无线传感器网络容分割及节能信息汇集算法研究
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摘要
在无线传感器网络中,由于传感器节点能量的有限及它们之间不稳定的无线电通信,可能造成网络的分割。针对无线传感器网络分区之间的通信,信息摆渡(Message Ferrying)是一种十分有效的方案。
对于连通网络,本文提出了几种基于树的路由算法。首先是基于Dijkstra算法的LET(Least Energy Tree)和MHT(Least Hop Tree)路由算法,它们是分别对整个网络的能量消耗和网络延时的最小化而得到的生成树。另外,一种是基于Prim算法的MST(Minimum Spanning Tree)路由算法,其中权值是根据能量消耗计算得到的。为了更好的比较,本文着重提出了一种智能的LPER(Learning-based Power EfficientRouting)路由算法。在LPER算法中,通过构建一个用来权衡网络生存时间,能量消耗和网络延时三方面的自适应函数,及使用蚁群系统来建立最佳路由。此外,使用增加学习来预测邻居节点的能量消耗。此算法可以保证低能耗和低延时的同时,最优化无线传感器网络的生存时间。通过实验显示,只是能量消耗高于LET算法,而在其他方面都要比MST和LET算法来得优越。
一旦网络出现分割,那么从传感器节点到基站的端到端的路由就需要重新建立。在这种情况之下,信息摆渡技术路由对于分割网络之间传输数据将是最佳选择。由于摆渡节点从一个分区运动到另一个分区是收集数据是预先设计好的,因此信息摆渡技术对于分离网络来说是一个先应式路由方案。本文提出了两类簇头选择模式:一类是基于树的簇头模式,本章中列举了三种具体的方式;另一类是基于支配集的簇头模式,通过OLT(One Level Tree)算法还可以得到每个节点的支配节点(簇头)。摆渡节点运动一圈需要消耗最小能量是一个TSP问题,本文使用遗传算法可以很好地解决这个问题。通过实验得到,在摆渡节点的能耗忽略不计或较小的情况下,OLT算法要比MHT,MST和LET算法更加节能。然后,在摆渡节点运动需要消耗较大的能量时,LET算法是一种较理想的选择。
Wireless sensor networks (WSNs) are prone to partitioning due to limited energy in sensor nodes and unreliable radio communications between them. Message ferrying (MF) schema has been proposed as an effective means to deliver data between separated parts of a partitioned WSN.
This dissertation proposes a tree-based routing algorithm for connected networks, in which minimum-weight trees of each partition of the WSN are evaluated with different alternate root nodes. Appropriate choice of the weights allows overall energy consumption or delay to be minimized. Two kinds of tree-construeting algorithms respectively named Least Energy Tree (LET) and Minimum Hop Tree (MHT) based on the Dijkstra algorithm are presented and evaluated by deriving an energy model. And, Minimum Spanning Tree (MST) based on Prim algorithm at a single root node is considered. For comparison, The Learning-based Power Efficient Routing (LPER) algorithm is emphatically proposed. In the LPER, a fitness function, which balances network lifetime, energy consumption, and packet delay, is constructed and used in an ant colony system to establish the optimal route. In addition, reinforcement learning is applied in predicting the energy consumption of neighboring nodes. The LPER is able to optimize network lifetime of WSNs, while keeping energy consumption and packet delay in a relative low level. Numeric experiments show the LPER outperforms the MST and LET based routing algorithms in terms of network lifetime and packet delay, although energy consumption of LET is superior to one of LPER.
An end-to-end route for data delivery from the source to the sink may not be reconstructed if the network is partitioned. In this situation, MF routing is a good choice to deliver data between network partitions. MF is a proactive routing scheme for disconnected networks, in which ferries move proactively into one network partition to collect messages and deliver them to other partitions when the network becomes partitioned. At first, this dissertation provides two kinds of cluster head selection. Three different selections are included in the first selection based on tree and OLT selection is based on the dominating set rule, which also determines each node's route path. How to get the distance-optimal ferry route is a Traveling Salesman Problem (TSP). In light of the combinatorial nature of the problem, genetic algorithms (GAs) are viable alternatives. Simulation experiments show that OLT outperforms MHT, MST, and LET when the energy consumption of the ferry is small or negligible. However, LET probably outperforms the other three methods when the energy consumption of the ferry is in the high level.
对于连通网络,本文提出了几种基于树的路由算法。首先是基于Dijkstra算法的LET(Least Energy Tree)和MHT(Least Hop Tree)路由算法,它们是分别对整个网络的能量消耗和网络延时的最小化而得到的生成树。另外,一种是基于Prim算法的MST(Minimum Spanning Tree)路由算法,其中权值是根据能量消耗计算得到的。为了更好的比较,本文着重提出了一种智能的LPER(Learning-based Power EfficientRouting)路由算法。在LPER算法中,通过构建一个用来权衡网络生存时间,能量消耗和网络延时三方面的自适应函数,及使用蚁群系统来建立最佳路由。此外,使用增加学习来预测邻居节点的能量消耗。此算法可以保证低能耗和低延时的同时,最优化无线传感器网络的生存时间。通过实验显示,只是能量消耗高于LET算法,而在其他方面都要比MST和LET算法来得优越。
一旦网络出现分割,那么从传感器节点到基站的端到端的路由就需要重新建立。在这种情况之下,信息摆渡技术路由对于分割网络之间传输数据将是最佳选择。由于摆渡节点从一个分区运动到另一个分区是收集数据是预先设计好的,因此信息摆渡技术对于分离网络来说是一个先应式路由方案。本文提出了两类簇头选择模式:一类是基于树的簇头模式,本章中列举了三种具体的方式;另一类是基于支配集的簇头模式,通过OLT(One Level Tree)算法还可以得到每个节点的支配节点(簇头)。摆渡节点运动一圈需要消耗最小能量是一个TSP问题,本文使用遗传算法可以很好地解决这个问题。通过实验得到,在摆渡节点的能耗忽略不计或较小的情况下,OLT算法要比MHT,MST和LET算法更加节能。然后,在摆渡节点运动需要消耗较大的能量时,LET算法是一种较理想的选择。
Wireless sensor networks (WSNs) are prone to partitioning due to limited energy in sensor nodes and unreliable radio communications between them. Message ferrying (MF) schema has been proposed as an effective means to deliver data between separated parts of a partitioned WSN.
This dissertation proposes a tree-based routing algorithm for connected networks, in which minimum-weight trees of each partition of the WSN are evaluated with different alternate root nodes. Appropriate choice of the weights allows overall energy consumption or delay to be minimized. Two kinds of tree-construeting algorithms respectively named Least Energy Tree (LET) and Minimum Hop Tree (MHT) based on the Dijkstra algorithm are presented and evaluated by deriving an energy model. And, Minimum Spanning Tree (MST) based on Prim algorithm at a single root node is considered. For comparison, The Learning-based Power Efficient Routing (LPER) algorithm is emphatically proposed. In the LPER, a fitness function, which balances network lifetime, energy consumption, and packet delay, is constructed and used in an ant colony system to establish the optimal route. In addition, reinforcement learning is applied in predicting the energy consumption of neighboring nodes. The LPER is able to optimize network lifetime of WSNs, while keeping energy consumption and packet delay in a relative low level. Numeric experiments show the LPER outperforms the MST and LET based routing algorithms in terms of network lifetime and packet delay, although energy consumption of LET is superior to one of LPER.
An end-to-end route for data delivery from the source to the sink may not be reconstructed if the network is partitioned. In this situation, MF routing is a good choice to deliver data between network partitions. MF is a proactive routing scheme for disconnected networks, in which ferries move proactively into one network partition to collect messages and deliver them to other partitions when the network becomes partitioned. At first, this dissertation provides two kinds of cluster head selection. Three different selections are included in the first selection based on tree and OLT selection is based on the dominating set rule, which also determines each node's route path. How to get the distance-optimal ferry route is a Traveling Salesman Problem (TSP). In light of the combinatorial nature of the problem, genetic algorithms (GAs) are viable alternatives. Simulation experiments show that OLT outperforms MHT, MST, and LET when the energy consumption of the ferry is small or negligible. However, LET probably outperforms the other three methods when the energy consumption of the ferry is in the high level.
引文
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[2]Holger Karl,Andreas Willing著,邱天爽等译.无线传感器网络协议与体系结[M].北京:电子工业出版社,2007.
[3]王殊,阎毓杰,胡富平,屈晓旭编著.无线传感器网络的理论及应用[M].北京:北京航空航天出版社,2007.
[4]Marco Dorigo,Thomas Stützle著,张军,胡晓敏,罗旭耀等译.蚁群优化[M].北京:清华大学出版社,2007.
[5]陈国良,王煦法,庄镇泉,王东生编著.遗传算法及其应用[M],北京:人民邮电出版社,1999.
[6]段海滨编著.蚁群算法原理及其应用[M].北京:科学出版社,2005.
[7]高炜欣,罗先觉著.基于蚁群算法的配电网网络规划[J].中国电机工程学报,2004,24(9):110-114.
[8]孙京浩,李秋艳等著.基于蚁群算法的故障识别[J].华东理工大学学报,2004,30(2):194-198.
[9]高阳,陈世福,陆鑫著.强化学习研究综述[J].自动化学报,2004,30(1):86-100.
[10]王小平,曹立明著.遗传算法:理论、应用与软件实现[M].西安交通大学出版社,2002.
[11]Marco Dorigo,Vittorio Maniezzo and Alberto Colorn.Ant System Optimizaiton by a Colony of cooperating Agents[J].IEEE Transachons System Man and Cybernetics,1996,26(1):29-41.
[12]Hedetniemi S,Liestman A.A survey of gossiping and broadcasting in communication networks[J].Networks,1998,18(4):319-349.
[13]Haas Z J,Halpem J Y,Li L.Gossip-based ad hoc routing[C].ha proceeding of the IEEE INFECOM,New York:IEEE Communications Society.2002,1707-1716.
[14]Kulik J,Hemelman W,Balakrishman H.Negotiation based protocols for disseminating information in wireless sensor networks[J].Wireless Networks,2002,8(2-3):169-185.
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