无线网络中的鲁棒性资源分配算法研究
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摘要
在过去的数十年中,人们对于随时随地与一切事物进行交互的梦想驱动着无线网络技术持续地蓬勃发展。为了以更低的成本和能耗提供更广阔的无线网络接入范围,基于无线多跳转发结构的网络如无线传感器网络、无线mesh网络和移动ad-hoc网络等成为当前的研究热点。然而网络中存在多种动态因素,如电池能量损耗、链路质量变化以及拓扑的随机性等,使得目前的无线多跳网络还难以提供稳定的服务质量。为了满足实际应用的需要,在动态环境下提高无线多跳网络的鲁棒性成为重要的技术挑战。在本文中我们分析导致无线传感器网络和无线mesh网络鲁棒性不足的主要原因,并针对性地采用拓扑控制、多接口多信道以及机会式路由三种技术手段进行网络鲁棒性优化。本论文的结构如下：
首先,我们考虑节点位置信息未知的无线传感器网络。要提高其鲁棒性,就要在能量受限的条件下令网络尽量长时间地保证连通性并满足覆盖强度需求。对此我们提出了一种名为自适应随机分簇(ARC)的拓扑控制算法,该算法可以在满足连通覆盖性能需求的前提下减少节点总体能量消耗并有效达到节点间能耗平衡。ARC算法采用了一种创新的簇头选举制度在网络中形成一个分簇拓扑,并可以避免各个簇内部的数据传输发生互相干扰。ARC通过调整簇内节点的唤醒门限自适应地满足覆盖强度需求,并通过设置适当的簇内通讯和簇间通讯发送功率来保证网络的连通性。仿真结果表明ARC可以效达到网络的连通覆盖性能要求,并显著延长网络寿命。
其次我们对于给定端到端流量需求的无线mesh网络利用多接口多信道技术进行鲁棒性优化。为了表征网络对抗信道变化和外部干扰的能力,我们结合了干扰裕量和中断概率的概念提出了鲁棒性度量。根据实际的接口切换、速率选择和多径路由模型,我们将网络的鲁棒性资源分配建立为一个混合整形非线性规划问题。为了降低问题的复杂度,我们首先将该问题进行分解并得到一个可行性检测问题,然后通过二元搜索算法对于可行性检测问题进行迭代求解以得到原问题的最优解。用试验床得到的实测信道变化数据进行仿真,我们验证了所提出的算法能够在有信道变化和外部干扰的环境中有效维持链路的鲁棒性。
接着我们对采用机会式路由结合网络编码的无线mesh网络进行研究,指出这种场景下网络的鲁棒性主要受到网络编码数据包相关性的影响。对此我们提出了转发节点流量控制的一组约束以减少节点收到的相关数据包数量,并将鲁棒性流量控制建立为一个非凸优化问题。我们通过一种集中式算法和一种分布式算法对原问题进行简化,其中前者只保留一部分关键的流量控制约束条件以降低问题复杂度,而后者则可以根据周围链路质量变化在本地自适应地运行。仿真结果表明相对已有算法,我们提出的算法在各种不同的网络拓扑中都可以更好地限制目的节点接收到相关数据包的概率并提高端到端有效吞吐量。
最后我们总结了本文的内容并展望了鲁棒性优化技术的未来研究方向。
In the past decades, the dream of interconnecting every thing, everywhere, all the time has driven the fast development of wireless networking technologies. To extend the network access range with reduced cost and energy consumption, networks with multi-hop wireless networking structure have been proposed for some specific applications, such as wireless sensor networks, wireless mesh networks and mobile ad-hoc networks. However, current wireless multi-hop net-works are still inadequate to provide guaranteed quality of service (QoS) due to various dynamic factors, such as battery exhaustion, channel dynamics, external interference and topology diver-sity. Therefore, how to improve the robustness of wireless multi-hop networks in the dynamic environments is a challenging issue for wireless network practitioners. In this work, we analyze the main causes of robustness deficiency in wireless sensor networks and wireless mesh network-s, and propose corresponding solutions with different technologies including topology control, multi-radio multi-channel and resource allocation, and opportunistic routing. The contents of this thesis are organized as follows.
Firstly, we consider wireless sensor networks where the location information of each sen-sor node is unknown. To improve the robustness of wireless sensor network, the main task is to ensure the network connectivity and guarantee the required coverage intensity as long as pos-sible with limited energy. To this end, we propose a topology control algorithm called adaptive random clustering (ARC), which can reduce the overall energy consumption and balance the energy usage among nodes while preserving the performance requirement. ARC forms a cluster topology using a novel cluster head competition scheme so as to provide contention free intra-cluster communication. The required coverage is achieved by adjusting the activation threshold of non-cluster-head node adaptively, and the connectivity is guaranteed by proper inter-cluster and intra-cluster transmit power control. Simulation results demonstrate that the required cover-age and connectivity can be guaranteed and the network lifetime is prolonged significantly.
Secondly, assuming multiple radios and channels are available for the network, we attempt to improve the robustness of wireless mesh networks where the end-to-end traffic demands are specified. The concepts of interference margin and outage probability are incorporated to char-acterize the network robustness under channel variations and external interference. We formu-late the robust resource allocation problems as mixed integer nonlinear programming (MINLP) problems by explicitly taking into account practical radio switching, co-channel contention and multi-path routing constraints. To reduce the complexity, we exploit the special properties of the problems and decompose them into the feasibility-checking problems, and propose a bina-ry search algorithm to find the optimal solutions of the problems using an iterative procedure. By simulations using traces collected from an indoor wireless testbed, we show that our algo-rithms are more robust to the existing schemes under moderate channel variations and external interference.
Thirdly, we consider the wireless mesh networks adopting both opportunistic routing and network coding techniques. We demonstrate that the robustness deficiency in this case is main-ly due to the dependency of network coding packets. We then propose a set of flow control constraints to alleviate the performance degradation caused by this problem, and formulate the robust flow control problem as a nonconvex optimization problem by taking into account of these constraints. To reduce the complexity of the problem, we propose a centralized algorithm which only considers the primary flow control constraints of the original problem, and a full distribu-tive algorithm which can operate adaptively according to the variation of link quality. Simulation results are provided to show that the proposed algorithms are superior to existing algorithms in reducing the packet dependency ratio and improving the goodput in both grid and random topology settings.
Finally we conclude this thesis and suggest the directions for future research.
首先,我们考虑节点位置信息未知的无线传感器网络。要提高其鲁棒性,就要在能量受限的条件下令网络尽量长时间地保证连通性并满足覆盖强度需求。对此我们提出了一种名为自适应随机分簇(ARC)的拓扑控制算法,该算法可以在满足连通覆盖性能需求的前提下减少节点总体能量消耗并有效达到节点间能耗平衡。ARC算法采用了一种创新的簇头选举制度在网络中形成一个分簇拓扑,并可以避免各个簇内部的数据传输发生互相干扰。ARC通过调整簇内节点的唤醒门限自适应地满足覆盖强度需求,并通过设置适当的簇内通讯和簇间通讯发送功率来保证网络的连通性。仿真结果表明ARC可以效达到网络的连通覆盖性能要求,并显著延长网络寿命。
其次我们对于给定端到端流量需求的无线mesh网络利用多接口多信道技术进行鲁棒性优化。为了表征网络对抗信道变化和外部干扰的能力,我们结合了干扰裕量和中断概率的概念提出了鲁棒性度量。根据实际的接口切换、速率选择和多径路由模型,我们将网络的鲁棒性资源分配建立为一个混合整形非线性规划问题。为了降低问题的复杂度,我们首先将该问题进行分解并得到一个可行性检测问题,然后通过二元搜索算法对于可行性检测问题进行迭代求解以得到原问题的最优解。用试验床得到的实测信道变化数据进行仿真,我们验证了所提出的算法能够在有信道变化和外部干扰的环境中有效维持链路的鲁棒性。
接着我们对采用机会式路由结合网络编码的无线mesh网络进行研究,指出这种场景下网络的鲁棒性主要受到网络编码数据包相关性的影响。对此我们提出了转发节点流量控制的一组约束以减少节点收到的相关数据包数量,并将鲁棒性流量控制建立为一个非凸优化问题。我们通过一种集中式算法和一种分布式算法对原问题进行简化,其中前者只保留一部分关键的流量控制约束条件以降低问题复杂度,而后者则可以根据周围链路质量变化在本地自适应地运行。仿真结果表明相对已有算法,我们提出的算法在各种不同的网络拓扑中都可以更好地限制目的节点接收到相关数据包的概率并提高端到端有效吞吐量。
最后我们总结了本文的内容并展望了鲁棒性优化技术的未来研究方向。
In the past decades, the dream of interconnecting every thing, everywhere, all the time has driven the fast development of wireless networking technologies. To extend the network access range with reduced cost and energy consumption, networks with multi-hop wireless networking structure have been proposed for some specific applications, such as wireless sensor networks, wireless mesh networks and mobile ad-hoc networks. However, current wireless multi-hop net-works are still inadequate to provide guaranteed quality of service (QoS) due to various dynamic factors, such as battery exhaustion, channel dynamics, external interference and topology diver-sity. Therefore, how to improve the robustness of wireless multi-hop networks in the dynamic environments is a challenging issue for wireless network practitioners. In this work, we analyze the main causes of robustness deficiency in wireless sensor networks and wireless mesh network-s, and propose corresponding solutions with different technologies including topology control, multi-radio multi-channel and resource allocation, and opportunistic routing. The contents of this thesis are organized as follows.
Firstly, we consider wireless sensor networks where the location information of each sen-sor node is unknown. To improve the robustness of wireless sensor network, the main task is to ensure the network connectivity and guarantee the required coverage intensity as long as pos-sible with limited energy. To this end, we propose a topology control algorithm called adaptive random clustering (ARC), which can reduce the overall energy consumption and balance the energy usage among nodes while preserving the performance requirement. ARC forms a cluster topology using a novel cluster head competition scheme so as to provide contention free intra-cluster communication. The required coverage is achieved by adjusting the activation threshold of non-cluster-head node adaptively, and the connectivity is guaranteed by proper inter-cluster and intra-cluster transmit power control. Simulation results demonstrate that the required cover-age and connectivity can be guaranteed and the network lifetime is prolonged significantly.
Secondly, assuming multiple radios and channels are available for the network, we attempt to improve the robustness of wireless mesh networks where the end-to-end traffic demands are specified. The concepts of interference margin and outage probability are incorporated to char-acterize the network robustness under channel variations and external interference. We formu-late the robust resource allocation problems as mixed integer nonlinear programming (MINLP) problems by explicitly taking into account practical radio switching, co-channel contention and multi-path routing constraints. To reduce the complexity, we exploit the special properties of the problems and decompose them into the feasibility-checking problems, and propose a bina-ry search algorithm to find the optimal solutions of the problems using an iterative procedure. By simulations using traces collected from an indoor wireless testbed, we show that our algo-rithms are more robust to the existing schemes under moderate channel variations and external interference.
Thirdly, we consider the wireless mesh networks adopting both opportunistic routing and network coding techniques. We demonstrate that the robustness deficiency in this case is main-ly due to the dependency of network coding packets. We then propose a set of flow control constraints to alleviate the performance degradation caused by this problem, and formulate the robust flow control problem as a nonconvex optimization problem by taking into account of these constraints. To reduce the complexity of the problem, we propose a centralized algorithm which only considers the primary flow control constraints of the original problem, and a full distribu-tive algorithm which can operate adaptively according to the variation of link quality. Simulation results are provided to show that the proposed algorithms are superior to existing algorithms in reducing the packet dependency ratio and improving the goodput in both grid and random topology settings.
Finally we conclude this thesis and suggest the directions for future research.
引文
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