Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of networks given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.

无线传感器网络（WSN）通常包括成千上万个资源受限的传感器，以监视其周围环境，收集数据并将其传输到远程服务器以进行进一步处理。尽管WSN被认为是高度灵活的自组织网络，但鉴于部署规模和相关的质量问题（例如资源管理，可伸缩性和可靠性），网络管理已成为这些类型网络中的一项基本挑战。拓扑管理被认为是解决这些问题的可行技术。群集是WSN中最著名的拓扑管理方法，它对节点进行分组以对其进行管理和/或以分布式方式执行各种任务，例如资源管理。尽管众所周知，群集技术可以提高能耗，通过聚类可以实现各种质量驱动的目标。在本文中，我们全面回顾了现有的WSN群集技术，其目标以及这些技术支持的网络属性。在完善了500多种聚类技术之后，我们提取了其中的215种作为最重要的技术，然后根据聚类目标以及网络属性（如移动性和异构性）对它们进行了进一步的审查，分类和分类。此外，还基于所选指标提供统计信息，从而为WSN中的群集技术设计提供了非常有用的见解。在完善了500多种聚类技术之后，我们提取了其中的215种作为最重要的技术，然后根据聚类目标以及网络属性（如移动性和异构性）对它们进行了进一步的审查，分类和分类。此外，还基于所选指标提供统计信息，从而为WSN中的群集技术设计提供了非常有用的见解。在完善了500多种聚类技术之后，我们提取了其中的215种作为最重要的技术，然后根据聚类目标以及网络属性（如移动性和异构性）对它们进行了进一步的审查，分类和分类。此外，还基于所选指标提供统计信息，从而为WSN中的群集技术设计提供了非常有用的见解。