Bagula Antoine, Abidoye Ademola Philip, Zodi Guy-Alain Lusilao
Intelligent Systems and Advanced Telecommunication Laboratory, Department of Computer Science, University of the Western Cape, Private Bag X17, Bellville, Cape Town 7535, South Africa.
Department of Computer Science, Namibia University of Science and Technology (NUST), Private Bag 13888, Windhoek 9000, Namibia.
Sensors (Basel). 2015 Dec 23;16(1):9. doi: 10.3390/s16010009.
Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices' service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes' life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN.
当前一代无线传感器路由算法和协议是基于短视路由方法设计的,在这种方法中,假定节点具有相同的传感和通信能力。短视路由并不自然适用于物联网,因为它可能导致能量失衡以及随后传感器网络寿命短暂,将传感器读数路由到服务最密集的传感器节点上,而让最不活跃的节点闲置。本文重新审视传感器网络中的能源效率问题,以提出一种聚类模型,其中传感器设备的服务交付被映射到一个能源感知模型中,用于设计一种聚类算法,该算法可在物联网环境中找到服务感知聚类(SAC)配置。性能评估揭示了所提出的SAC算法与相关路由算法相比在能耗、传感器节点寿命以及吞吐量和延迟方面的流量工程效率方面的相对能源效率。这些算法包括著名的低能耗自适应聚类分层协议(LEACH)和LEACH集中式(LEACH-C)算法,以及最新的算法,如DECSA和MOCRN。