In wireless sensor networks (WSNs), a mobile sink accumulate the data instead of routing directly to the sink to avoid the hotspot problem. In this process, it traverses a predetermined path by visiting a set of nodes called the rendezvous point (RP), and all the non-rendezvous points can transmit their data to the closest RP. Identifying the best collection of RPs and determining the mobile sink traveling path will decrease data loss and improve network performance. However, choosing a set of RPs and the route between them is a challenging task. It is more complicated in the event-driven applications due to the uneven data rate of SNs. In this context, we propose an extended ant colony optimization (ACO)-based mobile sink path construction for event-driven WSNs. In this, the best set of the RPs and the efficient mobile sink traveling path between them is determined. In addition to this, the RPs re-selection mechanism also adopted for balancing the energy between the nodes. After that, the virtual RPs are introduced to minimize the data transmissions between the sensor nodes and RPs. This process will improve WSNs’ performance in terms of reducing data losses while increasing network lifetime. The improved performance of the extended ACO-MSPD over existing is confirmed through simulation tests.

在无线传感器网络（WSN）中，移动接收器会累积数据，而不是直接路由到接收器，以避免出现热点问题。在此过程中，它通过访问称为集合点（RP）的一组节点来遍历预定路径，并且所有非集合点都可以将其数据传输到最近的RP。确定最佳的RP集合并确定移动宿移动路径将减少数据丢失并提高网络性能。但是，选择一组RP及其之间的路由是一项艰巨的任务。由于SN的数据速率不均匀，因此在事件驱动的应用程序中更加复杂。在这种情况下，我们为事件驱动的WSN提出了一种基于扩展蚁群优化（ACO）的移动宿路径构造。在这个 确定最佳的RP集和它们之间的有效移动宿移动路径。除此之外，还采用了RP重新选择机制来平衡节点之间的能量。之后，引入虚拟RP以最大程度地减少传感器节点和RP之间的数据传输。此过程将在减少数据丢失的同时提高网络寿命的同时提高WSN的性能。仿真测试证实了扩展后的ACO-MSPD与现有产品相比的改进性能。此过程将在减少数据丢失的同时提高网络寿命的同时提高WSN的性能。仿真测试证实了扩展后的ACO-MSPD与现有产品相比的改进性能。此过程将在减少数据丢失的同时提高网络寿命的同时提高WSN的性能。仿真测试证实了扩展后的ACO-MSPD与现有产品相比的改进性能。