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Delay optimization in manets using Knapsack and genetic algorithm

机译:使用背包和遗传算法延迟船只中的优化

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MANETs are wireless ad hoc network without any predefined infrastructure. They consist of autonomous or free nodes that can arrange themselves in various ways and operate without strict network administration. Multimedia transmission over Mobile Adhoc Networks (MANETs) is crucial to many applications. In MANETs, multiple path propagation is commonly used to transmit the data packets from source to destination. Multipath propagation results in out of order packet and thereby it increases the delay. For effective multimedia transmission, delay should be minimum and packets should reach the destination in defined order. The existing approaches either reduce the packet size or increase the streaming compression to reduce the loss. Reducing the packet size increases congestion whereas streaming compression only optimizes the bandwidth. The approach uses Knapsack algorithm for buffer management to maximize the in-order packets and minimize the out-of-order packets simultaneously. It also uses genetic algorithm to improve the packet delivery ratio.
机译:MANETS是无线临时网络,没有任何预定义的基础架构。它们由自主或自由节点组成,可以以各种方式安排并在没有严格的网络管理的情况下运行。移动adhoc网络上的多媒体传输(船只)对于许多应用来说至关重要。在船只中,通常用于将数据包从源传输到目的地。多径传播结果出现在订单数据包中,从而增加了延迟。对于有效的多媒体传输,延迟应为最小,并且数据包应以定义的顺序到达目的地。现有方法缩短数据包大小或增加流压缩以减少损耗。降低数据包大小增加了拥塞,而流压缩仅优化带宽。该方法使用缓冲管理的背包算法来最大化有序数据包,并同时最小化无序数据包。它还使用遗传算法来提高数据包传递比率。

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