基于跨层的无线传感器网络资源调度与路由算法研究
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摘要
无线传感器网络的路由选择和链路资源分配是一个联合优化问题,有效解决该问题的方法是采用联合物理层和数据链路层的跨层联合优化机制。由于无线传感器网路所具有的节点能量受限特性以及链路间干扰,使得实现这一目标成为条件受限的非线性优化问题。本文根据最大化效益理论,首先,对影响系统目标优化的分集特性理论进行了分析,其中包括:频率选择型分集、地点分集、时间分集以及成员节点队列分集。然后,针对无线传感器网络系统采用自组织分群的管理机制所需涉及的资源分配和路由节点选择问题,利用最大系统效益函数建立了联合路由选择和链路资源分配的跨层优化模型,并对优化过程中需要解决的几个关键性问题,提出了针对性有效实现算法。
通过系统性的整体分析可以得出:由于路由链路传输性能决定于链路信道的质量,因此,无线传感器网络中的路由链路建立及链路资源调度问题具有相互影响特点。根据最大系统效益理论,建立了基于最大总体效益函数值的系统资源优化模型。利用效益函数,推导出有效的相关因素数学关系计算方程。此外,设计了能够实现路由链路资源分配公平性的效益函数集,改善了系统资源调度整体性能。该系统模型的建立为后续问题的解决提供了理论分析依据。
根据有向图理论,对无线传感器网络中的实现有效路由选择机制的具体解决方法进行了分析。针对该问题所需要的资源利用有效性问题,在节点能量受限条件下,提出了一种基于联合物理层和数据链路层的跨层资源分配方案,并设计了基于局部分群管理的路由机制。采用所提出的分群路由管理方式,极大地减少了每个群内的成员节点数据计算和传输任务(包括路由选择)所需的资源开销,较大程度的减少了大量成员节点的负载量,有效降低了成员节点能耗,在不同的网络负载状态下,都能够使系统具有较高的资源分配有效性。
针对基于OFDM接入的无线传感器网络路由链路频率调度问题,理论分析了影响系统优化模型实现的两个主要因素:同频链路干扰分集和成员节点队列分集。根据理论分析结果,提出了一个动态子载波分配算法。通过对同频链路干扰因素的时间分布相关性预测,该算法确定了有效分配子载波的统计周期间隔,能够为OFDM无线传感器网络群内成员节点提供较好的路由链路传输性能。
时变的同频链路间干扰导致了链路的不稳定性,使采用子载波复用的OFDM无线传感器网络系统容量最大化问题具有较高的实现复杂度。为解决该问题,通过对基于时间失效的自动放弃策略和基于信噪比淹没的自动放弃策略进行研究,提出了一种基于启发式搜索的子载波分配算法(DSA)。为进一步改进全局公平性,对DSA算法采取了全局公平性控制机制,提出了全局公平调度算法(GPCSA)。理论分析和仿真结果证明:这两个算法能够极大地改善系统传输有效性和公平性。
通过数学建模分析以及仿真测试,以上提出的算法,在一定的系统状态下,能够使系统资源的调度和路由链路选择得到优化,进一步改进了系统资源的有效性与公平性。
Routing selection and resource allocation over links in wireless sensor networks is a combination optimization problem. The method to solve it effectively is to adopt the cross layer optimization by combining physical layer and data link layer. In addition, since there exist the limited energy in nodes and the interference among links, it becomes a optimization problem with constraints to achieve the optimization objective. According to the maximization utility theory, first, we analyze the diversity characteristic affecting the system optimization, including frequency selection diversity, location diversity, the time diversity and queue diversity of member nodes. Then, considering resource allocation and routing node selection required by the management mechanism based on self-clustering in wireless sensor networks, we establish the cross optimization model by the combination of routing selection and resource allocation over links accordant to the system utility maximization and propose efficient algorithms for several key problems needed during the optimization implementation.
After analyzing the performance of the system, we conclude that since the routing transmission performance depends on the channel quality of the link, it leads to the effect between selecting routing links and resource scheduling over links. By the utility function, we derive the efficient computation model for the correlative factors. The optimization model for system resource is formulated based on the maximization value of the total utility. Additionally, we design the set of utility function capable of achieving the fairness of resource allocation among links, as a result, improving the total performance of resource scheduling. The optimization model provides the theory analysis evidence for the problems needed to solve behind.
The implementation methods to achieve the effective routing selection are analyzed by directed graph theory. For the efficient resource allocation required by the problem, we propose a resource allocation scheme based on the combination of physical layer and data link layer using cross layer mechanism and design the routing mechanism based on local clustering. The resource overhead needed by the data transmission of member nodes within each cluster is significantly decreased by the proposed the management method using the routing based on clustering, with the large numbers of load decrease and the efficiently decreased energy consumption of member nodes. The higher performance of resource allocation is achieved under different system loads.
In order to solve the problem caused by scheduling frequency over routing links in OFDM wireless sensor networks, we analyze two key factors, interference among routing links using the same frequency width that affect the optimization of system model. A scheme for dynamic subcarrier allocation is proposed according to the theory analysis. Through predicting interference factors among the links using the same frequency width, we determine the statistical period for efficient subcarrier allocation, which provide the better transmission performance over routing links in OFDM wireless sensor networks.
Time-varying co-channel interference results in the instability of link condition, which leads to the higher complexity of the system capacity maximization in OFDM wireless sensor networks using the reuse of subcarrier. To solve it, we present a subcarrier allocation algorithm (DSA) based on heuristic searching mechanism after investigating automatic quitting due to time expiring and automatic quitting due to the higher level of signal to noise ratio. Applying the. global fairness control to DSA, we propose a global fairness scheduling algorithm (GPCSA). It is demonstrated by theory analysis and simulation results that DSA and GPCSA improve the efficiency and fairness of transmission respectively.
Using the mathematic model analysis and simulation measurement, we obtain the improved efficiency and fairness of system performance and the further optimized resource scheduling and routing link selection under some system conditions.
通过系统性的整体分析可以得出:由于路由链路传输性能决定于链路信道的质量,因此,无线传感器网络中的路由链路建立及链路资源调度问题具有相互影响特点。根据最大系统效益理论,建立了基于最大总体效益函数值的系统资源优化模型。利用效益函数,推导出有效的相关因素数学关系计算方程。此外,设计了能够实现路由链路资源分配公平性的效益函数集,改善了系统资源调度整体性能。该系统模型的建立为后续问题的解决提供了理论分析依据。
根据有向图理论,对无线传感器网络中的实现有效路由选择机制的具体解决方法进行了分析。针对该问题所需要的资源利用有效性问题,在节点能量受限条件下,提出了一种基于联合物理层和数据链路层的跨层资源分配方案,并设计了基于局部分群管理的路由机制。采用所提出的分群路由管理方式,极大地减少了每个群内的成员节点数据计算和传输任务(包括路由选择)所需的资源开销,较大程度的减少了大量成员节点的负载量,有效降低了成员节点能耗,在不同的网络负载状态下,都能够使系统具有较高的资源分配有效性。
针对基于OFDM接入的无线传感器网络路由链路频率调度问题,理论分析了影响系统优化模型实现的两个主要因素:同频链路干扰分集和成员节点队列分集。根据理论分析结果,提出了一个动态子载波分配算法。通过对同频链路干扰因素的时间分布相关性预测,该算法确定了有效分配子载波的统计周期间隔,能够为OFDM无线传感器网络群内成员节点提供较好的路由链路传输性能。
时变的同频链路间干扰导致了链路的不稳定性,使采用子载波复用的OFDM无线传感器网络系统容量最大化问题具有较高的实现复杂度。为解决该问题,通过对基于时间失效的自动放弃策略和基于信噪比淹没的自动放弃策略进行研究,提出了一种基于启发式搜索的子载波分配算法(DSA)。为进一步改进全局公平性,对DSA算法采取了全局公平性控制机制,提出了全局公平调度算法(GPCSA)。理论分析和仿真结果证明:这两个算法能够极大地改善系统传输有效性和公平性。
通过数学建模分析以及仿真测试,以上提出的算法,在一定的系统状态下,能够使系统资源的调度和路由链路选择得到优化,进一步改进了系统资源的有效性与公平性。
Routing selection and resource allocation over links in wireless sensor networks is a combination optimization problem. The method to solve it effectively is to adopt the cross layer optimization by combining physical layer and data link layer. In addition, since there exist the limited energy in nodes and the interference among links, it becomes a optimization problem with constraints to achieve the optimization objective. According to the maximization utility theory, first, we analyze the diversity characteristic affecting the system optimization, including frequency selection diversity, location diversity, the time diversity and queue diversity of member nodes. Then, considering resource allocation and routing node selection required by the management mechanism based on self-clustering in wireless sensor networks, we establish the cross optimization model by the combination of routing selection and resource allocation over links accordant to the system utility maximization and propose efficient algorithms for several key problems needed during the optimization implementation.
After analyzing the performance of the system, we conclude that since the routing transmission performance depends on the channel quality of the link, it leads to the effect between selecting routing links and resource scheduling over links. By the utility function, we derive the efficient computation model for the correlative factors. The optimization model for system resource is formulated based on the maximization value of the total utility. Additionally, we design the set of utility function capable of achieving the fairness of resource allocation among links, as a result, improving the total performance of resource scheduling. The optimization model provides the theory analysis evidence for the problems needed to solve behind.
The implementation methods to achieve the effective routing selection are analyzed by directed graph theory. For the efficient resource allocation required by the problem, we propose a resource allocation scheme based on the combination of physical layer and data link layer using cross layer mechanism and design the routing mechanism based on local clustering. The resource overhead needed by the data transmission of member nodes within each cluster is significantly decreased by the proposed the management method using the routing based on clustering, with the large numbers of load decrease and the efficiently decreased energy consumption of member nodes. The higher performance of resource allocation is achieved under different system loads.
In order to solve the problem caused by scheduling frequency over routing links in OFDM wireless sensor networks, we analyze two key factors, interference among routing links using the same frequency width that affect the optimization of system model. A scheme for dynamic subcarrier allocation is proposed according to the theory analysis. Through predicting interference factors among the links using the same frequency width, we determine the statistical period for efficient subcarrier allocation, which provide the better transmission performance over routing links in OFDM wireless sensor networks.
Time-varying co-channel interference results in the instability of link condition, which leads to the higher complexity of the system capacity maximization in OFDM wireless sensor networks using the reuse of subcarrier. To solve it, we present a subcarrier allocation algorithm (DSA) based on heuristic searching mechanism after investigating automatic quitting due to time expiring and automatic quitting due to the higher level of signal to noise ratio. Applying the. global fairness control to DSA, we propose a global fairness scheduling algorithm (GPCSA). It is demonstrated by theory analysis and simulation results that DSA and GPCSA improve the efficiency and fairness of transmission respectively.
Using the mathematic model analysis and simulation measurement, we obtain the improved efficiency and fairness of system performance and the further optimized resource scheduling and routing link selection under some system conditions.
引文
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