无线传感器网络能量高效组建关键技术的研究
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摘要
无线传感器网络通常是指由密布在感知区域内的大量传感器节点组成的网络。无线传感器网络的组建可不依赖于任何网络基础设施,它是一种无中心、分布式、多跳传输、自组织的无线通信网络。由于其具有可快速部署、抗毁性强、监测精度高、覆盖区域大等特点,无线传感器网络技术已经成为当前信息领域的研究热点之一。传感器节点多采用电池进行供电,能量十分有限,因此如何高效利用传感器节点的有限能量,尽可能的延长无线传感器网络的寿命成为无线传感器网络技术的基本研究目标。针对这一研究目标,本文对能量高效的无线传感器网络组网技术中的几个关键技术,包括地址分配技术、密度控制技术、拓扑控制技术和接入技术进行了研究,通过在其中使用节能技术,提高了无线传感器网络的能量效率,延长了网络寿命。
传感器节点的地址自动分配是实现无线传感器网络组建的前提和基础。地址分配协议的效率对传感器节点的能量消耗也有着一定的影响。为了方便传感器网络与Internet的互联,考虑到IPv6可以提供大量网络地址,更符合无线传感器网络要求地址数量较多的这个特点,本文为无线传感器网络提出了一种基于多代理的IPv6地址自动配置协议SNMAAP。通过在网络中使用地址代理节点,不仅可以使节点在很短的时间内获得可用地址,也大大降低了地址出现冲突的概率和网络开销。实验结果表明在相同条件下SNMAAP协议不仅保证了IPv6地址的唯一分配,协议的开销、延迟和重复检测开销也均较小。
在无线传感器网络中通常密布着大量传感器节点。如果让所有的传感器节点都工作,不仅会出现大量冗余信息,也会对网络吞吐率、带宽、时延、能量等造成很大影响,因此需要使用密度控制技术,在保证网络覆盖与网络连通的前提下减少工作节点的数量。本文为无线传感器网络提出一种密度控制算法SNDC,通过使用此算法只要令尽量少的传感器节点处于活跃工作状态中,就可获得对一个感知区域的连通的完全覆盖。不活跃的传感器可以关闭它们的感知模块来节约能量。与其它算法不同,本算法不依赖于传感器节点的精确位置信息或者距离信息。它只要求每个活跃的传感器节点周期性的发送三个不同传输距离的信标帧,传感器节点可以由此决定是否保持活跃状态或者不活跃状态。此算法也是具有容错性的,当任何活跃的传感器节点因为能量耗尽或者出现故障而失效时,一个或多个不活跃的传感器节点可以转化为活跃节点来接管工作。在假设RC≥2RS的前提下,本文的算法可获得接近最优的连通覆盖,其中RC为传感器节点的通信半径,RS为传感器节点的感知半径。
拓扑控制技术对无线传感器网络性能也有着直接的影响。本文在本地最小生成树LMST算法的基础上,提出一种能量均衡的拓扑控制算法EBTCA。该算法在构建局部最小生成树时不仅考虑了节点间的通信能耗,也考虑了节点剩余能量,从而既能使局部总能耗接近最小化,又获得了节点能量平衡的效果,解决了网络中“瓶颈”节点因负载过大较快死亡的问题,延长了节点的工作时间,进而延长了网络的生命期。实验结果表明EBTCA算法在保证了较低的端到端时延、较高的吞吐量与投递率等前提下,提高了网络内生存节点的数量,有效地延长了网络寿命。
当无线传感器网络接入到Internet中时,可以更好的发挥无线传感器网络的作用。传统的无线传感器网络接入策略没有对多sink网络环境中的sink节点进行负载平衡处理,也没有考虑sink节点一跳范围内传感器节点的负载平衡问题,这样不仅会使接入延迟较大,也会大量消耗节点能量,缩短网络接入时间。本文提出了一种在多sink环境下的无线传感器网络接入策略ELSIC,将sink节点一跳范围内的传感器节点设置为代理节点,综合考虑能量、延迟、距离等因素,通过负载平衡策略,将无线传感器网络的接入负载分摊给每个代理节点和sink节点,这样既可减少接入延迟,又延长了网络接入时间。仿真实验结果表明在相同的条件下ELSIC策略不仅实现了传感器网络与Internet的数据接入,其接入延迟更小,节点工作时间更长,网络接入时间更久,吞吐量也较高。
为了考察在组建无线传感器网络过程中综合使用本文研究内容时的网络性能和节能效果,本文对传感器网络的体系结构进行了分析与设计,并将此网络于OPNET Modeler仿真平台上进行了仿真测试。为了考察传感器网络在不同节点数量、密度和不同网络负载情况下的性能,本文又设计了四种网络场景。在仿真时主要对生存节点数量、网络总能量、平均节点能量、投递率、端到端时延、吞吐量进行了考察。仿真结果显示,本文研究的协议和算法不仅可以保证较好的投递率、端到端时延和吞吐量,也可以大大提高网络中生存节点的数量和能量效率,网络寿命得到了延长。
A wireless sensor network is a wireless network consisted of a great deal of sensor nodes which are deployed densely in the sensing region. The establishment of wireless sensor network does not depend on any network infrastructure. It is a non-central, distributed, multi-hop transmission, self-organizing wireless communication networks. Owing to its features, such as rapid deployment, survivability, high accuracy surveillance and large coverage, wireless sensor network technology has become a research hotspot of IT field. Sensor node is battery-powered, and its energy is very limited. Consequently, how to efficiently use the limited energy of sensor nodes and extend wireless sensor network lifetime as long as possible has become its basic research goal. Aim at this goal, this article studies some key technologies which are used to build sensor networks, including address allocation strategy, density control technology, topology control technology and access technology. By putting energy-saving technology in these technologies, the wireless sensor network improves energy efficiency and extends its lifetime.
The auto assignment of IP address is the premise and foundation to form wireless sensor networks. It also has an effect on energy consumption of sensor nodes. In order to communicate with the Internet easily, in this paper, we present SNMAAP (Sensor Networks Multi-agents Address Assignment Protocol), an IPv6 address assignment protocol based on multi-agents for sensor networks, utilizing the IPv6 to meet the wireless sensor network requirement of considerable network addresses. By using agent nodes in the network, not only each node can get an IP address in a short period of time, but also the probability of the address collision and overhead is low. The simulation results demonstrate that under the same condition, SNMAAP guarantees a unique IP address assignment and has lower latency, communication and duplicate address detection overhead.
There are often a large number of sensor nodes in wireless sensor network. If all sensor nodes worked together, not only there would be a lot of redundant information, but also they would have great adverse impact on network throughput, bandwidth, latency, and energy. So we use density control technology to reduce the number of active sensor nodes under the precondition of ensuring network coverage and network connectivity. We propose SNDC (Sensor Network Density Control), a density control algorithm for wireless sensor network to keep as few as possible sensors in active state to achieve a complete connected coverage of a specific monitored area. Inactive sensors can turn off sensing modules to save energy. Unlike other algorithms, the proposed one does not rely on position information or ranging information of sensors. It just requires each active sensor to periodically send three beacons of different transmission ranges. Sensors can decide to stay active or inactive state according to received beacons. The proposed algorithm is fault-tolerant in the sense that one or more inactive sensors can switch to the active state to take over the surveillance responsibility when any active sensor runs out of energy or fails. Under the assumption of RC≥2RS, the algorithm can approximate the optimal connected coverage, where RC and RC are the radio communication radius and the sensing radius of sensors, respectively.
Topology control technology of wireless sensor network has a direct impact on network performance. This article proposes EBTCA (Energy Balance Topology Control Algorithm) based on LMST algorithm. The algorithm takes not only the communication but also the remaining node energy into account. It will be able to minimize total energy consumption, achieve energy balance, and solve the problem that bottlenecks nodes die rapidly because of high load. It can also extend the working time of the sensor nodes, and then extend the network lifetime. The simulation results show that EBTCA effectively extends the lifetime of the network under the premise of guaranteeing low end-to-end latency, high throughput and delivery rate.
The internet connectivity is required in order that the wireless sensor network can be applied effectively. Traditional wireless sensor network connectivity strategy doesn't take the load balance of sinks and sensor nodes within the one hop range of sinks into account. It will lead to the increase of connection latency, the consumption of node energy and the decrease of connection time. In this paper, we present ELSIC (Energy-aware Load-balanced Strategy for Internet Connectivity of wireless sensor network). We make the sensor node that in the one hop range of sink the agent node. By using the load balance strategy which takes energy, latency, distance and other factors into account, we distribute the connection load to every sink and agent node. This will decrease the latency, prolong the connection time. The simulation results demonstrate that under the same condition, ELSIC guarantees the internet connectivity and has lower latency, longer node life and connection time, and the higher throughput.
In order to evaluate the network performance and energy performance when building wireless sensor network with the algorithm proposed by this paper, we analysis and design architecture of wireless sensor network and simulate search strategy on the OPNET Modeler. We design four scenes for studying sensor network performance in different node density and network load. The number of alive nodes, network energy, avergy node energy, delivery ratio, end-to-end latency, and throughput are considered and compared in the simulation. The simulation results demonstrate that proposed algorithms not only can ensure good delivery rate, end-to-end latency and throughput, but also can greatly increase the number of alive nodes in the network, improved energy efficiency and prolong the lifetime of network.
传感器节点的地址自动分配是实现无线传感器网络组建的前提和基础。地址分配协议的效率对传感器节点的能量消耗也有着一定的影响。为了方便传感器网络与Internet的互联,考虑到IPv6可以提供大量网络地址,更符合无线传感器网络要求地址数量较多的这个特点,本文为无线传感器网络提出了一种基于多代理的IPv6地址自动配置协议SNMAAP。通过在网络中使用地址代理节点,不仅可以使节点在很短的时间内获得可用地址,也大大降低了地址出现冲突的概率和网络开销。实验结果表明在相同条件下SNMAAP协议不仅保证了IPv6地址的唯一分配,协议的开销、延迟和重复检测开销也均较小。
在无线传感器网络中通常密布着大量传感器节点。如果让所有的传感器节点都工作,不仅会出现大量冗余信息,也会对网络吞吐率、带宽、时延、能量等造成很大影响,因此需要使用密度控制技术,在保证网络覆盖与网络连通的前提下减少工作节点的数量。本文为无线传感器网络提出一种密度控制算法SNDC,通过使用此算法只要令尽量少的传感器节点处于活跃工作状态中,就可获得对一个感知区域的连通的完全覆盖。不活跃的传感器可以关闭它们的感知模块来节约能量。与其它算法不同,本算法不依赖于传感器节点的精确位置信息或者距离信息。它只要求每个活跃的传感器节点周期性的发送三个不同传输距离的信标帧,传感器节点可以由此决定是否保持活跃状态或者不活跃状态。此算法也是具有容错性的,当任何活跃的传感器节点因为能量耗尽或者出现故障而失效时,一个或多个不活跃的传感器节点可以转化为活跃节点来接管工作。在假设RC≥2RS的前提下,本文的算法可获得接近最优的连通覆盖,其中RC为传感器节点的通信半径,RS为传感器节点的感知半径。
拓扑控制技术对无线传感器网络性能也有着直接的影响。本文在本地最小生成树LMST算法的基础上,提出一种能量均衡的拓扑控制算法EBTCA。该算法在构建局部最小生成树时不仅考虑了节点间的通信能耗,也考虑了节点剩余能量,从而既能使局部总能耗接近最小化,又获得了节点能量平衡的效果,解决了网络中“瓶颈”节点因负载过大较快死亡的问题,延长了节点的工作时间,进而延长了网络的生命期。实验结果表明EBTCA算法在保证了较低的端到端时延、较高的吞吐量与投递率等前提下,提高了网络内生存节点的数量,有效地延长了网络寿命。
当无线传感器网络接入到Internet中时,可以更好的发挥无线传感器网络的作用。传统的无线传感器网络接入策略没有对多sink网络环境中的sink节点进行负载平衡处理,也没有考虑sink节点一跳范围内传感器节点的负载平衡问题,这样不仅会使接入延迟较大,也会大量消耗节点能量,缩短网络接入时间。本文提出了一种在多sink环境下的无线传感器网络接入策略ELSIC,将sink节点一跳范围内的传感器节点设置为代理节点,综合考虑能量、延迟、距离等因素,通过负载平衡策略,将无线传感器网络的接入负载分摊给每个代理节点和sink节点,这样既可减少接入延迟,又延长了网络接入时间。仿真实验结果表明在相同的条件下ELSIC策略不仅实现了传感器网络与Internet的数据接入,其接入延迟更小,节点工作时间更长,网络接入时间更久,吞吐量也较高。
为了考察在组建无线传感器网络过程中综合使用本文研究内容时的网络性能和节能效果,本文对传感器网络的体系结构进行了分析与设计,并将此网络于OPNET Modeler仿真平台上进行了仿真测试。为了考察传感器网络在不同节点数量、密度和不同网络负载情况下的性能,本文又设计了四种网络场景。在仿真时主要对生存节点数量、网络总能量、平均节点能量、投递率、端到端时延、吞吐量进行了考察。仿真结果显示,本文研究的协议和算法不仅可以保证较好的投递率、端到端时延和吞吐量,也可以大大提高网络中生存节点的数量和能量效率,网络寿命得到了延长。
A wireless sensor network is a wireless network consisted of a great deal of sensor nodes which are deployed densely in the sensing region. The establishment of wireless sensor network does not depend on any network infrastructure. It is a non-central, distributed, multi-hop transmission, self-organizing wireless communication networks. Owing to its features, such as rapid deployment, survivability, high accuracy surveillance and large coverage, wireless sensor network technology has become a research hotspot of IT field. Sensor node is battery-powered, and its energy is very limited. Consequently, how to efficiently use the limited energy of sensor nodes and extend wireless sensor network lifetime as long as possible has become its basic research goal. Aim at this goal, this article studies some key technologies which are used to build sensor networks, including address allocation strategy, density control technology, topology control technology and access technology. By putting energy-saving technology in these technologies, the wireless sensor network improves energy efficiency and extends its lifetime.
The auto assignment of IP address is the premise and foundation to form wireless sensor networks. It also has an effect on energy consumption of sensor nodes. In order to communicate with the Internet easily, in this paper, we present SNMAAP (Sensor Networks Multi-agents Address Assignment Protocol), an IPv6 address assignment protocol based on multi-agents for sensor networks, utilizing the IPv6 to meet the wireless sensor network requirement of considerable network addresses. By using agent nodes in the network, not only each node can get an IP address in a short period of time, but also the probability of the address collision and overhead is low. The simulation results demonstrate that under the same condition, SNMAAP guarantees a unique IP address assignment and has lower latency, communication and duplicate address detection overhead.
There are often a large number of sensor nodes in wireless sensor network. If all sensor nodes worked together, not only there would be a lot of redundant information, but also they would have great adverse impact on network throughput, bandwidth, latency, and energy. So we use density control technology to reduce the number of active sensor nodes under the precondition of ensuring network coverage and network connectivity. We propose SNDC (Sensor Network Density Control), a density control algorithm for wireless sensor network to keep as few as possible sensors in active state to achieve a complete connected coverage of a specific monitored area. Inactive sensors can turn off sensing modules to save energy. Unlike other algorithms, the proposed one does not rely on position information or ranging information of sensors. It just requires each active sensor to periodically send three beacons of different transmission ranges. Sensors can decide to stay active or inactive state according to received beacons. The proposed algorithm is fault-tolerant in the sense that one or more inactive sensors can switch to the active state to take over the surveillance responsibility when any active sensor runs out of energy or fails. Under the assumption of RC≥2RS, the algorithm can approximate the optimal connected coverage, where RC and RC are the radio communication radius and the sensing radius of sensors, respectively.
Topology control technology of wireless sensor network has a direct impact on network performance. This article proposes EBTCA (Energy Balance Topology Control Algorithm) based on LMST algorithm. The algorithm takes not only the communication but also the remaining node energy into account. It will be able to minimize total energy consumption, achieve energy balance, and solve the problem that bottlenecks nodes die rapidly because of high load. It can also extend the working time of the sensor nodes, and then extend the network lifetime. The simulation results show that EBTCA effectively extends the lifetime of the network under the premise of guaranteeing low end-to-end latency, high throughput and delivery rate.
The internet connectivity is required in order that the wireless sensor network can be applied effectively. Traditional wireless sensor network connectivity strategy doesn't take the load balance of sinks and sensor nodes within the one hop range of sinks into account. It will lead to the increase of connection latency, the consumption of node energy and the decrease of connection time. In this paper, we present ELSIC (Energy-aware Load-balanced Strategy for Internet Connectivity of wireless sensor network). We make the sensor node that in the one hop range of sink the agent node. By using the load balance strategy which takes energy, latency, distance and other factors into account, we distribute the connection load to every sink and agent node. This will decrease the latency, prolong the connection time. The simulation results demonstrate that under the same condition, ELSIC guarantees the internet connectivity and has lower latency, longer node life and connection time, and the higher throughput.
In order to evaluate the network performance and energy performance when building wireless sensor network with the algorithm proposed by this paper, we analysis and design architecture of wireless sensor network and simulate search strategy on the OPNET Modeler. We design four scenes for studying sensor network performance in different node density and network load. The number of alive nodes, network energy, avergy node energy, delivery ratio, end-to-end latency, and throughput are considered and compared in the simulation. The simulation results demonstrate that proposed algorithms not only can ensure good delivery rate, end-to-end latency and throughput, but also can greatly increase the number of alive nodes in the network, improved energy efficiency and prolong the lifetime of network.
引文
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49 L.-H. Yen, C. W. Yu, Y.-M. Cheng. Expected k-coverage in wireless sensor networks. Ad Hoc Networks, 2006, 5(4): 636~650
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54 Seungki Hong Yeon-Jun Choi, Sun-Joong Kim. An Energy Efficient Topology Control Protocol in Wireless Sensor Networks. Advanced Communication Technology, The 9th International Conference on. 12-14 Feb. 2007, (1): 537~541
55 Zhonglou Meng, Shu Wang, Qi Wang. Fault Tolerant Topology Control for Clustered Wireless Sensor Networks. Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on. 12-14 Oct. 2008: 1~5
56 Ramanathan R, Rosales-Hain R. Topology Control of Multihop Wireless Networks Using Transmit Power Adjustment. Proc. IEEE INFOCOM. 2000: 404~413
57 Zhuochuan Huang, Chien-Chung Shen, Srisathapornphat, Jaikaeo C. Topology Control for Ad Hoc Networks with Directional Antennas. In Computer Communications and Networks. 2002: 16~21
58 Jerzy W. Jaromczyk, Godfried T. Toussaint. The Relative Neighbourhood Graphs and Their Relatives. Proceedings of the IEEE. Sept. 1992, 80(9): 1502~1517
59 Chi-Fu Huang, Yu-Chee Tseng, Shih-Lin Wu, Jang-Ping Sheu. Distributed Topology Control Algorithm for Multihop Wireless Networks. Proceedings of the 2002 International Joint Conference on. 2002, (1): 355~360
60 Kenneth J. Supowit. The Relative Neighbourhood Graph with Application to Minimum Spannig Trees. Journal of the ACM. 1983, 30(3): 428~448
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