An Improved Energy-Efficient Clustering Protocol to Prolong the Lifetime of the WSN-Based IoT

Ali Abdul Hussian Hassan, Wahidah Md Shah, Abdul Hussien Hassan Habeb, Mohd Fairuz Iskandar Othman, Mohammed Nasser Al-Mhiqani

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)


A wireless sensor network (WSN) is an important part of the Internet of Things (IoT). However, sensor nodes of a WSN-based IoT network are constraining with the energy resources. A clustering protocol provides an efficient solution to ensure energy saving of nodes and prolong the network lifetime by organizing nodes into clusters to reduce the transmission distance between the sensor nodes and base station (BS). However, existing clustering protocols suffer from issues concerning the clustering structure that adversely affects the performance of these protocols. In this study, we propose an improved energy-efficient clustering protocol (IEECP) to prolong the lifetime of the WSN-based IoT. The proposed IEECP consists of three sequential parts. First, an optimal number of clusters is determined for the overlapping balanced clusters. Then, the balanced-static clusters are formed on the basis of a modified fuzzy C-means algorithm by combining this algorithm with a mechanism to reduce and balance the energy consumption of the sensor nodes. Lastly, cluster heads (CHs) are selected in optimal locations with rotation of the CH function among members of the cluster based on a new CH selection-rotation algorithm by integrating a back-off timer mechanism for CH selection and rotation mechanism for CH rotation. In particular, the proposed protocol reduces and balances the energy consumption of nodes by improving the clustering structure, where IEECP is suitable for networks that require a long lifetime. The evaluation results prove that the IEECP performs better than existing protocols.

Original languageEnglish
Article number9247097
Pages (from-to)200500-200517
Number of pages18
JournalIEEE Access
Early online date3 Nov 2020
Publication statusPublished - 16 Nov 2020
Externally publishedYes

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