UWSN(Underwater Wireless Sensor Networks)相较于传统的无线传感器网络采用了声信号进行数据传输,由于高传输延迟的引入,冲突类数据丢失现象凸显,网络可靠通信面临全新的挑战.为了在这样的环境中实现低消耗、高可靠网络通信这一目的,...UWSN(Underwater Wireless Sensor Networks)相较于传统的无线传感器网络采用了声信号进行数据传输,由于高传输延迟的引入,冲突类数据丢失现象凸显,网络可靠通信面临全新的挑战.为了在这样的环境中实现低消耗、高可靠网络通信这一目的,文中设计了一种最小化冲突概率路由算法MCR(Minimum Conflict probability Routing).该算法融合了网络节点的度值和节点工作负载,形成了一种全新的路由策略DBM(Degree and Buff based Metric).在该路由策略基础上,采用图论中的随机游走模型对源节点与sink节点之间的路径进行选择.MCR算法的核心思想是选择两点之间冲突概率最低的路径完成数据传输,虽然该算法不能从Mac层解决冲突类丢包问题,但是从基于NS-2的仿真实验结果来看,在UWSN环境下,MCR算法相较于传统路由算法有效地减少了路径中的冲突类丢包概率,提升了端到端链路可靠性、具有较高较稳定的网络吞吐量.展开更多
The Internet now is a large-scale platform with big data. Finding truth from a huge dataset has attracted extensive attention, which can maintain the quality of data collected by users and provide users with accurate ...The Internet now is a large-scale platform with big data. Finding truth from a huge dataset has attracted extensive attention, which can maintain the quality of data collected by users and provide users with accurate and efficient data. However, current truth finder algorithms are unsatisfying, because of their low accuracy and complication. This paper proposes a truth finder algorithm based on entity attributes (TFAEA). Based on the iterative computation of source reliability and fact accuracy, TFAEA considers the interactive degree among facts and the degree of dependence among sources, to simplify the typical truth finder algorithms. In order to improve the accuracy of them, TFAEA combines the one-way text similarity and the factual conflict to calculate the mutual support degree among facts. Furthermore, TFAEA utilizes the symmetric saturation of data sources to calculate the degree of dependence among sources. The experimental results show that TFAEA is not only more stable, but also more accurate than the typical truth finder algorithms.展开更多
文摘UWSN(Underwater Wireless Sensor Networks)相较于传统的无线传感器网络采用了声信号进行数据传输,由于高传输延迟的引入,冲突类数据丢失现象凸显,网络可靠通信面临全新的挑战.为了在这样的环境中实现低消耗、高可靠网络通信这一目的,文中设计了一种最小化冲突概率路由算法MCR(Minimum Conflict probability Routing).该算法融合了网络节点的度值和节点工作负载,形成了一种全新的路由策略DBM(Degree and Buff based Metric).在该路由策略基础上,采用图论中的随机游走模型对源节点与sink节点之间的路径进行选择.MCR算法的核心思想是选择两点之间冲突概率最低的路径完成数据传输,虽然该算法不能从Mac层解决冲突类丢包问题,但是从基于NS-2的仿真实验结果来看,在UWSN环境下,MCR算法相较于传统路由算法有效地减少了路径中的冲突类丢包概率,提升了端到端链路可靠性、具有较高较稳定的网络吞吐量.
基金supported by the National Natural Science Foundation of China(61472192)the Scientific and Technological Support Project(Society)of Jiangsu Province(BE2016776)
文摘The Internet now is a large-scale platform with big data. Finding truth from a huge dataset has attracted extensive attention, which can maintain the quality of data collected by users and provide users with accurate and efficient data. However, current truth finder algorithms are unsatisfying, because of their low accuracy and complication. This paper proposes a truth finder algorithm based on entity attributes (TFAEA). Based on the iterative computation of source reliability and fact accuracy, TFAEA considers the interactive degree among facts and the degree of dependence among sources, to simplify the typical truth finder algorithms. In order to improve the accuracy of them, TFAEA combines the one-way text similarity and the factual conflict to calculate the mutual support degree among facts. Furthermore, TFAEA utilizes the symmetric saturation of data sources to calculate the degree of dependence among sources. The experimental results show that TFAEA is not only more stable, but also more accurate than the typical truth finder algorithms.
