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Routing an Electric Vehicle for Optimum Energy Consumption with EE-MAODV Using NS3

机译:使用NS3通过EE-MAODV路由电动汽车以实现最佳能耗

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Now a days, electric vehicles will turn into a famous method of travel when increment. of oil costs and intensifies global warming. Power is less expensive than the petroleum products and can be created utilizing characteristic sustainable assets for. example, solar| or wind power, and consequently restricts contamination. Electric vehicles are more productive and expend less vitality than fuel vehicles. The improvement of e/ectric vehicle turns out to be more since progression in battery innovation and engine productivity. Energym Management is the key factor in EV or hybrid Electric vehicles (HEV) plan. The main challenge in the EV is the charging time required for the batteries and deficiency of charging stations (cs). By thinking about the issue of shortest path and1 energy utilization, this1 Paper incorporates1 the execution examination of AODV (adhoc On-demand distance1 Vector) directing1 convention with1 the improved1 EE-MAODV (energy efficient Modified AODV) for QOS (quality of service) metrics1 in route finding1 and maintenance with energy utilization and Route enhancement utilizing network simulator3. This paper especially1 centered around1 usage and examination1of execution parameters for1 example, average1 end-end delay, Packet1 Delivery Ratio (PDR), directing1 overhead and energym consumption. The proposed strategy is compared with the basic AODV for tracking system so that the implement controller has the attributes of high modularity and probability.
机译:如今,电动汽车在增加时将成为一种著名的出行方式。石油成本的上升,加剧了全球变暖。电力比石油产品便宜,可以利用具有特色的可持续资产来发电。例如,太阳能|或风力发电,从而限制了污染。电动汽车比燃油汽车生产率更高,并且生命力更少。由于电池创新和发动机生产率的提高,电动/电动汽车的进步更加明显。能源管理是电动汽车或混合动力汽车(HEV)计划中的关键因素。电动汽车的主要挑战是电池所需的充电时间和充电站(cs)的不足。通过考虑最短路径和1能源利用的问题,本文将1 AODV(临时按需距离1矢量)指导1惯例的执行检查与1改进的1 EE-MAODV(能源效率改进的AODV)用于QOS(服务质量)度量标准1进行了合并。通过网络模拟器3进行路线查找1和能源利用的维护以及路线增强。本文尤其以1用法和1执行参数的检查为中心,例如平均1端延迟,Packet1传输率(PDR),指导1开销和能耗。将提出的策略与基本的AODV跟踪系统进行比较,以使机具控制器具有较高的模块化和高概率性。

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