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.