无线Mesh网路由与调度联合优化算法研究
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摘要
无线Mesh网WMNs（Wireless Mesh Networks）是一种从Ad Hoc网络发展而来的具有动态自组织、自愈性的无线多跳网络，是下一代无线网络的一种关键技术。无线Mesh网具有低成本，易敷设，组织形式及覆盖范围灵活的特点，近年来得到越来越广泛的应用。如何提高无线Mesh网的网络性能一直是当前的研究热点。本文在系统分析无线Mesh网络技术原理和研究现状的基础上，集中研究了无线Mesh网的路由及调度跨层联合优化算法，取得了以下具有创新性的研究成果：
1）针对时分复用（TDMA）模式下无线Mesh网的路由及调度的联合优化，在以最短系统调度时间为目标的跨层联合优化模型的基础上，提出了一种基于极大团搜索的最优算法。该算法通过极大团搜索列举网络中所有极大并发传输模式，使优化问题的模型得到简化，从而可以用线性规划的方法最小化系统调度时间，优化运算的速度得到了极大的提高。通过对比仿真实验表明，对比目前该类优化问题常用的列生成最优算法，优化运算时间缩短了99%以上。
2）对于较大规模的无线Mesh网，因为考虑链路无线干扰的前提下，其最大化吞吐量问题本质上是一个NP难问题，所以对其进行吞吐量的最优化计算存在计算时间较长的问题。根据无线Mesh回程网的流量汇聚的特点，本文提出了一种基于链路权重分类的快速启发式算法，首先由各条链路在流量传输中的重要性对其分类并赋予不同的权重值，对含有较大权重链路的极大并发传输模式以较大的概率选出。然后，通过建立起极大并发模式的搜索次数与优化结果之间的有效联系，使得该算法的收敛特性得到保证，从而较快的得出次优的结果。仿真结果表明，对于中等规模的网络，该启发式算法得到的次优结果相对最优结果的平均偏离率在0.5%以内，而平均运算时间仅为最优算法的4%左右。
3）对于对等式通信模式下无线Mesh网中存在多个不同源目的点对间业务流情形下的优化问题，由于不存在无线Mesh回程网中的流汇聚特性，不能简单对各条链路进行分类并赋权重值，对此本文提出了一种利用改进的Dijkstra路由算法来寻找流传输可能会用到的关键链路，然后结合本文提出的基于权重的启发式算法对网络吞吐量进行优化。该算法的创新点在于：首先对链路占用率的计算考虑了不同链路的并发对同一链路的干扰，避免了对被干扰链路占用率的重复计算；其次对关键链路进行了反复搜索，每次搜索前都对源-目的点对间业务流进行随机排序，减小了因路由先后次序对关键链路生成的影响。仿真结果验证了该算法的能够较好解决对等式无线Mesh网的吞吐量优化问题，且其优势随网络规模的扩大而愈加明显。
Wireless Mesh Networks (WMN) have emerged recently as a type of wireless multi-hopnetworks developed form ad-hoc networks. WMNs have the capability of self-forming,self-healing and self-organization and are a key technology for the next generation wirelessnetworks. With the characteristics of easy deployment at low cost, flexible structure andcoverage, WMNs have more and more application scenarios in recent years. Based on thesurvey on the fundamentals of WMNs technology and recent advances in related research, thecross-layer joint optimization algorithms for WMNs are investigated and the contributionsand innovations are achieved as follows:
1) To address the cross-layer optimization of routing and scheduling for TDMA-basedwireless mesh backhaul networks under the centralized control mode, based on introducing across-layer joint optimization framework whose optimal target is minimizing the systemactivation time, we propose a fast optimal algorithm by using maximal cliques searchingalgorithm to enumerate all maximal concurrent transmission scenarios in a wireless meshnetwork. Based on that, the optimization framework can be simplified to a LP (LinearProgramming) problem, so the global optimal solution could be easily found. Simulationresults verify that compared with the classical column generation algorithm usually used inthis kind of optimization problems, the average runtime has been reduced by more than99%.
2) In order to maximize the throughput of relatively large scale WMNs, optimalalgorithms will take quite a long time to calculate the optimal result because the optimizationof thoughput of WMNs under the consideration of wireless interference is an NP-hardproblem by nature. According to the flow character in wireless mesh backhaul networks, wepropose a fast heuristic algorithm to get suboptimal results. Based on classification of linkweight, the heuristic algorithm can find out with high probability those maximal CTSs whichinclude high weight links and which are relatively more important. Furthermore, throughestablishing the effective connection between the searching times newly added and thevariance of the optimized results, the convergence of the algorithm can be guaranteed and thesuboptimal results can be obtained quickly. The simulation results show that the heuristicalgorithm can obtain suboptimal results within average0.5%of optimality for modest sizenetworks, and the average runtime is only about4%of that of maximal cliques algorithm.
3) In the scenario of solving the throughput optimization problem of peer-to-peer WMNsin which there are traffic flows between multi source-destination pairs, without the flow convergence feature in wireless mesh backhaul networks, it is hard to classify the wirelesslinks and assign weight value to them. To solve this problem, firstly we propose an improvedDijkstra routing algorithm to search those key links probably used to transmit flow, thencombine those links and the heuristic algorithm mentioned above to slove the throughputoptimization. The innovative points lie in: firstly in order to avoid repeated calculation ofinterfered links’ occupancy ratio, we consider the concurrent transmission of different links inthe same path when we calculate link occupancy ratio; secondly we search those key linksrepeatedly and each time we change the sequence of the source-destination pairs ranodomly,that will reduce the influence to key links generation caused by routing sequence. Simulationresults show that this approach can solve the throughput optimization of peer-to-peer WMNsproperly and its advantage becomes more obvious with the enlargement of network scale.
1）针对时分复用（TDMA）模式下无线Mesh网的路由及调度的联合优化，在以最短系统调度时间为目标的跨层联合优化模型的基础上，提出了一种基于极大团搜索的最优算法。该算法通过极大团搜索列举网络中所有极大并发传输模式，使优化问题的模型得到简化，从而可以用线性规划的方法最小化系统调度时间，优化运算的速度得到了极大的提高。通过对比仿真实验表明，对比目前该类优化问题常用的列生成最优算法，优化运算时间缩短了99%以上。
2）对于较大规模的无线Mesh网，因为考虑链路无线干扰的前提下，其最大化吞吐量问题本质上是一个NP难问题，所以对其进行吞吐量的最优化计算存在计算时间较长的问题。根据无线Mesh回程网的流量汇聚的特点，本文提出了一种基于链路权重分类的快速启发式算法，首先由各条链路在流量传输中的重要性对其分类并赋予不同的权重值，对含有较大权重链路的极大并发传输模式以较大的概率选出。然后，通过建立起极大并发模式的搜索次数与优化结果之间的有效联系，使得该算法的收敛特性得到保证，从而较快的得出次优的结果。仿真结果表明，对于中等规模的网络，该启发式算法得到的次优结果相对最优结果的平均偏离率在0.5%以内，而平均运算时间仅为最优算法的4%左右。
3）对于对等式通信模式下无线Mesh网中存在多个不同源目的点对间业务流情形下的优化问题，由于不存在无线Mesh回程网中的流汇聚特性，不能简单对各条链路进行分类并赋权重值，对此本文提出了一种利用改进的Dijkstra路由算法来寻找流传输可能会用到的关键链路，然后结合本文提出的基于权重的启发式算法对网络吞吐量进行优化。该算法的创新点在于：首先对链路占用率的计算考虑了不同链路的并发对同一链路的干扰，避免了对被干扰链路占用率的重复计算；其次对关键链路进行了反复搜索，每次搜索前都对源-目的点对间业务流进行随机排序，减小了因路由先后次序对关键链路生成的影响。仿真结果验证了该算法的能够较好解决对等式无线Mesh网的吞吐量优化问题，且其优势随网络规模的扩大而愈加明显。
Wireless Mesh Networks (WMN) have emerged recently as a type of wireless multi-hopnetworks developed form ad-hoc networks. WMNs have the capability of self-forming,self-healing and self-organization and are a key technology for the next generation wirelessnetworks. With the characteristics of easy deployment at low cost, flexible structure andcoverage, WMNs have more and more application scenarios in recent years. Based on thesurvey on the fundamentals of WMNs technology and recent advances in related research, thecross-layer joint optimization algorithms for WMNs are investigated and the contributionsand innovations are achieved as follows:
1) To address the cross-layer optimization of routing and scheduling for TDMA-basedwireless mesh backhaul networks under the centralized control mode, based on introducing across-layer joint optimization framework whose optimal target is minimizing the systemactivation time, we propose a fast optimal algorithm by using maximal cliques searchingalgorithm to enumerate all maximal concurrent transmission scenarios in a wireless meshnetwork. Based on that, the optimization framework can be simplified to a LP (LinearProgramming) problem, so the global optimal solution could be easily found. Simulationresults verify that compared with the classical column generation algorithm usually used inthis kind of optimization problems, the average runtime has been reduced by more than99%.
2) In order to maximize the throughput of relatively large scale WMNs, optimalalgorithms will take quite a long time to calculate the optimal result because the optimizationof thoughput of WMNs under the consideration of wireless interference is an NP-hardproblem by nature. According to the flow character in wireless mesh backhaul networks, wepropose a fast heuristic algorithm to get suboptimal results. Based on classification of linkweight, the heuristic algorithm can find out with high probability those maximal CTSs whichinclude high weight links and which are relatively more important. Furthermore, throughestablishing the effective connection between the searching times newly added and thevariance of the optimized results, the convergence of the algorithm can be guaranteed and thesuboptimal results can be obtained quickly. The simulation results show that the heuristicalgorithm can obtain suboptimal results within average0.5%of optimality for modest sizenetworks, and the average runtime is only about4%of that of maximal cliques algorithm.
3) In the scenario of solving the throughput optimization problem of peer-to-peer WMNsin which there are traffic flows between multi source-destination pairs, without the flow convergence feature in wireless mesh backhaul networks, it is hard to classify the wirelesslinks and assign weight value to them. To solve this problem, firstly we propose an improvedDijkstra routing algorithm to search those key links probably used to transmit flow, thencombine those links and the heuristic algorithm mentioned above to slove the throughputoptimization. The innovative points lie in: firstly in order to avoid repeated calculation ofinterfered links’ occupancy ratio, we consider the concurrent transmission of different links inthe same path when we calculate link occupancy ratio; secondly we search those key linksrepeatedly and each time we change the sequence of the source-destination pairs ranodomly,that will reduce the influence to key links generation caused by routing sequence. Simulationresults show that this approach can solve the throughput optimization of peer-to-peer WMNsproperly and its advantage becomes more obvious with the enlargement of network scale.
引文
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