共查询到16条相似文献,搜索用时 93 毫秒
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混合式无线mesh网络中信道分配算法研究 总被引:4,自引:0,他引:4
目前混合式信道分配算法未考虑节点数据传输量差异,从而导致信道负载不均,针对该问题,提出了负载平衡的分布式信道分配算法--LBCA.该算法通过分布式构建节点冲突图,使同一冲突域中数据量较大的接口卡优先选择负载较小的信道,从而较好平衡了信道负载.理论分析表明,LBCA算法以趋近1的概率在O(log n)轮内结束,n为网络固定接口卡数目;模拟实验表明,在网络负载达到80%以上时,对信道数目不大于6的网络,LBCA算法的网络吞吐率与目前同类算法相比提升10%以上. 相似文献
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混合频谱共享是适应认知用户不同地理分布的有效频谱共享模式。信道分配是无线通信网络中关键的问题之一,近年来得到了广泛研究。集中式信道分配算法是最常用的算法形式,但在认知无线电网络这种分布式系统中,集中式算法不易实现。将混合共享认知无线网络的信道分配问题构建为一对一的匹配博弈,提出了分布式用户-信道匹配算法。该算法数学复杂度低,且能够达到稳定匹配。仿真结果表明,算法收敛时间短,稳定匹配状态下的平均传输速率与使用匈牙利算法的最优分配算法所获得传输速率相接近,远优于随机分配算法的传输速率。 相似文献
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为解决认知无线mesh网络中的信道干扰问题,提出了一种基于容量与干扰的分布式信道分配和路由算法.首先根据路由度量有效地选择最低累积代价路由,再根据信道干扰容量比最小化来选择信道.仿真结果表明:所提算法与基于干扰、基于链接的算法相比,能够显著改善平均吞吐量和时延等网络参数性能. 相似文献
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基于分组管理的无线mesh网多信道分配算法* 总被引:1,自引:1,他引:0
为了合理利用多信道来提高无线网络吞吐量,针对基于802.11标准无线mesh网的业务特点,提出了基于分组管理的分布式多信道分配算法。该算法将节点接口分为回程接口与转发接口,并使回程接口分配到在干扰区域内干扰值尽可能小的信道。仿真实验结果表明,该算法可以减少区域干扰,并可充分利用信道的多样性和得到较高的网络吞吐量。 相似文献
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如果网络中的节点不能及时公平地共享信道资源,会造成数据传输延时的增加和节点能量的浪费。为解决这种信道分配不均问题,提出一种基于TDMA的调度算法TSFA。该算法分为网络分簇、节点染色、独立集调度3个步骤,主要思想是在分布式顶点染色算法DVCA的基础上得到最大独立集,其根据每个独立集内的数据流量大小分配时隙。仿真结果表明,TSFA避免了相邻节点间的通信干扰,减少了网络的通信延时,提高了网络的吞吐量,实现了信道分配的公平性。 相似文献
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一种优化算法物联网技术分布式协作路由研究 总被引:1,自引:1,他引:0
研究无线传感器网络分布式协作优化问题。针对无线传感器网络资源利用率和传输效率低下等问题,建立了一种基于遗传优化算法的无线信道质量预测的分布式优化协作路由技术。该技术充分利用遗传算法,采用启发式方法建立无线链路信道信噪比预测模型,然后根据信道质量选择最优者作为协作节点,以较小代价在动态无线网络拓扑中搜寻到最优路由。数学分析表明,遗传算法收敛速度快、可靠性高,可以准确地预测无线链路质量;同时该协作路由技术对无线传感器网络具有更好的适应性,并有效延长了网络生命周期。 相似文献
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高效分布式算法设计是保证无线传感网络性能的关键问题。提出了一种基于信道容量约束的无线传感网络效用最大化问题模型。针对传统一阶算法存在收敛速度慢、步长选择敏感等缺点,文章设计了具有二阶收敛速度的快速分布式牛顿算法。研究和仿真实验表明,该算法在与传统一阶算法交互几乎相同信息的情况下具有二次收敛速度,算法迭代次数和运行时间改进了近两个数量级。 相似文献
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《Journal of Parallel and Distributed Computing》2000,60(4):451-473
A channel allocation algorithm includes a channel acquisition algorithm and a channel selection algorithm. Most of the previous work concentrates on the channel selection algorithm since early channel allocation algorithms simply use a centralized channel acquisition algorithm, which depends on a mobile switching center (MSC) to accomplish channel acquisition. Recently, distributed channel acquisition algorithms have received considerable attention due to their high reliability and scalability. There are two approaches to designing distributed channel acquisition algorithms: search and update. The update approach has shorter acquisition delay and lower call blocking rate, but higher message complexity. On the other hand, the search approach has lower message complexity, but longer acquisition delay and higher call blocking rate. In this paper, we propose a novel distributed channel acquisition algorithm, which is a significant improvement over both approaches. Also, we identify two guiding principles in designing channel selection algorithms and propose an algorithm which has low call blocking rate and low intrahandoff overhead. By integrating the channel selection algorithm into our channel acquisition algorithm, we get a complete distributed channel allocation algorithm. By keeping the borrowed channels, the channel allocation algorithm makes use of the temporal locality and adapts to the network traffic; i.e., free channels are transferred to hot cells to achieve load balance. Simulation results show that our channel allocation algorithm significantly outperforms the search approach and the update approach in terms of call blocking rate, message complexity, and acquisition delay. 相似文献
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针对多接口多信道无线Mesh网络,提出了一种基于链路负载和链路“潜在的”干扰度的权值的分布式静态信道分配算法。给出基于链路负载和链路“潜在的”干扰度的权值的定义和基于权值的链表的构建方法;阐述了算法的设计思想和实现步骤。仿真实验测试结果表明,该算法不但能适应业务流量分布均匀或不均匀的状态,而且能相应地提高网络吞吐量,提升网络性能。 相似文献
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Jointly optimal congestion control, channel allocation and power control in multi-channel wireless multihop networks 总被引:1,自引:0,他引:1
In this paper, to increase end-to-end throughput and energy efficiency of the multi-channel wireless multihop networks, a framework of jointly optimize congestion control in the transport layer, channel allocation in the data link layer and power control in the physical layer is proposed. It models the network by a generalized network utility maximization (NUM) problem with elastic link data rate constraints. Through binary linearization and log-transformation, and after relaxing the binary constraints on channel allocation matrix, the NUM problem becomes a convex optimization problem, which can be solved by the gateway centralized through branch and bound algorithm with exponential time complexity. Then, a partially distributed near-optimal jointly congestion control, channel allocation and power control (DCCCAPC) algorithm based on Lagrangian dual decomposition technique is proposed. Performance is assessed through simulations in terms of network utility, energy efficiency and fairness index. Convergence of both centralized and distributed algorithms is proved through theoretic analysis and simulations. As the available network resources increase, the performance gain on network utility increases. 相似文献