TRAffic Modelling for Sensor Network Optimisation and Development (TRAMSNOD)

用于传感器网络优化和开发的流量建模 (TRAMSNOD)

• 批准号: EP/D053943/1
• 负责人: David Hunter
• 金额: $ 23.16万
• 依托单位: University of Essex
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FD053943%2F1
• 关键词: TRAffic; Modelling; Sensor; Network; Optimisation

Wireless sensor networks consist of hundreds or even thousands of tiny sensor nodes, which communicate with each other via radio, and gather information about, for example, temperature, pressure, or humidity. This proposal aims to develop useful models of the data traffic in such networks, describing in a statistical manner how information travels through the network of nodes. These models will be based in some cases, upon access to traffic measurements from real test-beds and network deployments and, in others, upon calculations from first principles. Besides using results from the extensive literature of simulation studies, this project will leverage data from projects that are already in progress, namely the DTI-funded project SECOAS, and the EPSRC-funded projects PROSEN and MC-DIAS. All three academic partners in the project are already working on these projects. Based upon these traffic models, we will assess, optimise and improve specific existing protocols, to make them suitable for our selected applications. Wherever possible, our findings will be validated in field trials.Protocols for wireless sensor networks are already well under investigation; however modelling of the traffic they generate is an important and virtually untouched topic, which will facilitate a much more informed approach to protocol design, modelling, modification and deployment. For example, models for wireless sensor network traffic will differ fundamentally from those for Internet traffic. Some of our new traffic models may be amenable to analytical solutions, if suitable assumptions are made.There will be two distinct sources of information for these traffic models:1. We will gather traces of wireless sensor traffic from existing field trials and test-beds. These will be made available to us from other projects that the project partners are involved in.2. We will work from first principles, by producing a statistical description of how much data a sensor node generates in a given application, which will be referred to as traffic source statistics throughout. By making assumptions about, for example, network layout and aggregation strategy, we will be able to produce models of traffic behaviour, which can then be compared with the measurements described above.The models we produce will lead to the development of new ways of emulating sensor network traffic. For example, using our traffic models, a sensor node could be programmed to mimic traffic from a large group of nodes. In this way, large sensor networks could be emulated using only a modest number of nodes, many of which are emulating part of a much larger network. It will hence be possible to obtain useful performance information more quickly than otherwise, using less equipment. This concept will be investigated and developed as part of our work. Moreover, there is the potential to make the emulation software we develop as part of this activity available to other groups that are researching this topic.We will also integrate the software development from earlier in the project, and deploy it in real-world trials. The proposers' involvement with SECOAS, PROSEN and MC-DIAS represents access to experimental scenarios that will enable studies of the protocol performance and analysis of results in the applications areas of the environment, power, water and telecommunications (see letter of support form British Telecommunications). Relationships will be established with these programmes and trials which will allow the integration of new protocol strategies with their extended programmes of activities e.g. wind farm test site at TUV NEL Ltd. The key aim will be to demonstrate the benefits of understanding the application and the resultant traffic profiles and the appropriate analysis of the protocol that supports that application.

无线传感器网络由数百甚至数千个微小的传感器节点组成，这些节点通过无线电相互通信，并收集温度、压力或湿度等信息。本提案旨在开发此类网络中有用的数据流量模型，以统计方式描述信息如何在节点网络中传播。在某些情况下，这些模型将基于对实际测试平台和网络部署的流量测量的访问，而在其他情况下，则基于第一原理的计算。除了使用大量模拟研究文献的结果外，该项目还将利用已经进行的项目的数据，即dti资助的项目SECOAS，以及epsrc资助的项目PROSEN和MC-DIAS。该项目的所有三个学术合作伙伴都已经在从事这些项目。根据这些流量模型，我们会评估、优化和改进特定的现有协议，使它们适合我们选定的应用。只要有可能，我们的发现将在现场试验中得到验证。无线传感器网络的协议已经在研究中；然而，对它们产生的流量进行建模是一个重要且几乎未触及的主题，它将促进对协议设计、建模、修改和部署的更明智的方法。例如，无线传感器网络流量的模型将与互联网流量的模型根本不同。如果做出适当的假设，我们的一些新交通模型可能适用于分析解决方案。这些流量模型将有两个不同的信息源：1。我们将从现有的现场试验和试验台收集无线传感器流量的痕迹。这些信息将从项目合作伙伴参与的其他项目中提供给我们。我们将从第一原则出发，通过生成传感器节点在给定应用程序中生成多少数据的统计描述，这将被称为流量源统计。通过假设，例如，网络布局和聚合策略，我们将能够产生交通行为模型，然后可以与上面描述的测量结果进行比较。我们所建立的模型将会引导传感器网络流量仿真新方法的发展。例如，使用我们的流量模型，可以对传感器节点进行编程，以模拟来自一大组节点的流量。通过这种方式，大型传感器网络可以只使用少量的节点来模拟，其中许多节点是模拟更大网络的一部分。因此，使用较少的设备，可以比其他方法更快地获得有用的性能信息。这个概念将作为我们工作的一部分进行调查和发展。此外，还有可能使我们开发的仿真软件作为该活动的一部分提供给正在研究该主题的其他小组。我们还将集成项目早期的软件开发，并将其部署到实际试验中。提案人与SECOAS、PROSEN和MC-DIAS的合作代表了对实验场景的访问，这将使协议性能的研究和环境、电力、水和电信应用领域的结果分析成为可能（见英国电信的支持信）。将与这些计划和试验建立关系，这将允许将新的协议战略与他们的扩展活动计划相结合，例如TUV NEL有限公司的风电场试验场。主要目的是演示理解应用程序和由此产生的流量配置文件的好处，以及对支持该应用程序的协议的适当分析。