物联网智能交通系统的混合节能和qos感知算法

Victor Chang, G. Sunitha, S. D. Dilip Kumar, S. Raghavendra, N. Srinidhi
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引用次数: 3

摘要

物联网(IoT)由大量耗能设备组成,这些设备是为了提高几种工业应用的有效能力而预先设计的。在不影响智能交通系统的服务质量(QoS)的情况下,降低物联网网络中部署的每个设备的能耗是非常重要的。为了实现这一目标,设计了一个多目标优化问题,以实现对聚类过程停机性能和网络生存期的估计。随后,提出了一种混合节能和QoS感知(HEEQA)算法,该算法将量子粒子群优化(QPSO)与改进的非支配排序遗传算法(NSGA)相结合,以实现设备之间的能量平衡。将NSGA应用于多目标优化问题,并利用QPSO算法在集群中寻找最优的合作节点和簇头。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid energy-efficient and QoS-aware algorithm for intelligent transportation system in IoT
The Internet of Things (IoT) consists of large amount of energy consuming devices which are pre-figured to progress the effective competence of several industrial applications. It is very much essential to bring down the energy use of every device deployed in the IoT network without compromising the Quality of Service (QoS) for intelligent transportation system. To achieve this objective, a multiobjective optimisation problem to accomplish the aim of estimating the outage performance of clustering process and the network lifetime is devised. Subsequently, a Hybrid Energy Efficient and QoS Aware (HEEQA) algorithm that is a combination of Quantum Particle Swarm Optimisation (QPSO) along with improved Non-dominated Sorting Genetic Algorithm (NSGA) to achieve energy balance among the devices is proposed. NSGA is applied to solve the problem of multiobjective optimisation and the QPSO algorithm is used to find the optima cooperative nodes and cluster head in the clusters.
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