论文标题
无线传感器网络优化的生物启发算法
Bio-inspired Algorithms in the Optimisation of Wireless Sensor Networks
论文作者
论文摘要
WSN是工业和个人用途领域中不断增长的技术。 WSN的服务质量（QoS）与WSN节点和网络设计的架构有关。在这项工作中，分析了节点和网络的组成。 WSN的成功与设备的寿命和覆盖范围的最大化有关，与最小化的能源消耗和节点数量相关，可以保证良好的网络连接和高传输。提出和审查了最常见的WSN问题。最合适的优化技术是多目标（MOO），这在这项工作中是由复杂的多目标功能所用的，其中包括几个WSN问题。这篇综述的第二部分重点是WSN优化中的生物启发算法：遗传算法（GA），颗粒群群优化（PSO）和蚂蚁菌落优化（ACO）。其他不常见的方法也存在，并且与WSN问题有关。
WSN are a growing technology in industrial and personal use fields. The Quality of Service (QoS) of WSN is associated to the architecture of WSN nodes and network design. In this work, the composition of the nodes and network is analysed. The success of WSN is related to the maximisation of the lifetime and coverage of the device, allied to the minimisation of energy consumption and number of nodes, guaranteeing a good network connectivity and high transmission. The most common WSN issues are presented and reviewed. The most suitable optimisation technique is Multi-objective (MOO) which is exemplified in this work from complex multi-objective functions which include several WSN problems. The second part of this review focus on bio-inspired algorithms in WSN optimisation: Genetic Algorithms (GA), Particles Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). Other less common methods are also present and related to WSN issues.
