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Reducing Route discovery latency in MANETs using ACO

机译:使用ACO减少MANET中的路由发现延迟

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Mobile Ad-hoc Networks (MANETs) have Routing as a censorious challenge. The substantial issue in ad-hoc network is seeking out a shortest path among communicating nodes. The contemplations in MANET framework and the constitution of the mobile nodes create inconveniences that bring the necessity to evolve special routing techniques to eliminate such issues. Swarm intelligence is a bio-propelled technique that is really resilient to alternative issue space. The activities of individual ants in ant colonies are not administered by any centralized infrastructure. The robust self-organizing nature of ant colony is because of interacting behaviour among neighbour ants and dynamics of individuals. This novel feature has made ant societies an inspiring model for developing new algorithms for routing in MANET frameworks. In this paper, Ant Colony based routing algorithms and its variations have been examined and evaluated. Here the delivery ratio of packets and end to end delivery has been especially taken as the performance factor for MANETs. The fundamental thought of this paper is to use Ant Colony Optimization (ACO) in MANET protocol Ad-hoc On Demand Vector (AODV) to optimize its performance by reducing Route discovery latency.
机译:移动自组织网络(MANET)将路由作为一项严峻的挑战。 ad-hoc网络中的实质性问题是寻找通信节点之间的最短路径。 MANET框架中的考虑和移动节点的构造带来了不便,这带来了发展特殊路由技术以消除此类问题的必要性。群智能是一种生物推动技术,对其他问题空间具有真正的弹性。蚂蚁群落中单个蚂蚁的活动不受任何集中式基础设施的管理。蚂蚁群体强大的自组织性质是由于相邻蚂蚁之间的相互作用行为和个体动态。这项新颖的功能使蚂蚁社会成为一种启发性的模型,用于开发用于在MANET框架中进行路由的新算法。在本文中,已经研究和评估了基于蚁群的路由算法及其变体。在这里,数据包的传输率和端到端的传输已被特别视为MANET的性能因素。本文的基本思想是在MANET协议即席按需向量(AODV)中使用蚁群优化(ACO)通过减少路由发现延迟来优化其性能。

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