEE802.15.4 Wireless Sensor Network (WSN), an improved Sliding Window Non-parameter Cumulation Sum (SWN-CUSUM) algorithm based on statistics was proposed to decrease the detection delay. By tracing the delay characteristic sequence between successful transmissions, the algorithm could distinguish if there was a selfish behavior in the WSNs. The NS2 simulation tool was conducted to validate the feasibility of the proposed algorithm. The experimental results show that the improved algorithm not only weakens the impact of the threshold on the performance of the algorithm, but also reduces the size of sliding window used to detect selfish behavior, and the improved algorithm makes improvement in the calculation and the detection delay than the primitive SWN-CUSUM algorithm, so the improved algorithm can detect effectively and rapidly the selfish behavior of nodes in IEEE802.15.4 WSNs.