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Enhanced Algorithms for Fault Nodes Recovery in Wireless Sensors Network

机译:无线传感器网络中故障节点恢复的增强算法

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An integration of sensing environment with the numerous deployments of sensor nodes in Wireless Sensor Network (WSN) causes the severe security threats and hence the trust assurance mechanisms are required. For the large scale WSN, the existence of a number of intermediate nodes is responsible for the data forwarding to the sink node. Due to the battery operated sensors, the recharge and replace mechanisms suffer from the energy conservation and minimum network lifetime. The identification of fault nodes on the transmission path plays the major role in energy conservation. With the dense deployment of sensor nodes, the failures in node and link are high that disrupts the entire communication. This paper proposes the suitable alternative fault-free path prediction model to perform the communication among the nodes. Initially, the sensor nodes are deployed in the WSN environment. Once the initialization of source and destination nodes are over, the path between them is predicted through the Hamiltonian path prediction model. During the failure, scenario, this paper estimates the node and link parameters such as Received Signal Strength Indicator (RSSI), queue size, response time, and bandwidth are individually estimated and group them into the Quality Factor (QF). Based on the QF, the proposed work predicts the fault-free link to alleviate the unnecessary transmissions to the fault node and reduces the energy consumption. The comparison between the proposed Hamiltonian Path-based Hyper Cube (HPHC) network with the existing fault detection mechanisms regarding the performance measures such as Packet Delivery Ratio (PDR), fault node detection rate, throughput and end-to-end delay assures the effectiveness of HPHC in WSN communication.
机译:传感环境与无线传感器网络(WSN)中传感器节点的众多部署的集成会带来严重的安全威胁,因此需要信任保证机制。对于大规模WSN,大量中间节点的存在负责将数据转发到宿节点。由于使用电池供电的传感器,因此充电和更换机制会受到能量节省和网络寿命最短的困扰。传输路径中故障节点的识别在节能中起着重要作用。随着传感器节点的密集部署,节点和链接中的故障很高,破坏了整个通信。本文提出了合适的替代性无故障路径预测模型来执行节点之间的通信。最初,传感器节点部署在WSN环境中。一旦源节点和目标节点的初始化结束,就可以通过哈密顿路径预测模型预测它们之间的路径。在发生故障的情况下,本文估计了节点和链路参数,例如接收信号强度指示器(RSSI),队列大小,响应时间和带宽,这些参数是单独估计的,并将它们分组为质量因子(QF)。基于QF,所提出的工作预测了无故障链路,以减轻到故障节点的不必要传输并降低能耗。拟议的基于汉密尔顿路径的超立方体(HPHC)网络与现有的故障检测机制之间的比较,涉及诸如分组传输率(PDR),故障节点检测率,吞吐量和端到端延迟等性能指标,从而确保了有效性WSN通信中HPHC的概念。

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