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Ant Colony Optimization Based Energy Efficient Routing Algorithms For Routing In Mobile Ad Hoc Networks

机译:Ad Hoc网络中基于蚁群优化的高效路由算法。

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Routing protocols in Mobile Ad-hoc Networks (MANETs) has yielded optimistic results for a long time, but the conflicts begin when we start tofocus on particular parameters of the algorithms, like packet delivery ratio, end-to-end delay, throughput, energy consumptions, etc. These factors arevery crucial in an algorithm as these are the building blocks of the optimal solution. For example, if an algorithm has a satisfactory packet delivery ratiobut the energy used/consumed by the nodes of MANETs is such high that is it not feasible to implement or beneficial to implement in a real-time issue,then the algorithm would not be a practical solution to the efficient routing problem. Ant colony optimization is a heuristic which has so far yielded resultsthat are satisfactory compared to other nature-inspired heuristics. In this paper, we propose Ant Colony Optimization – Energy Efficient RoutingAlgorithm (ACO-EERA), an algorithm which has produced significantly good results in comparison with other algorithms. The algorithm implements afunction which chooses less the nodes with low energy remaining and it reduces the loss of energy of packets being dropped. At the end of the researchpaper, we also compare our proposed algorithm with Ad-Hoc On-demand Distance Vector (AODV), for the factors such as Packet delivery ratio, End toEnd delay and total Energy consumption.
机译:长期以来,移动自组织网络(MANET)中的路由协议都产生了乐观的结果,但是当我们开始关注算法的特定参数(例如数据包传输率,端到端延迟,吞吐量,能量)时,冲突就开始了。这些因素在算法中非常关键,因为它们是最佳解决方案的基础。例如,如果一种算法的分组传送率令人满意,但是MANET的节点所使用/消耗的能量如此之高,以致于无法实时实施或有益于实时发行,则该算法将不是高效路由问题的实际解决方案。蚁群优化是一种启发式方法,到目前为止,与其他自然启发式启发式方法相比,其结果令人满意。在本文中,我们提出了蚁群优化–节能路由算法(ACO-EERA),与其他算法相比,该算法已产生了明显的良好结果。该算法实现的功能是选择较少节点且剩余能量较低,从而减少了丢弃数据包的能量损失。在研究的最后,我们还将所提出的算法与Ad-Hoc按需距离矢量(AODV)进行了比较,以分析数据包传输率,端到端延迟和总能耗等因素。

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