基于二进制量子行为粒子群优化的WSN自适应设计

Design of Wireless Sensor Networks Based on Binary Quantum-behaved Particle Swarm Optimization

无线传感器网络(WSN)所处的物理环境,探测对象以及WSN本身都存在很多不确定的因素,这要求WSN能够适时地调整和优化。提出一种基于簇结构的自适应WSN,采用二进制量子行为粒子群算法实现网络拓扑控制优化与网络覆盖优化,提高了全局搜索能力。算法中采用基于并行位操作的高效率算子处理二进制串。该算法融合于WSN动态结构设计,能有效延长WSN的使用寿命。

There are many uncertain factors in physical environment, detecting targets and wireless sensor networks themselves. Wireless sensor networks application required duly adjusting and optimizing. It presents an adaptive cluster structure, and uses bi- nary quantum - behaved particle swarm optimization for network topology controlling and network coverage optimization. Efficient bi- nary series processing operators are designed based on parallel bit operation. This method prolongs network service life effectively.