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LIDAR: a protocol for stable and energy-efficient clustering of ad-hoc multihop networks

机译:LIDAR:一种用于稳定多跳网络的稳定高效节能群集的协议

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Clustering has been proposed as a promising method for simplifying the routing process in mobile ad hoc networks (MANETs). The main objective in clustering is to identify suitable node representatives, i.e. cluster heads (CHs) to store routing and topology information; CHs should be elected so as to maximize clusters stability, that is to prevent frequent cluster re-structuring. Since CHs are engaged on packet forwarding they are prone to rapidly drop their energy supplies, hence, another important objective of clustering is to prevent such node failures. Recently proposed clustering algorithms either suggest CH election based on node IDs (nodes with locally lowest ID value become CHs) or take into account additional metrics (such as energy and mobility) and optimize initial clustering. Yet, the former method is biased against nodes with low IDs (which are likely to serve as CHs for long periods and therefore run the risk of rapid battery exhaustion). Similarly, in the latter method, in many situations (e.g. in relatively static topologies) re-clustering procedure is hardly ever invoked; hence initially elected CHs soon suffer from energy drainage. Herein, we propose LIDAR, a novel clustering method which represents a major improvement over alternative clustering algorithms: node IDs are periodically re-assigned so that nodes with low mobility rate and high energy capacity are assigned low ID values and, therefore, are likely to serve as CHs. Therefore, LIDAR achieves stable cluster formations and balanced distribution of energy consumption over mobile nodes. Our protocol also greatly reduces control traffic volume of existing algorithms during clustering maintenance phase, while not risking the energy availability of CHs. Simulation results demonstrate the efficiency, scalability and stability of our protocol against alternative approaches.
机译:已经提出了群集化作为简化移动自组织网络(MANET)中路由过程的一种有前途的方法。群集的主要目的是确定合适的节点代表,即用于存储路由和拓扑信息的群集头(CH)。应选择CH,以最大程度地提高群集的稳定性,即防止频繁的群集重组。由于CH参与数据包转发,因此它们倾向于迅速降低其能量供应,因此,群集的另一个重要目标是防止此类节点故障。最近提出的聚类算法或者建议基于节点ID的CH选择(具有最低ID值的本地节点成为CH),或者考虑其他指标(例如能量和移动性)并优化初始聚类。但是,前一种方法偏向于ID较低的节点(它们很可能长期用作CH,因此存在电池快速耗尽的风险)。同样,在后一种方法中,在许多情况下(例如,在相对静态的拓扑中),几乎不会调用重新聚类过程。因此,最初当选的CH很快就会消耗能量。在这里,我们提出LIDAR,这是一种新颖的聚类方法,它代表了对替代聚类算法的重大改进:定期重新分配节点ID,以便为低移动性和高能量容量的节点分配低ID值,因此很可能会充当CH。因此,LIDAR实现了稳定的集群结构和移动节点上能量消耗的均衡分配。我们的协议还可以在集群维护阶段极大地减少现有算法的控制流量,同时又不会威胁CH的能源可用性。仿真结果证明了我们的协议相对于其他方法的效率,可扩展性和稳定性。

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