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A Novel Dynamic Noise-Dependent Probabilistic Algorithm for Route Discovery in MANETs

机译:MANET中路由发现的一种新的动态噪声相关概率算法

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In mobile ad hoc networks (MANETs), broadcasting is widely used in route discovery and other network services. The most widely used broadcasting algorithm is simple flooding, which aggravates a high number of redundant packet retransmissions, causing contention and collisions. Proper use of dynamic probabilistic algorithm significantly reduces the number of retransmissions, which reduces the chance of contention and collisions. In current dynamic probabilistic algorithm, the retransmission probability (p) is formulated as a linearon-linear function of a single variable, the number of first-hop neighbors (k). However, such algorithm is suffers in the presence of noise due to increasing packet-loss. In this paper, the authors propose a new dynamic probabilistic algorithm in which p( is determined locally by the retransmitting nodes considering both k and the noise-level. This algorithm is referred to as the dynamic noise-dependent probabilistic (DNDP) algorithm. The performance of the DNDP algorithm is evaluated through simulations using the MANET simulator (MANSim). The simulation results show that the DNDP algorithm presents higher network reachability than the dynamic probabilistic algorithm at a reasonable increase in the number of retransmissions for a wide range of noise-level. The effects of nodes densities and nodes speeds on the performance of the DNDP algorithm are also investigated.
机译:在移动自组织网络(MANET)中,广播广泛用于路由发现和其他网络服务。最广泛使用的广播算法是简单泛洪,它会加剧大量的冗余数据包重传,从而引起竞争和冲突。正确使用动态概率算法会大大减少重传次数,从而减少争用和冲突的机会。在当前的动态概率算法中,将重传概率(p)公式化为单个变量,第一跳邻居的数量(k)的线性/非线性函数。然而,由于增加的分组丢失,这种算法在存在噪声的情况下遭受痛苦。在本文中,作者提出了一种新的动态概率算法,其中p(由同时考虑k和噪声水平的重传节点本地确定,该算法称为动态噪声相关概率(DNDP)算法。通过使用MANET仿真器(MANSim)进行的仿真评估了DNDP算法的性能,仿真结果表明,在动态范围较大的噪声下,合理地增加重传次数,DNDP算法比动态概率算法具有更高的网络可达性。还研究了节点密度和节点速度对DNDP算法性能的影响。

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