A novel energy-aware bio-inspired clustering scheme for IoT communication
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ORIGINAL RESEARCH
A novel energy‑aware bio‑inspired clustering scheme for IoT communication Yefei Zhang1 · Yichuan Wang1 Received: 17 May 2019 / Accepted: 7 January 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Nowadays, the internet of thing (IoT) is a novel paradigm that is rapidly gaining ground in the scenario of modern wireless telecommunications. Wireless sensor network (WSN) is an important part of IoT, and it is mainly responsible for acquiring and reporting data. As lifetime and coverage area of WSN directly determine IoT performance, how to design a method to conserve nodes energy and reduce nodes death rates become important issues. Sensor network clustering is one efficient method to solve these problems. It divides nodes into clusters and selects one to be cluster head (CH). The data transmission and communication within one cluster are managed by its CH. Many traditional strategies have been designed out, but because of network dynamic feature, machine learning methods become more attractive and many literature are working on them. Particle swarm optimization (PSO) is one evolutionary algorithm. Inspired by this algorithm, we propose a novel energy-aware bio-inspired clustering scheme (PSO-WZ). We firstly initialize CHs combination randomly and assign non-CHs based on division rules. Then, using the fitness function to guide the selection process until the maximum time is reached. Since the division rule is directly related with the network topology and node energy consumption distribution, we design it from two angles: non-CHs and the whole network, to save the energy of each node as much as possible. Meanwhile, in order to balance energy load among nodes, which contributes to lowering nodes reduction and preserving network coverage range, we introduce the Gini coefficient into the objective function. From the results obtained, we conclude that the proposed algorithm is able to keep more nodes alive over time, prolong the network life cycle, and improve the overall performance of IoT further. Keywords IoT · WSN · PSO · Gini coefficient · Connectivity and coverage
1 Introduction Internet of Thing (IoT) is a term commonly used to identify a system consisting of unique identifiable objects, autonomous in nature and able to connect to the Internet to present and exchange real-world information in a digital form (Kruger and Hancke 2014; Kim et al. 2017). It is aimed at enabling everything (i.e. including live objects) to be accessible, sensed, and interconnected by Internet in the future. The development of IoT depends on a number of new technologies, such as WSNs, cloud computing and information
* Yichuan Wang [email protected] Yefei Zhang [email protected] 1
Xi’an University of Technology, Xi’an, China
sensing. In IoT-based information systems, a low-cost data acquisition system is necessary to effectively collect and process the data and information at IoT end nodes (IENs) (Li et al. 2013). Regarding this notion, the wireless sensor network (WSN) plays an
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