一种基于认知的基于蚁群优化稳定路径选择的通道分类方法

N. Kumar, G. Bala
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引用次数: 0

摘要

路由协议具有发现和维护网络中的路由的能力。然而,所设计的路由协议的效率取决于节点的能力和应用需求。物联网(IoTN)正在被应用于实时应用中,如寻找到达目的地的最短路径、交通管理、根据天气状况重新路由路径、幸福家庭架构、天气系统等。尽管IoTN的应用非常广泛,但电池寿命和能源效率有限,无法满足IoTN的应用。因此,该算法所选择的特征有助于利用基于蚁群的系统对路径进行优化,以选择到目的地的最佳和最小距离路径。提出的蚁群优化稳定路径(AOSP)选择算法主要关注熟人选择、渠道决策和能量管理等网络选择阶段。传感器可以与目标基站通信,有效地转发或中继数据到达服务器。最优的中间传感器可以作为簇头,以最小的能量从一组传感器中收集信息,从而提高了吞吐量,降低了丢包率。
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A Cognitive Based Channel Assortment Using Ant-Colony Optimized Stable Path Selection in an IoTN
Routing protocols have ability to discover and maintain routes in the network. However, the efficiency of designed routing protocol depends on the node capability and application requirement. IoTN (Internet of Things Network) is being adopted into real time applications such as finding shortest path to reach destination, traffic management, rerouting path based on weather conditions, happy home architectures, weather systems and so on. Despite enormous applications of IoTN, the battery life and energy efficiency are limited to fulfil applications in IoTN. Hence the selected features for the proposed algorithm contribute towards optimizing the path to select best and least distance path to destination using ant-based system. Proposed Ant-colony optimized stable path (AOSP) selection algorithm focus on network selection stages like Selection of acquaintances, channel decisions and Energy management. Sensors can communicate with target BS (Base station) to forward or relay the data efficiently to reach server. The optimal intermediate sensors can act as cluster head and collect information from group of sensors with minimal energy spent which increase the throughput and decrease the packet dropping ratio.
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