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Stable Sensor Network (SSN): A Dynamic Clustering Technique for Maximizing Stability in Wireless Sensor Networks

机译:稳定传感器网络(SSN):一种动态聚类技术,用于最大化无线传感器网络的稳定性

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Stability is one of the major concerns in advancement of Wireless Sensor Networks (WSN). A number of applications of WSN require guaranteed sensing, coverage and connectivity throughout its operational period. Death of the first node might cause instability in the network. Therefore, all of the sensor nodes in the network must be alive to achieve the goal during that period. One of the major obstacles to ensure these phenomena is unbalanced energy consumption rate. Different techniques have already been proposed to improve energy consumption rate such as clustering, efficient routing, and data aggregation. However, most of them do not consider the balanced energy consumption rate which is required to improve network stability. In this paper, we present a novel technique, Stable Sensor Network (SSN) to achieve balanced energy consumption rate using dynamic clustering to guarantee stability in WSN. Our technique is based on LEACH (Low-Energy Adaptive Clustering Hierarchy), which is one of the most widely deployed simple and effective clustering solutions for WSN. We present three heuristics to increase the time before the death of first sensor node in the network. We devise the algorithm of SSN based on those heuristics and also formulate its complete mathematical model. We verify the efficiency of SSN and correctness of the mathematical model by simulation results. Our simulation results show that SSN significantly improves network stability period compared to LEACH and its best variant.
机译:稳定性是无线传感器网络(WSN)发展中的主要问题之一。 WSN的许多应用都需要在其整个运营期间内保证传感,覆盖和连接。第一个节点的死亡可能会导致网络不稳定。因此,在此期间,网络中的所有传感器节点都必须处于活动状态才能实现该目标。确保这些现象的主要障碍之一是能耗率的不平衡。已经提出了各种技术来提高能耗率,例如集群,有效路由和数据聚合。但是,它们中的大多数都没有考虑提高网络稳定性所需的平衡能耗率。在本文中,我们提出了一种新技术,即稳定传感器网络(SSN),它使用动态聚类来确保WSN的稳定性,从而实现了平衡的能耗率。我们的技术基于LEACH(低能量自适应集群层次结构),LEACH是针对WSN部署最广泛的简单有效的集群解决方案之一。我们提出三种启发式方法,以增加网络中第一个传感器节点死亡之前的时间。基于这些启发式算法,设计了SSN算法,并建立了完整的数学模型。我们通过仿真结果验证了SSN的效率和数学模型的正确性。我们的仿真结果表明,与LEACH及其最佳变体相比,SSN显着改善了网络稳定期。

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