无线传感器网络拓扑控制与优化研究
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摘要
无线传感器网络是当前信息技术领域的一个热点研究方向，可用于军事侦察、环境监测、城市交通管理、仓储管理等军事和民用领域。在影响无线传感器网络性能的众多因素之中，拓扑控制是核心问题之一，因此如何优化网络拓扑结构、增强网络拓扑的自适应性和鲁棒性，并为上层通信协议提供良好的底层拓扑支撑是拓扑控制与优化研究的重要问题。本文对无线传感器网络拓扑控制与优化进行了研究，所取得的主要研究成果为：
1.合适的节点发射功率是保证网络连通性和覆盖度，延长网络生命周期的重要保证。为了寻求最优的发射功率，在保证网络通信连通的同时优化拓扑结构，本文提出了一种基于非合作博弈的无线传感器网络功率控制算法。该算法将节点的功率控制抽象为一个多人的非合作博弈过程，通过节点间的博弈进行功率控制。算法在设计功率控制的支付函数时充分考虑了节点剩余能量的因素，通过选择合适的效用因子及价格因子组合能有效地优化网络中各节点的发射功率，降低网络的总发射功率，从而节约节点能量。此外，本文还求出了功率控制博弈的纳什均衡点，并证明了纳什均衡的存在性和唯一性。仿真结果表明了算法具有很好的收敛性，通过功率控制能有效地优化网络拓扑结构，延长网络的生命周期。
2.合理有效的分簇是节约能量，优化无线传感器网络拓扑的关键。针对该问题，本文提出了一种基于贝叶斯博弈的无线传感器网络分簇算法。算法将无线传感器网络节点的簇头选举抽象为一个多人的博弈过程，节点之间通过不完全信息的静态博弈进行簇头选举。算法在贝叶斯分簇的支付函数设计时充分考虑了节点能耗和路径损耗等因素，因此通过节点间的贝叶斯博弈能实现簇头的合理分布，在优化网络拓扑的同时可使网络能耗更加稳定、能量分布更加均匀，有效地延长网络生命周期。
3.部署对网络拓扑构成和网络布局优化都有重要的影响，针对无线传感器网络中传统网络部署方法不能很好地适应动态网络环境，存在监测盲区的问题。本文提出了一种基于模糊控制的无线传感器网络部署优化算法。算法将模糊控制策略用于无线传感器网络的节点部署中，通过对移动节点的移动距离和移动方向进行模糊控制实现节点的合理部署，以提高网络的覆盖率。由于在模糊控制规则的设计中充分考虑了节点剩余能量、节点路径损耗、节点邻居数等因素，因此该算法能有效提高网络覆盖率，使网络拓扑结构更加健全完善，延长网络生命周期。
4.构建高可靠性和高抗毁性的拓扑结构是无线传感器网络面临的新问题。针对该问题，本文分别提出了两种基于无标度网络的拓扑演化算法。在基于能量有效的无标度传感器网络拓扑演化算法中，算法首先通过分簇实现簇头的合理分布，然后按照无标度网络随机行走的方式进行簇头间的拓扑演化。由于在拓扑演化过程中充分考虑了节点剩余能量、节点度等因素。因此演化后的网络拓扑具有较好的负载均衡和能量均衡，适于无线传感器网络的实际应用；在具有重构机制的无标度传感器网络拓扑演化算法中，算法首先通过分簇实现簇头的合理分布，然后根据无线传感器网络实际应用中随机加点、随机去点、随机去边和重连的方式进行簇头间的拓扑演化。由于在拓扑演化时引入了重构机制，并且考虑了节点和链路变化的随机性问题，因此演化的网络拓扑具有很好的自愈性、重构性和可调性。仿真结果表明，利用上述两种算法演化的网络拓扑在随机和蓄意打击下都具有较高的鲁棒性，可满足恶劣环境对无线传感器网络鲁棒性的要求。
5.针对无线传感器网络中如何判断节点重要性的问题，本文提出了一种基于拓扑贡献和能量有效的无线传感器网络节点重要性评价方法。该方法首先综合考虑网络拓扑结构和网络能耗之间的关系，设计了一种测度网络拓扑抗毁性和网络能耗的综合评价指标；其次在该评价指标的基础上设计了无线传感器网络节点重要性评价算法。仿真结果表明了该评价方法的合理性和有效性，利用该评价方法能有效地判断网络中重要节点的位置，通过对重要节点的保护能有效地优化网络拓扑结构，增强网络抗毁性。此外，本文还对在网络中加入超级节点实现重要节点的保护问题进行了研究。
The wireless senor networks (WSNs) have been hot research area over recent yearsdue to their promising applications in environment monitoring, battlefield surveillance,traffic and warehouse managements. Topology control is one of the core issues in WSNs.A well-designed network topology not only provides a good underlying topologysupport for upper layer protocols, but also helps improve the robustness and adaptivityof the network. Therefore how to optimize the network topology is of great significance.Topology control and optimization issues are studied in this dissertation, with specificstudies as follows:
1. Suitable transmission power plays a crucial role in ensuring networkconnectivity, network coverage and prolonging network lifetime. In this dissertation, wepropose a non-cooperative game-based power control algorithm which determines theoptimal transmit power while ensuring network connectivity. The power controloptimization is cast as strategic non-cooperative games, where each sensor node is aplayer that competes against the others in resource allocation to maximize its ownpayoff function. Residual energy of each node is taken into account when designing thepayoff function. By selecting a proper utility factor and a price factor, the algorithm canconsiderably reduce the total transmit power, and thus save the network’s energy. Inaddition, the nash equilibrium is found, with its existence and uniqueness proved.Simulation results show that the proposed power control algorithm has a goodconvergence property, and can effectively prolong the network lifetime and provide awell-designed network topology.
2. Effective clustering is important to the optimization of the network topologyand to the energy saving. In this dissertation, we propose a bayesian game-basedclustering algorithm. In the algorithm, the election of the cluster head is modeled as amulti-player game, in which the cluster head is elected through static games withincomplete information. The node energy consumption and the path loss are fully takeninto our consideration when designing the payoff function. Hence the algorithm canprovide a more reasonable distribution of the cluster heads, a more stable energyconsumption and a more uniform energy distribution with the optimization of networktopology. As a consequence, the network lifetime can be prolonged considerably.
3. Node deployment strategy is one of the key issues in network topology control.Traditional node deployment strategies cannot well adapt to the dynamic networkenvironment and suffer from blind spot area. To overcome these difficulties, weintroduce a fuzzy control strategy for node deployment. Through fuzzy control of themovement distance and direction, the proposed node deployment strategy provides areasonable deployment of the nodes and improves the network coverage. Since theresidual energy, path loss and the number of neighbors are considered in the design offuzzy control rules, the algorithm can effectively improve network coverage, makenetwork topology more perfect and prolong network lifetime.
4. Constructing a topological structure that has a high reliability and highsurvivability is a challenging and new problem in WSNs. Two topology evolutionalgorithms are proposed based on scale-free network topologies.1) A energy-efficienttopology evolution algorithm based on scale-free network topologies is introduced. Thealgorithm first achieves a reasonable distribution of the cluster heads, and then thetopology evolves via scale-free network random walks. Since residual energy, nodedegree and other factors are sufficiently considered during the topology evolution, thefinally obtained topology has an acceptable load and a good energy balance, thus issuitable for the practical application of WSNs;2) Topology evolution algorithm withreconstruction mechanism based on scale-free network topology is proposed. Thealgorithm first achieve a reasonable distribution of cluster heads, then the topologyevolves considering those factors arising from practical requirements, such as randomnode addition or deletion, and edge deletion or reconstruction. During the evolution ofthe topology, the random failures of nodes or links are fully considered, and thereconstruction mechanism is introduced. Therefore the network topologies haveattractive quality such as self-healing ability, reconstruction ability and adjustability.Simulation results demonstrate that network topologies generated by the above twoalgorithms both have high robustness under random, deliberate attacks and can meet therequirements under harsh environmental conditions in WSNs.
5. We considered the problem of evaluating node importance in WSNs. Anevaluation method is proposed in this dissertation based on topology contributions andenergy effectiveness. Firstly, by examining the relationship between topology structureand energy consumptions, we design a comprehensive evaluation index that is able tomeasure the topology invulnerability and energy consumptions. Secondly, a nodeimportance evaluation algorithm is designed based on the evaluation index. Simulation results show that the index is rational and effective, important nodes are effectivelylocated, network topology is optimized and network survivability is enhanced withimportant nodes being protected. Furthermore, we also discuss how to protect importantnodes through adding super nodes to the network.
1.合适的节点发射功率是保证网络连通性和覆盖度，延长网络生命周期的重要保证。为了寻求最优的发射功率，在保证网络通信连通的同时优化拓扑结构，本文提出了一种基于非合作博弈的无线传感器网络功率控制算法。该算法将节点的功率控制抽象为一个多人的非合作博弈过程，通过节点间的博弈进行功率控制。算法在设计功率控制的支付函数时充分考虑了节点剩余能量的因素，通过选择合适的效用因子及价格因子组合能有效地优化网络中各节点的发射功率，降低网络的总发射功率，从而节约节点能量。此外，本文还求出了功率控制博弈的纳什均衡点，并证明了纳什均衡的存在性和唯一性。仿真结果表明了算法具有很好的收敛性，通过功率控制能有效地优化网络拓扑结构，延长网络的生命周期。
2.合理有效的分簇是节约能量，优化无线传感器网络拓扑的关键。针对该问题，本文提出了一种基于贝叶斯博弈的无线传感器网络分簇算法。算法将无线传感器网络节点的簇头选举抽象为一个多人的博弈过程，节点之间通过不完全信息的静态博弈进行簇头选举。算法在贝叶斯分簇的支付函数设计时充分考虑了节点能耗和路径损耗等因素，因此通过节点间的贝叶斯博弈能实现簇头的合理分布，在优化网络拓扑的同时可使网络能耗更加稳定、能量分布更加均匀，有效地延长网络生命周期。
3.部署对网络拓扑构成和网络布局优化都有重要的影响，针对无线传感器网络中传统网络部署方法不能很好地适应动态网络环境，存在监测盲区的问题。本文提出了一种基于模糊控制的无线传感器网络部署优化算法。算法将模糊控制策略用于无线传感器网络的节点部署中，通过对移动节点的移动距离和移动方向进行模糊控制实现节点的合理部署，以提高网络的覆盖率。由于在模糊控制规则的设计中充分考虑了节点剩余能量、节点路径损耗、节点邻居数等因素，因此该算法能有效提高网络覆盖率，使网络拓扑结构更加健全完善，延长网络生命周期。
4.构建高可靠性和高抗毁性的拓扑结构是无线传感器网络面临的新问题。针对该问题，本文分别提出了两种基于无标度网络的拓扑演化算法。在基于能量有效的无标度传感器网络拓扑演化算法中，算法首先通过分簇实现簇头的合理分布，然后按照无标度网络随机行走的方式进行簇头间的拓扑演化。由于在拓扑演化过程中充分考虑了节点剩余能量、节点度等因素。因此演化后的网络拓扑具有较好的负载均衡和能量均衡，适于无线传感器网络的实际应用；在具有重构机制的无标度传感器网络拓扑演化算法中，算法首先通过分簇实现簇头的合理分布，然后根据无线传感器网络实际应用中随机加点、随机去点、随机去边和重连的方式进行簇头间的拓扑演化。由于在拓扑演化时引入了重构机制，并且考虑了节点和链路变化的随机性问题，因此演化的网络拓扑具有很好的自愈性、重构性和可调性。仿真结果表明，利用上述两种算法演化的网络拓扑在随机和蓄意打击下都具有较高的鲁棒性，可满足恶劣环境对无线传感器网络鲁棒性的要求。
5.针对无线传感器网络中如何判断节点重要性的问题，本文提出了一种基于拓扑贡献和能量有效的无线传感器网络节点重要性评价方法。该方法首先综合考虑网络拓扑结构和网络能耗之间的关系，设计了一种测度网络拓扑抗毁性和网络能耗的综合评价指标；其次在该评价指标的基础上设计了无线传感器网络节点重要性评价算法。仿真结果表明了该评价方法的合理性和有效性，利用该评价方法能有效地判断网络中重要节点的位置，通过对重要节点的保护能有效地优化网络拓扑结构，增强网络抗毁性。此外，本文还对在网络中加入超级节点实现重要节点的保护问题进行了研究。
The wireless senor networks (WSNs) have been hot research area over recent yearsdue to their promising applications in environment monitoring, battlefield surveillance,traffic and warehouse managements. Topology control is one of the core issues in WSNs.A well-designed network topology not only provides a good underlying topologysupport for upper layer protocols, but also helps improve the robustness and adaptivityof the network. Therefore how to optimize the network topology is of great significance.Topology control and optimization issues are studied in this dissertation, with specificstudies as follows:
1. Suitable transmission power plays a crucial role in ensuring networkconnectivity, network coverage and prolonging network lifetime. In this dissertation, wepropose a non-cooperative game-based power control algorithm which determines theoptimal transmit power while ensuring network connectivity. The power controloptimization is cast as strategic non-cooperative games, where each sensor node is aplayer that competes against the others in resource allocation to maximize its ownpayoff function. Residual energy of each node is taken into account when designing thepayoff function. By selecting a proper utility factor and a price factor, the algorithm canconsiderably reduce the total transmit power, and thus save the network’s energy. Inaddition, the nash equilibrium is found, with its existence and uniqueness proved.Simulation results show that the proposed power control algorithm has a goodconvergence property, and can effectively prolong the network lifetime and provide awell-designed network topology.
2. Effective clustering is important to the optimization of the network topologyand to the energy saving. In this dissertation, we propose a bayesian game-basedclustering algorithm. In the algorithm, the election of the cluster head is modeled as amulti-player game, in which the cluster head is elected through static games withincomplete information. The node energy consumption and the path loss are fully takeninto our consideration when designing the payoff function. Hence the algorithm canprovide a more reasonable distribution of the cluster heads, a more stable energyconsumption and a more uniform energy distribution with the optimization of networktopology. As a consequence, the network lifetime can be prolonged considerably.
3. Node deployment strategy is one of the key issues in network topology control.Traditional node deployment strategies cannot well adapt to the dynamic networkenvironment and suffer from blind spot area. To overcome these difficulties, weintroduce a fuzzy control strategy for node deployment. Through fuzzy control of themovement distance and direction, the proposed node deployment strategy provides areasonable deployment of the nodes and improves the network coverage. Since theresidual energy, path loss and the number of neighbors are considered in the design offuzzy control rules, the algorithm can effectively improve network coverage, makenetwork topology more perfect and prolong network lifetime.
4. Constructing a topological structure that has a high reliability and highsurvivability is a challenging and new problem in WSNs. Two topology evolutionalgorithms are proposed based on scale-free network topologies.1) A energy-efficienttopology evolution algorithm based on scale-free network topologies is introduced. Thealgorithm first achieves a reasonable distribution of the cluster heads, and then thetopology evolves via scale-free network random walks. Since residual energy, nodedegree and other factors are sufficiently considered during the topology evolution, thefinally obtained topology has an acceptable load and a good energy balance, thus issuitable for the practical application of WSNs;2) Topology evolution algorithm withreconstruction mechanism based on scale-free network topology is proposed. Thealgorithm first achieve a reasonable distribution of cluster heads, then the topologyevolves considering those factors arising from practical requirements, such as randomnode addition or deletion, and edge deletion or reconstruction. During the evolution ofthe topology, the random failures of nodes or links are fully considered, and thereconstruction mechanism is introduced. Therefore the network topologies haveattractive quality such as self-healing ability, reconstruction ability and adjustability.Simulation results demonstrate that network topologies generated by the above twoalgorithms both have high robustness under random, deliberate attacks and can meet therequirements under harsh environmental conditions in WSNs.
5. We considered the problem of evaluating node importance in WSNs. Anevaluation method is proposed in this dissertation based on topology contributions andenergy effectiveness. Firstly, by examining the relationship between topology structureand energy consumptions, we design a comprehensive evaluation index that is able tomeasure the topology invulnerability and energy consumptions. Secondly, a nodeimportance evaluation algorithm is designed based on the evaluation index. Simulation results show that the index is rational and effective, important nodes are effectivelylocated, network topology is optimized and network survivability is enhanced withimportant nodes being protected. Furthermore, we also discuss how to protect importantnodes through adding super nodes to the network.
引文
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