Improving the Quality of Service (QoS) and Resource Allocation in Vehicular Platoon Using Meta-Heuristic Optimization Algorithm

R. Priya, N. Sivakumar
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Abstract

The concept of vehicular platooning is emerging due to its self-driving capability, whereas a set of cars are arranged closely and that can drive safely even in high speed. Moreover the communication can also takes place between two platoons and hence the platoon leader can control the speed and direction. Traffic difficulties, like as collisions and delay at road junctions, need the use of platoon mechanisms. The most efficient vehicle traffic management in platoons is acknowledged in Intelligent Transportation System (ITS) for improving energy efficiency, road capacity, and road safety. Essentially, it is critical to analyse the connection characteristic of any two platoons in order to improve connectivity. As a result, under bi-directional platoon architecture, the possibility of connectivity between platoon members and Road Side Units (RSUs) is generated. Providing Quality of Service (QoS) to automotive network is difficult issue because elements such as asynchronous transmission or high mobility, crowded and fragmented channels, hardware defects, and various vehicular gadgets. As a result, it is extremely desired to utilize and distribute resources efficiently. Despite the existence of other bio-inspired meta-heuristic optimization methods, the Bacterial Foraging Algorithm has the benefit of simplicity and efficiency, and so may be used to a wide range of engineering applications. However, in the event of sophisticated analysis, the constraint is a lower convergence rate. To improve resource allocation, this study employs the Improved Bacterial Foraging Optimization based Channel Allocation (IBFOCA) technique. Set of channels allocated to platoon members are signified as bacteria’s position. By using latency, Signal-to-Interference Ratio (SINR) and Quality of Service (QoS), available channel is initially determined. This approach is used to find a channel that is acceptable for platoon members. Simulation results are used to examine the presentation of multi-channel distributions in platoons utilizing suggested optimization strategy. Signal-to-interference ratio is lowered by 29 decibel, throughput is raised by 69 kilobits per second, collision probability is reduced by 21.4 percent, and average batch size is 57 percent with a delay of 49 milliseconds.
利用元启发式优化算法提高车辆队列的服务质量和资源分配
车辆排成一排的概念之所以出现,是因为它具有自动驾驶的能力,而一组车紧密排列在一起,即使在高速行驶中也能安全行驶。此外,通信也可以在两个排之间进行,因此排长可以控制速度和方向。交通困难,比如在路口的碰撞和延误,需要使用排排机制。在智能交通系统(ITS)中,最有效的车辆交通管理被公认为提高能源效率,道路容量和道路安全。从本质上讲,分析任意两个排的连接特性是提高连通性的关键。因此,在双向组队架构下,组队成员与路旁单位(Road Side Units, rsu)之间产生了连接的可能性。由于异步传输或高移动性、拥挤和分散的信道、硬件缺陷和各种车载设备等因素,向汽车网络提供服务质量(QoS)是一个难题。因此,有效地利用和分配资源是非常需要的。尽管存在其他启发生物的元启发式优化方法,但细菌觅食算法具有简单和高效的优点,因此可以用于广泛的工程应用。然而,在复杂分析的情况下,约束是较低的收敛速率。为了提高资源分配效率,本研究采用了基于改进细菌觅食优化的通道分配(IBFOCA)技术。分配给排成员的通道集表示为细菌的位置。通过使用延迟、信干扰比(SINR)和服务质量(QoS),初步确定可用信道。这种方法用于寻找排成员可以接受的通道。仿真结果被用来检验多通道分布的表现在排利用建议的优化策略。信干扰比降低了29分贝,吞吐量提高了69千比特/秒,碰撞概率降低了21.4%,平均批大小减少了57%,延迟为49毫秒。
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