Study on real time data collection and distribution method in sensor networks

传感器网络实时数据采集与分发方法研究

• 批准号: 17500043
• 负责人: SUGANO Masashi
• 金额: $ 1.92万
• 依托单位: Osaka Prefecture University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2005
• 资助国家: 日本
• 起止时间: 2005 至 2006
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-17500043/
• 关键词: sensor network; simulation; localization; cluster; energy consumption; swarm intelligence; スループット

In large-scale sensor networks, multi-hop communication between sensor nodes is necessary to cover a large monitoring region. Moreover, sensor nodes should be grouped into clusters to enhance scalability and robustness. We examine the characteristics of multi-hop communication between clusters in large-scale sensor networks and compare them with other routing methods. We also apply CSMA/CA since the information of only neighboring sensor nodes is necessary. As a result, using CSMA/CA, power consumption increases by 12% and the packet collection time becomes about four times longer in comparison to using TDMA based on location information of all sensor nodes.Furthermore, to verify the validity of our autonomous indoor localization system for sensor networks in an actual environment, we implemented it in a wireless sensor network based on the ZigBee standard. The system automatically estimates the distance between sensor nodes by measuring the RSSI (received signal strength indicator) at an appropriate number of sensor nodes. Through experiments, we clarified the validity of our data collection and position estimation techniques. The results show that the position estimation error was reduced to 1.5-2 m.Moreover, we propose a new scheme of gathering data from sensor networks with multi-sink configurations inspired by the swarm intelligence. Each sensor node determines its next action through repeated interaction and feedback from its neighbors and environments in this scheme. Advantageous clustering and routing emerge in network level from these actions. Our simulation results revealed that the proposed scheme can reliably deliver event information to the sink nodes, is robust over very-poor-quality wireless channels, and has self-recovery capability to deal with sensor-node failure and even that in sink nodes.

在大规模传感器网络中，传感器节点之间的多跳通信是覆盖大范围监测区域所必需的。此外，传感器节点应分组成簇，以提高可扩展性和鲁棒性。我们研究了大规模传感器网络中簇间多跳通信的特点，并将其与其他路由方法进行了比较。我们还应用CSMA/CA，因为只有相邻的传感器节点的信息是必要的。因此，使用CSMA/CA，功耗增加了12%，数据包收集时间变得比使用TDMA的基础上的所有传感器节点的位置信息的约4倍长。此外，为了验证我们的自主室内定位系统的传感器网络在实际环境中的有效性，我们实现了基于ZigBee标准的无线传感器网络。系统通过测量适当数量的传感器节点处的RSSI（接收信号强度指示符）来自动估计传感器节点之间的距离。通过实验，我们阐明了我们的数据收集和位置估计技术的有效性。结果表明，位置估计误差降低到1.5-2米。此外，我们提出了一种新的计划，收集数据的传感器网络与多sink配置的启发群体智能。在该方案中，每个传感器节点通过与邻居和环境的反复交互和反馈来确定其下一步行动。这些行为在网络层产生了复杂的集群和路由。我们的仿真结果表明，该方案可以可靠地提供事件信息的汇聚节点，是非常糟糕的无线信道质量的鲁棒性，并具有自我恢复能力，以处理传感器节点故障，甚至在汇聚节点。

项目成果

Performance analysis of large-scale wireless sensor network architecture with multi-cluster configuration.

多集群配置的大规模无线传感器网络架构的性能分析。

• 发表时间: 2006
• 期刊: Proceedings if IASTED International Conference on Networks and Communication Systems
• 作者: Masashi Sugano;Yuichi Kiri;Masayuki Murata
• 通讯作者: Masayuki Murata

Performance Evaluation of intercluster multi-hop communication on large-scale sensor networks.

大规模传感器网络集群间多跳通信的性能评估。

• 发表时间: 2006
• 期刊: Technical Report of IEICE Vol.106. No.42
• 作者: Yuichi Kiri;Masashi Sugano;Masayuki Murata
• 通讯作者: Masayuki Murata

Indoor Localization System using RSSI Measurement of Wireless Sensor Network based on ZigBee Standard

• 发表时间: 2006
• 作者: M. Sugano;T. Kawazoe;Y. Ohta;M. Murata

マルチシンク構成のセンサネットワークにおけるロバストな情報収集メカニズムの提案と評価

多汇传感器网络中鲁棒信息收集机制的提出和评估

• 发表时间: 2007
• 期刊: 電子情報通信学会 技術研究報告 Vol. 106 No. 578
• 作者: 木利友一;菅野正嗣;村田正幸
• 通讯作者: 村田正幸

Performance analysis of large-scale wireless sensor network architecture with multi-cluster configuration

多集群配置的大规模无线传感器网络架构性能分析

• 发表时间: 2006
• 期刊: Proceedings of IASTED International Conference on Networks and Communication Systems
• 作者: Masashi Sugano;Yuichi Kiri;Masayuki Murata
• 通讯作者: Masayuki Murata