HPCP-QCWOA: High Performance Clustering Protocol based on Quantum Clone Whale Optimization Algorithm in Integrated Energy System

Abstract

Combined with highly developed technologies such as cloud computing and the Internet of Things, the integrated energy system (IES) has realized the coordinated scheduling and utilization of various energy resources with its superiority of comprehensive control and high applicability. Meanwhile, approaches to enhance the quality of service (QoS), e.g. network lifetime, energy distribution, and data transmission delay, of an indispensable component of IES, i.e., integrated energy system wireless sensor networks (IESWSNs), have become an urgent research issue. To tackle the issue, a high-performance clustering protocol termed quantum clone whale optimization algorithm (HPCP-QCWOA) is proposed for IESWSNs. By designing a new quantum operator and a new layering clone operator, HPCP-QCWOA can find an approximate optimal clustering scheme to improve the QoS performance of IESWSNs. Unlike other population-based clustering protocols, a new objective function that embraces remaining energy, intra-cluster distance, BS distance, and data transmission delay is designed in the HPCP-QCWOA, which renders its clustering performance more desirable than some other state-of-the-art clustering protocols, i.e., O-LEACH, LDIWPSO, and ARSH-FATI-CHS. Empirically, simulation experiments under different scenarios illustrated that the lifetime of the HPCP-QCWOA-based clustering has increased by 28.78%, 25.50% and 11.22% respectively compared with O-LEACH, LDIWPSO, and ARSH-FATI-CHS.