Aiming at the serious waste of energy in the current lighting environment， a lighting control optimization method based on Progressive Sparrow Search Algorithm （P-SSA） was proposed. Firstly， to increase the diversity of the initial population， avoid premature convergence and enhance the ability to search for optimization， the Logistic chaotic initialization， the Cauchy mutation and the memory function of the historical optimal position were introduced into SSA. Then， the presence of people in the light environment， the distribution of natural light and the coupling between multiple lamps and lanterns were comprehensively considered to establish a fitness function. DIALux evo professional lighting simulation software was used to obtain the artificial illuminance transfer matrix and natural illuminance distribution. Finally， the performance of P-SSA was verified， and several optimization algorithms were used to carry out experiments about optimization of the combination of dimming coefficients. Experimental results show that compared with optimization algorithms such as Particle Swarm Optimization algorithm （PSO） and Arithmetic Optimization Algorithm （AOA）， the lighting control optimization method based on P-SSA can find the combination of optimal dimming coefficients quickly and accurately， and meet the requirement of maximum energy saving under the premise of comfort.

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.