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.

翻译：无线传感器网络（WSN）在工业和个人应用领域正成为一项日益增长的技术。WSN的服务质量（QoS）与WSN节点的架构及网络设计相关联。本文对节点及网络的构成进行了分析。WSN的成功取决于最大化设备寿命和覆盖率，同时最小化能耗和节点数量，以确保良好的网络连通性和高传输性能。本文介绍并综述了最常见的WSN问题。最合适的优化技术是多目标优化（MOO），本文通过包含多个WSN问题的复杂多目标函数对其进行了例证。本综述的第二部分聚焦于WSN优化中的生物启发算法：遗传算法（GA）、粒子群优化（PSO）和蚁群优化（ACO）。其他较少见的方法也被提及，并与WSN问题相关联。