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Novel chemical reaction optimization based unequal clustering and routing algorithms for wireless sensor networks

机译:基于新型化学反应优化的不平等聚类和路由算法的无线传感器网络

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Energy conserving of sensor nodes is the most crucial issue in the design of wireless sensor networks (WSNs). In a cluster based routing approach, cluster heads (CHs) cooperate with each other to forward their data to the base station (BS) via multi-hop routing. In this process, CHs closer to the BS are burdened with heavier relay traffic and tend to die prematurely which causes network partition is popularly known as a hot spot problem. To mitigate the hot spot problem, in this paper, we propose unequal clustering and routing algorithms based on novel chemical reaction optimization (nCRO) paradigm, we jointly call these algorithms as novel CRO based unequal clustering and routing algorithms (nCRO-UCRA). In clustering, we partition the network into unequal clusters such that smaller size clusters near to the sink and larger size clusters relatively far away from the sink. For this purpose, we develop the CH selection algorithm based on nCRO paradigm and assign the non-cluster head sensor nodes to the CHs based on derived cost function. Then, a routing algorithm is presented which is also based on nCRO based approach. All these algorithms are developed with the efficient schemes of molecular structure encoding and novel potential energy functions. The nCRO-UCRA is simulated extensively on various scenarios of WSNs and varying number of sensors and the CHs. The results are compared with some existing algorithms and original CRO based algorithm called as CRO-UCRA to show the superiority in terms of various performance metrics like residual energy, network lifetime, number of alive nodes, data packets received by the BS and convergence rate.
机译:传感器节点的节能是无线传感器网络(WSN)设计中最关键的问题。在基于群集的路由方法中,群集头(CH)相互协作,以通过多跳路由将其数据转发到基站(BS)。在此过程中,距离BS较近的CH会承受较大的中继流量负担,并且倾向于过早死亡,这导致网络分区被普遍称为热点问题。为了缓解热点问题,在本文中,我们提出了基于新型化学反应优化(nCRO)范式的不平等聚类和路由算法,我们将这些算法统称为基于新型CRO的不平等聚类和路由算法(nCRO-UCRA)。在群集中,我们将网络划分为不相等的群集,以使较小的群集靠近接收器,而较大的群集则相对远离接收器。为此,我们开发了基于nCRO范式的CH选择算法,并根据派生的成本函数将非簇头传感器节点分配给CH。然后,提出了一种基于nCRO的路由算法。所有这些算法都是通过有效的分子结构编码方案和新颖的势能函数开发的。 nCRO-UCRA在各种WSN和不同数量的传感器和CH上进行了广泛的仿真。将结果与一些现有算法以及基于原始CRO的称为CRO-UCRA的算法进行比较,以显示在各种性能指标方面的优越性,例如剩余能量,网络寿命,活动节点数,BS接收的数据包和收敛速率。

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