无线Ad Hoc网络节点移动部署研究
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摘要
无线Ad Hoc网络是一种具有自组织、自配置、自愈合能力的无需任何固定设施支持的移动网络。Ad Hoc节点的随机移动性改变了网络的拓扑结构，影响了网络的性能。但是，通过控制的节点移动可以优化配置网络拓扑结构，提高链路的有效性，增强网络的连通性，平衡网络能量消耗。本文研究无线Ad Hoc网络节点部署问题，从传感器节点的覆盖，节点移动控制技术两方面进行论述，并讨论了Ad Hoc节点的定位问题，具体成果如下：
1.针对离散、不均匀分布的目标点覆盖问题，提出了一个传感器节点部署算法。首先，将这一问题用整数线性规划模型描述，通过启发式的方法确定近似最优解。在能够覆盖数目最多且未达到覆盖要求的目标点的位置部署传感器节点，然后，对已部署的传感器节点构造Steiner树，并在Steiner点位置添加新的传感器节点用以形成连通传感器网络。算法不仅能覆盖所有不均匀分布的目标点且部署的传感器节点能够形成连通的网络。
2.为了提高中继链路的可靠性，延长网络生存期，提出了不依赖位置信息的节点盲移动算法。算法一方面以最小化链路代价函数为目标搜索优化位置，当节点位于优化位置时，其与通信邻节点之间的传输消耗最小。另一方面，节点能够在不具备位置信息的情况下，根据接收信号强度的变化，在移动过程中自适应调节其移动的方向和移动的步长。
3.为了增强Ad Hoc网络的连通性，构建容许一个节点失效的两连通网络拓扑，提出了基于接收信号强度的单节点移动算法。算法以消除网络中的分割节点为目标，通过选择分割节点的邻节点中的一个节点进行移动。要求移动节点能够以最小能量消耗、最大程度地建立与目标连接节点之间的链路。算法不但能够在不具备位置信息的条件下，根据接收到的分割节点以及相关邻节点的信号强度确定节点移动的方向和距离，还能确保节点移动过程中，保留网络原有连通性。在单节点移动的基础上，通过增加移动节点，可进一步构造具有两连通性的网络拓扑。
4.针对节点定位问题，提出了基于测距的节点移动定位算法。节点分别测试其本地坐标系的x、y轴方向上邻节点信号功率，并将其转化为节点之间的距离，再由三边法计算得到邻节点在移动节点的本地坐标系下的位置坐标，然后通过矢量和运算将本地位置坐标统一为网络系统坐标系下的位置。节点移动改变位置信息后，更新位置矢量表，无需重新计算节点的位置，从而极大地减小了能量消耗的同时保证了定位的准确性。算法无需假设网络中提前布置少量的位置固定且位置信息已知的节点作为计算位置的参考节点，而是根据节点的本地信息计算节点的位置。
Wireless Ad Hoc network is a collection of wireless mobile nodes which is formedwithout the aid of fixed infrastructure, and the it is of self-organizing, self-configuringand self-healing. The mobility of nodes in Ad Hoc network can have a significant effecton the network topology, and will further influence the network performance. Therefore,the main research problems of movement control which deal with the optimization ofthe network topology can greatly enhance the link availability, improve the networkconnectivity and even balance the energy consumptions. In this dissertation, we discussthe problems of Ad Hoc networks in three aspects: the optimal configuration forconnected wireless sensor networks, bi-connected mobile Ad Hoc networks, and nodes’localization with node mobility. The main contributions are listed as follows:
1. A minimum number of sensor deployment algorithm for connected wirelesssensor network is proposed to cover the dispersed, non-uniform distributed targetpoints, as well as to establish a connected sensor network by the deployed sensors.When targets’ positions are available, the connected deployment problem is firstlyformulated as an integer linear program problem. And then a greedy algorithm isproposed to deploy sensors into the sub-regions where it covers maximized numberof un-covered targets. The algorithm runs iteratively until all the targets arecovered. Finally, a Steiner tree is constructed based on the already deployedsensors, and newly added sensor nodes are required at the Steiner points to connectthe deployed sensors.
2. To improve the reliability of network links and extend the network lifetime, ablind node movement algorithm is proposed. The algorithm is used for Ad Hocnodes without positions, so the optimal position of a relay node is defined as thepoint where the cost of related links is minimized. To reduce the transmittingconsumption, the moving node moves according to the signal strength receivedfrom its neighbors.
3. A single node movement to increase the network connectivity is proposed. Itaims to get rid of the cut vertex in the network while the ongoing applications arekept. One of the neighbors of a cut vertex which can build the link to the otherneighbor of the same cut vertex but in different part with minimized energyconsumption is selected to move. And node moves according to the signal strength received from its1-hop neighbors, the cut vertex and its counterpart. Based on thesingle node movement algorithm, more nodes which are neighbors of the cutvertex, are needed to move to increase the bi-connectivity rate. Similarly, One ofthe neighbors of a cut vertex is required to move with minimized energyconsumption at each time.
4. A node movement based localization algorithm is introduced for nodes whichlack of GPS. In static networks, a node firstly moves along the+x,+y axis, and its1-hop neighbors sample the signal strength from the moving node and convert eachvalue to the distance to the moving node. Position of the1-hop neighbors in localcoordinate system of the moving node can be calculated by trilateral rule, and thennodes positions in the network coordinate system are available according to thesum of position vectors. Since node postion changes with its moving, a data tableis required to reduce the energy consumption for re-computing and also ensure thelocation accuracy. There is no need to acquire the position using the anchor nodes.
1.针对离散、不均匀分布的目标点覆盖问题，提出了一个传感器节点部署算法。首先，将这一问题用整数线性规划模型描述，通过启发式的方法确定近似最优解。在能够覆盖数目最多且未达到覆盖要求的目标点的位置部署传感器节点，然后，对已部署的传感器节点构造Steiner树，并在Steiner点位置添加新的传感器节点用以形成连通传感器网络。算法不仅能覆盖所有不均匀分布的目标点且部署的传感器节点能够形成连通的网络。
2.为了提高中继链路的可靠性，延长网络生存期，提出了不依赖位置信息的节点盲移动算法。算法一方面以最小化链路代价函数为目标搜索优化位置，当节点位于优化位置时，其与通信邻节点之间的传输消耗最小。另一方面，节点能够在不具备位置信息的情况下，根据接收信号强度的变化，在移动过程中自适应调节其移动的方向和移动的步长。
3.为了增强Ad Hoc网络的连通性，构建容许一个节点失效的两连通网络拓扑，提出了基于接收信号强度的单节点移动算法。算法以消除网络中的分割节点为目标，通过选择分割节点的邻节点中的一个节点进行移动。要求移动节点能够以最小能量消耗、最大程度地建立与目标连接节点之间的链路。算法不但能够在不具备位置信息的条件下，根据接收到的分割节点以及相关邻节点的信号强度确定节点移动的方向和距离，还能确保节点移动过程中，保留网络原有连通性。在单节点移动的基础上，通过增加移动节点，可进一步构造具有两连通性的网络拓扑。
4.针对节点定位问题，提出了基于测距的节点移动定位算法。节点分别测试其本地坐标系的x、y轴方向上邻节点信号功率，并将其转化为节点之间的距离，再由三边法计算得到邻节点在移动节点的本地坐标系下的位置坐标，然后通过矢量和运算将本地位置坐标统一为网络系统坐标系下的位置。节点移动改变位置信息后，更新位置矢量表，无需重新计算节点的位置，从而极大地减小了能量消耗的同时保证了定位的准确性。算法无需假设网络中提前布置少量的位置固定且位置信息已知的节点作为计算位置的参考节点，而是根据节点的本地信息计算节点的位置。
Wireless Ad Hoc network is a collection of wireless mobile nodes which is formedwithout the aid of fixed infrastructure, and the it is of self-organizing, self-configuringand self-healing. The mobility of nodes in Ad Hoc network can have a significant effecton the network topology, and will further influence the network performance. Therefore,the main research problems of movement control which deal with the optimization ofthe network topology can greatly enhance the link availability, improve the networkconnectivity and even balance the energy consumptions. In this dissertation, we discussthe problems of Ad Hoc networks in three aspects: the optimal configuration forconnected wireless sensor networks, bi-connected mobile Ad Hoc networks, and nodes’localization with node mobility. The main contributions are listed as follows:
1. A minimum number of sensor deployment algorithm for connected wirelesssensor network is proposed to cover the dispersed, non-uniform distributed targetpoints, as well as to establish a connected sensor network by the deployed sensors.When targets’ positions are available, the connected deployment problem is firstlyformulated as an integer linear program problem. And then a greedy algorithm isproposed to deploy sensors into the sub-regions where it covers maximized numberof un-covered targets. The algorithm runs iteratively until all the targets arecovered. Finally, a Steiner tree is constructed based on the already deployedsensors, and newly added sensor nodes are required at the Steiner points to connectthe deployed sensors.
2. To improve the reliability of network links and extend the network lifetime, ablind node movement algorithm is proposed. The algorithm is used for Ad Hocnodes without positions, so the optimal position of a relay node is defined as thepoint where the cost of related links is minimized. To reduce the transmittingconsumption, the moving node moves according to the signal strength receivedfrom its neighbors.
3. A single node movement to increase the network connectivity is proposed. Itaims to get rid of the cut vertex in the network while the ongoing applications arekept. One of the neighbors of a cut vertex which can build the link to the otherneighbor of the same cut vertex but in different part with minimized energyconsumption is selected to move. And node moves according to the signal strength received from its1-hop neighbors, the cut vertex and its counterpart. Based on thesingle node movement algorithm, more nodes which are neighbors of the cutvertex, are needed to move to increase the bi-connectivity rate. Similarly, One ofthe neighbors of a cut vertex is required to move with minimized energyconsumption at each time.
4. A node movement based localization algorithm is introduced for nodes whichlack of GPS. In static networks, a node firstly moves along the+x,+y axis, and its1-hop neighbors sample the signal strength from the moving node and convert eachvalue to the distance to the moving node. Position of the1-hop neighbors in localcoordinate system of the moving node can be calculated by trilateral rule, and thennodes positions in the network coordinate system are available according to thesum of position vectors. Since node postion changes with its moving, a data tableis required to reduce the energy consumption for re-computing and also ensure thelocation accuracy. There is no need to acquire the position using the anchor nodes.
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