无线传感器网络周期性数据收集研究
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摘要
无线传感器网络的出现将为人类的生产和生活提供极大的便捷,它将人类和物理世界互联。无线传感器网络通常会被部署在无人看护的户外等环境较为恶劣的区域。无线传感器网络中的节点的计算能力,通信能力有限,但是人们通常需要它们能自组网并提供有效和长时间的通信服务。由于严格的能量限制,传感器网络的能量必须仔细地管理和使用,从而延长网络的生命期。在大多数无线传感器网络的应用中,感测数据需要周期性的获取并发送到一个相对较远的基站。这个过程就是数据收集。它涉及到组网、路由、数据融合等关键技术,是一个综合性的问题。
本文针对周期性数据收集中的几个关键问题进行了研究。这几个问题是：能量均衡性、能效与时延平衡性、数据感知分簇。主要解决了“坏链路”问题、“热区”问题、时延优化问题、合理利用数据相关性问题,并且实现了协议,验证了性能。本文的主要工作和创新点有：
1.提出了能量均衡的数据收集协议
分析总结了能耗不均衡的原因,比如节点分布的随机性、被检测信息的时间和空间上的不规则性等。提出了一种能量均衡的数据收集协议LDEERS(Low Delay Energy Equalizing Routing Scheme),它由快速建立阶段、拓扑调整阶段和数据收集阶段组成。LDEERS采用了一种动态路由选择机制,该机制基于节点权值和高度值建立起一棵动态汇聚树,并根据一种类似于令牌传递的算法来选取树根。在每一轮里,当前根节点收集并融合所有节点发来的信息后传送给基站,然后选取下一轮的根节点。在这些机制的支持下,LDEERS能够以较低的开销简捷快速地组织网络中所有的节点,而且对网络拓扑变化有很好的健壮性。与PEGASIS(Power-Efficient Gathering in Sensor Information Systems)和HEED(Hybrid, Energy-Efficient, Distributed clustering approach)相比,仿真结果表明LDEERS实现了降低能耗,均衡所有节点能量,同时很好地延长网络生命期的目标。
2.提出了能效与时延平衡的数据收集机制
在追求能量高效的同时,考虑数据汇聚时延,提出了一种能效与时延平衡的数据收集机制EEDBDG(Energy Efficiency and Delay Balancing Data Gathering scheme),该机制采用一种新型动态树来组织网络拓扑,消除了“热区”问题,节点动态选择路由并轮换充当树根,根节点收集数据并与基站直接通信。同时,针对不同的时延和能效要求,提出了3种数据收集策略：能效最优算法EEDBDG-E(Energy),时延最优算法EEDBDG-D(Delay)和能效时延平衡算法EEDBDG-M(Median)。仿真结果表明,在节点通信半径受限的情况下,EEDBDG平衡了节点能量消耗,延长了网络生命时间,在节能与省时上均表现出了突出的性能。与GSEN(Group-based SEsor Network)相比,在最好情况下,EEDBDG-E网络生命期提高了72%,EEDBDG-D汇聚时延降低了74%。同时,探讨了基于动态树的数据收集过程中的安全问题,并给出了一种安全保证方案。
3.提出了基于数据感知的分簇数据收集协议
在以数据为中心的无线传感器网络中,节点间感知数据的相关性影响到分簇协议簇头数据聚合能力。分析了区域数据相关性对分簇能效性能的影响,指出了现有的协议中对数据相关度和数据融合能力假设的片面性和理想化。提出了一种基于数据感知的分簇数据收集协议DACDG(Data-Aware Clustering for Data Gathering). DACDG采用节点剩余能量和邻居节点感知数据的相关度作为成簇因素,并采用了多次迭代计算的办法选举簇头。与现有分簇协议比较,仿真结果表明DACDG降低和均衡了所有节点能耗,显著地延长了网络的生命期。
4.设计实验系统验证了数据收集协议性能
设计了一个数据收集实验系统,系统采用了自主设计的一个嵌入式小型协议栈,包括射频驱动层、MAC(Medium Access Control)层、网络层和传输层。协议栈适用于当前大多数无线传感器节点平台,使节点快速的自组织构建网络并且实现数据通信。在协议栈里实现了数据收集机制EEDBDG,并提出了一种可靠性数据通信组网方法MIN(Multiple Interactive Networking), MIN将链路选择融入到组网过程,基于准稳定区进行通信,提高节点间通信可靠性,完善了数据汇聚树的建立。最后给出了测试结果,验证了协议的性能。
The emergence of wireless sensor networks is making peoples' lives more convenient, and helps them more efficiently connect with the physical world. Wireless sensor networks are usually deployed in tougher outdoor environments where there is the absence of care. The capabilities of node processing and communication are limited, but people need them to provide more effective and longer service. Due to strict energy constraints, sensor network's energy resources should be carefully managed to extend the lifetime of the network. In many applications of wireless sensor networks, the sensed data must be periodically gathered and transmitted to a comparatively remote base station. This process is called data gathering which involves networking, routing, data fusion and other key technologies, and is a comprehensive issue.
In this dissertation, several key issues in periodic data gathering are studied. These issues are energy equalizing, energy efficiency and delay balance, data-aware clustering. The resolved problems are "bad-links" problem, "hot spots" problem, latency optimization problem, the rational use of data correlation. The proposed protocols are also achieved and the performances are verified. The main work and contributions of this dissertation include:
1. Proposes an energy equalizing data gathering scheme
The causes of energy imbalance, such as the random distribution of nodes, the irregular of the monitoring information in time and space are analyzed and summarized. A low delay energy equalizing routing scheme LDEERS is proposed for data gathering. It consists of rapid establishment phase, topology adjustment phase and data collection phase. LDEERS introduces a dynamic route selecting scheme based on weight-value and height-value to form a tree and a mechanism similar to token passing to elect the root of the tree in each round. In each round, the current root node collects and integrates all the information sent from nodes and transmits to the base station, and then selects the next root node. Underpinned by these schemes, LDEERS can simply and fast organize all the nodes with low overhead and is robust enough to the topology changes. Compared with PEGASIS (Power-Efficient Gathering in Sensor Information Systems) and HEED(Hybrid, Energy-Efficient, Distributed clustering approach), simulation results show that LDEERS achieves its goals of consuming less energy, equalizing the energy consumption of all the nodes, as well as extending the network lifetime perfectly.
2. Proposes an energy efficiency and delay balancing data gathering scheme
To consider the data gathering delay while seeking high energy efficiency in wireless sensor networks, energy efficiency and delay balancing data gathering scheme EEDBDG is proposed. EEDBDG organizes the topology based on a novel dynamic tree and avoids the "hot spots" problem. Nodes select routing path dynamically and take turns to act as the root of the tree. The root node gathers the data and communicates with the base station directly. In EEDBDG, three data gathering strategies are proposed for different request of delay and energy efficiency. These are optimum energy efficiency algorithm EEDBDG-E(Energy), optimum delay algorithm EEDBDG-D(Delay) and a compromise algorithm EEDBDG-M(Median). In the case that the sensor nodes communication radius is restricted, simulation results show that EEDBDG equalizes the energy consumption of all the nodes, prolongs the network lifetime and acquires an outstanding performance in energy-saving and time-thrift. Compared with GSEN(Group-based SEsor Network), in the best case, the network lifetime of EEDBDG-E is prolonged by 72% and the data gathering delay using EEDBDG-D is decreased by 74%. The security issues of dynamic tree-based data collection are also discussed, and a security scheme is proposed.
3. Proposes a data-aware clustering for data gathering
The data fusing ability of a cluster head is affected by the correlation of the sensed data from different nodes in wireless sensor networks, which are data centered. The influence of regional data correlation on the energy efficiency of a clustering protocol is analyzed, and it is pointed out that the assumptions of existing protocols for data correlation and data fusion capability of cluster head are one-sided and too ideal. A data-aware clustering for data gathering DACDG is proposed. DACDG uses the residual energy and the correction of sensed data from the neighbors to construct clusters, and adopts iterative computing to elect a cluster head. When compared with existing protocols, our simulation results show that DACDG achieves its goals of consuming less energy, equalizing the energy consumption of all the nodes, and extremely extending the network lifetime.
4. Designs an experimental system to verify the performances of data gathering protocols
An experimental system of data collection is designed. An embedded protocol stack was designed and used in our system, including the Radio Frequency driver layer, MAC(Medium Access Control) layer, network layer and transport layer. The protocol stack adapts to most of the current wireless sensor network node platform, which can quickly construct the network systematically, and realize data communication. The data gathering scheme EEDBDG is achieved in the protocol stack. An effective stable data communication networking approach called MIN (Multiple Interactive Networking) is designed to establish a quasi-stable link and to form the network. MIN transmits data using the most reliable node, improves the reliability of data transmissions, and prefects the establishment of data aggregation tree. Finally, the test results verify the performance of the protocol.
本文针对周期性数据收集中的几个关键问题进行了研究。这几个问题是：能量均衡性、能效与时延平衡性、数据感知分簇。主要解决了“坏链路”问题、“热区”问题、时延优化问题、合理利用数据相关性问题,并且实现了协议,验证了性能。本文的主要工作和创新点有：
1.提出了能量均衡的数据收集协议
分析总结了能耗不均衡的原因,比如节点分布的随机性、被检测信息的时间和空间上的不规则性等。提出了一种能量均衡的数据收集协议LDEERS(Low Delay Energy Equalizing Routing Scheme),它由快速建立阶段、拓扑调整阶段和数据收集阶段组成。LDEERS采用了一种动态路由选择机制,该机制基于节点权值和高度值建立起一棵动态汇聚树,并根据一种类似于令牌传递的算法来选取树根。在每一轮里,当前根节点收集并融合所有节点发来的信息后传送给基站,然后选取下一轮的根节点。在这些机制的支持下,LDEERS能够以较低的开销简捷快速地组织网络中所有的节点,而且对网络拓扑变化有很好的健壮性。与PEGASIS(Power-Efficient Gathering in Sensor Information Systems)和HEED(Hybrid, Energy-Efficient, Distributed clustering approach)相比,仿真结果表明LDEERS实现了降低能耗,均衡所有节点能量,同时很好地延长网络生命期的目标。
2.提出了能效与时延平衡的数据收集机制
在追求能量高效的同时,考虑数据汇聚时延,提出了一种能效与时延平衡的数据收集机制EEDBDG(Energy Efficiency and Delay Balancing Data Gathering scheme),该机制采用一种新型动态树来组织网络拓扑,消除了“热区”问题,节点动态选择路由并轮换充当树根,根节点收集数据并与基站直接通信。同时,针对不同的时延和能效要求,提出了3种数据收集策略：能效最优算法EEDBDG-E(Energy),时延最优算法EEDBDG-D(Delay)和能效时延平衡算法EEDBDG-M(Median)。仿真结果表明,在节点通信半径受限的情况下,EEDBDG平衡了节点能量消耗,延长了网络生命时间,在节能与省时上均表现出了突出的性能。与GSEN(Group-based SEsor Network)相比,在最好情况下,EEDBDG-E网络生命期提高了72%,EEDBDG-D汇聚时延降低了74%。同时,探讨了基于动态树的数据收集过程中的安全问题,并给出了一种安全保证方案。
3.提出了基于数据感知的分簇数据收集协议
在以数据为中心的无线传感器网络中,节点间感知数据的相关性影响到分簇协议簇头数据聚合能力。分析了区域数据相关性对分簇能效性能的影响,指出了现有的协议中对数据相关度和数据融合能力假设的片面性和理想化。提出了一种基于数据感知的分簇数据收集协议DACDG(Data-Aware Clustering for Data Gathering). DACDG采用节点剩余能量和邻居节点感知数据的相关度作为成簇因素,并采用了多次迭代计算的办法选举簇头。与现有分簇协议比较,仿真结果表明DACDG降低和均衡了所有节点能耗,显著地延长了网络的生命期。
4.设计实验系统验证了数据收集协议性能
设计了一个数据收集实验系统,系统采用了自主设计的一个嵌入式小型协议栈,包括射频驱动层、MAC(Medium Access Control)层、网络层和传输层。协议栈适用于当前大多数无线传感器节点平台,使节点快速的自组织构建网络并且实现数据通信。在协议栈里实现了数据收集机制EEDBDG,并提出了一种可靠性数据通信组网方法MIN(Multiple Interactive Networking), MIN将链路选择融入到组网过程,基于准稳定区进行通信,提高节点间通信可靠性,完善了数据汇聚树的建立。最后给出了测试结果,验证了协议的性能。
The emergence of wireless sensor networks is making peoples' lives more convenient, and helps them more efficiently connect with the physical world. Wireless sensor networks are usually deployed in tougher outdoor environments where there is the absence of care. The capabilities of node processing and communication are limited, but people need them to provide more effective and longer service. Due to strict energy constraints, sensor network's energy resources should be carefully managed to extend the lifetime of the network. In many applications of wireless sensor networks, the sensed data must be periodically gathered and transmitted to a comparatively remote base station. This process is called data gathering which involves networking, routing, data fusion and other key technologies, and is a comprehensive issue.
In this dissertation, several key issues in periodic data gathering are studied. These issues are energy equalizing, energy efficiency and delay balance, data-aware clustering. The resolved problems are "bad-links" problem, "hot spots" problem, latency optimization problem, the rational use of data correlation. The proposed protocols are also achieved and the performances are verified. The main work and contributions of this dissertation include:
1. Proposes an energy equalizing data gathering scheme
The causes of energy imbalance, such as the random distribution of nodes, the irregular of the monitoring information in time and space are analyzed and summarized. A low delay energy equalizing routing scheme LDEERS is proposed for data gathering. It consists of rapid establishment phase, topology adjustment phase and data collection phase. LDEERS introduces a dynamic route selecting scheme based on weight-value and height-value to form a tree and a mechanism similar to token passing to elect the root of the tree in each round. In each round, the current root node collects and integrates all the information sent from nodes and transmits to the base station, and then selects the next root node. Underpinned by these schemes, LDEERS can simply and fast organize all the nodes with low overhead and is robust enough to the topology changes. Compared with PEGASIS (Power-Efficient Gathering in Sensor Information Systems) and HEED(Hybrid, Energy-Efficient, Distributed clustering approach), simulation results show that LDEERS achieves its goals of consuming less energy, equalizing the energy consumption of all the nodes, as well as extending the network lifetime perfectly.
2. Proposes an energy efficiency and delay balancing data gathering scheme
To consider the data gathering delay while seeking high energy efficiency in wireless sensor networks, energy efficiency and delay balancing data gathering scheme EEDBDG is proposed. EEDBDG organizes the topology based on a novel dynamic tree and avoids the "hot spots" problem. Nodes select routing path dynamically and take turns to act as the root of the tree. The root node gathers the data and communicates with the base station directly. In EEDBDG, three data gathering strategies are proposed for different request of delay and energy efficiency. These are optimum energy efficiency algorithm EEDBDG-E(Energy), optimum delay algorithm EEDBDG-D(Delay) and a compromise algorithm EEDBDG-M(Median). In the case that the sensor nodes communication radius is restricted, simulation results show that EEDBDG equalizes the energy consumption of all the nodes, prolongs the network lifetime and acquires an outstanding performance in energy-saving and time-thrift. Compared with GSEN(Group-based SEsor Network), in the best case, the network lifetime of EEDBDG-E is prolonged by 72% and the data gathering delay using EEDBDG-D is decreased by 74%. The security issues of dynamic tree-based data collection are also discussed, and a security scheme is proposed.
3. Proposes a data-aware clustering for data gathering
The data fusing ability of a cluster head is affected by the correlation of the sensed data from different nodes in wireless sensor networks, which are data centered. The influence of regional data correlation on the energy efficiency of a clustering protocol is analyzed, and it is pointed out that the assumptions of existing protocols for data correlation and data fusion capability of cluster head are one-sided and too ideal. A data-aware clustering for data gathering DACDG is proposed. DACDG uses the residual energy and the correction of sensed data from the neighbors to construct clusters, and adopts iterative computing to elect a cluster head. When compared with existing protocols, our simulation results show that DACDG achieves its goals of consuming less energy, equalizing the energy consumption of all the nodes, and extremely extending the network lifetime.
4. Designs an experimental system to verify the performances of data gathering protocols
An experimental system of data collection is designed. An embedded protocol stack was designed and used in our system, including the Radio Frequency driver layer, MAC(Medium Access Control) layer, network layer and transport layer. The protocol stack adapts to most of the current wireless sensor network node platform, which can quickly construct the network systematically, and realize data communication. The data gathering scheme EEDBDG is achieved in the protocol stack. An effective stable data communication networking approach called MIN (Multiple Interactive Networking) is designed to establish a quasi-stable link and to form the network. MIN transmits data using the most reliable node, improves the reliability of data transmissions, and prefects the establishment of data aggregation tree. Finally, the test results verify the performance of the protocol.
引文
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