Optimal performance and improved lifetime are the most desirable design benchmarks for WSNs and the mechanism for data gathering is a major constituent influencing these standards. Several researchers have provided significant evidence on the advantage of mobile sink (MS) in performing effective gathering of relevant data. However, determining the trajectory for MS is an NP-hard-problem. Especially in delay-inevitable applications, it is challenging to select the best-stops or rendezvous points (RPs) for MS and also to design an efficient route for MS to gather data. To provide a suitable solution to these challenges, we propose in this paper, a game theory and enhanced ant colony based MS route selection and data gathering (GTAC-DG) technique. This is a distributed method of data gathering using MS, combining the optimal decision making skill of game theory in selecting the best RPs and computational swarm intelligence of enhanced ant colony optimization in choosing the best path for MS. GTAC-DG helps to reduce data transfer and management, energy consumption and delay in data delivery. The MS moves in a reliable and intelligent trajectory, extending the lifetime and conserving the energy of WSN. The simulation results prove the effectiveness of GTAC-DG in terms of metrics such as energy and network lifetime.

最优的性能和更长的使用寿命是WSN最理想的设计基准，并且数据收集机制是影响这些标准的主要因素。一些研究人员提供了有关移动接收器（MS）在有效收集相关数据方面的优势的重要证据。但是，确定MS的轨迹是一个NP难题。特别是在不可避免的延迟应用中，选择MS的最佳站点或集合点（RP）以及设计MS收集数据的有效路径都具有挑战性。为了提供应对这些挑战的合适解决方案，我们在本文中提出了一种博弈论和基于蚁群的MS路线选择和数据收集（GTAC-DG）技术。这是一种使用MS进行数据收集的分布式方法，结合选择最佳RP的博弈论的最佳决策技巧和选择MS最佳路径的增强蚁群优化的计算群智能。GTAC-DG有助于减少数据传输和管理，能耗以及数据传输的延迟。MS沿着可靠且智能的轨迹运动，从而延长了使用寿命并节省了WSN的能量。仿真结果证明了GTAC-DG在能量和网络寿命等指标方面的有效性。延长使用寿命并节省WSN的能量。仿真结果证明了GTAC-DG在能量和网络寿命等指标方面的有效性。延长使用寿命并节省WSN的能量。仿真结果证明了GTAC-DG在能量和网络寿命等指标方面的有效性。