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TinyBee: Mobile agent based data gathering system in wireless sensor networks.

机译:TinyBee:无线传感器网络中基于移动代理的数据收集系统。

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摘要

Scope and Method of Study. The thesis proposes the mobile-agent-based data-gathering system in sensor networks from a new point of view. The objectives of the thesis are: (1) Studying concepts of mobile agents and previous research related to the thesis; (2) Exploring data-gathering system under a specific situation where a server is movable in sensor networks; (3) Making the system time-efficient as well as energy-efficient enough; (4) Simulating the system with appropriate data settings; (5) Experimenting, analyzing results, and evaluating the proposed system. The execution time and the consumed energy are performance metrics of the system by comparing to the traditional server/client model. In simulation experiments, we change the number of sensor nodes, the size of mobile agents, and a kind of network protocols in order to analyze effects of such parameters on the system.;Findings and Conclusions. We designed data gathering system using a special kind of mobile agents called TinyBee to successfully collect data all over the network. TinyBee migrates from node to node after dispatched from a mobile server like a robot. We also introduced two kinds of network protocols called MMCBR and LEAR-AODV in order to let TinyBee returns to the robot energy-efficiently. The system was precisely evaluated with a simulator called NetLogo. Simulation experiments showed that our TinyBee based model is not only both time-efficient and energy-efficient, but also scalable rather than a traditional server/client based model. In addition to analyzing performance improvement between the server/client based model and the TinyBee based model, we also investigated performance difference between the TinyBee based model using MMCBR protocol and the model using LEAR-AODV protocol. Experiments showed using LEAR-AODV is a superior solution than using MMCBR in terms of distribution of energy residual on sensor nodes.
机译:研究范围和方法。本文从新的角度提出了传感器网络中基于移动代理的数据收集系统。本文的目的是:(1)研究移动代理的概念以及与该论文相关的先前研究; (2)在服务器在传感器网络中移动的特定情况下,探索数据收集系统; (3)使系统既高效又节能。 (4)用适当的数据设置模拟系统; (5)实验,分析结果并评估所提出的系统。与传统的服务器/客户端模型相比,执行时间和能耗是系统的性能指标。在仿真实验中,我们更改了传感器节点的数量,移动代理的大小以及一种网络协议,以分析此类参数对系统的影响。我们使用一种称为TinyBee的特殊移动代理设计了数据收集系统,以成功地通过网络收集数据。从机器人之类的移动服务器分派后,TinyBee从一个节点迁移到另一个节点。我们还介绍了两种网络协议,分别称为MMCBR和LEAR-AODV,以使TinyBee高效返回机器人。使用称为NetLogo的模拟器对系统进行了精确评估。仿真实验表明,我们基于TinyBee的模型不仅省时省力,而且具有可扩展性,而不是传统的基于服务器/客户端的模型。除了分析基于服务器/客户端的模型与基于TinyBee的模型之间的性能改进之外,我们还研究了使用MMCBR协议的基于TinyBee的模型与使用LEAR-AODV协议的模型之间的性能差异。实验表明,就传感器节点上的残余能量分布而言,使用LEAR-AODV是优于使用MMCBR的解决方案。

著录项

  • 作者

    Ota, Kaoru.;

  • 作者单位

    Oklahoma State University.;

  • 授予单位 Oklahoma State University.;
  • 学科 Computer Science.
  • 学位 M.S.
  • 年度 2008
  • 页码 58 p.
  • 总页数 58
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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