IDCT: Intelligent Data Collection Technique for IoT-Enabled Heterogeneous Wireless Sensor Networks in Smart Environments

• Published in: IEEE sensors journal 2021-09, Vol.21 (18), p.21099-21112
• Main Authors: Osamy, Walid, Salim, Ahmed, Khedr, Ahmed M., El-Sawy, Ahmed A.
• Format: Article
• Language: English
• Subjects: Algorithms; Approximation algorithms; bees based algorithm; Computer science; Data collection; dominating set; Energy; Energy consumption; Energy management; Environmental monitoring; Heterogeneous wireless sensor networks (HWSNs); Heuristic algorithms; network lifetime; Nodes; Optimization; Sensors; Swarm intelligence; the Internet of Things (IoT); the IoT-enabled WSN; Wireless networks; Wireless sensor networks
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2021.3100339

Wireless Sensor Networks (WSNs) lend themselves to a wide variety of applications in our daily lives, such as environmental monitoring, safety, health-care, animal monitoring, etc. However, one of the key issues in WSN is energy constraints. This makes energy-conservation one of the major keys to the efficient functioning and lifetime of WSN. In this paper, given a network of nodes with heterogeneous energy, our goal is to determine energy-aware disjoint dominating sets (DSs) that work as data collection nodes in each round, to improve overall WSN lifetime. In order to accomplish this goal, we propose an intelligent data collection technique with two phases, the collector nodes selection, and the data gathering path formation and collection phases. In the collector nodes selection phase, an energy-aware algorithm based on swarm intelligence is proposed to construct disjoint dominating sets that work as collector nodes in each round. In the data gathering path formation and collection phase, data gathering path is determined for achieving maximal data collection efficiency and reduced energy consumption. The efficiency of our proposed technique is proved mathematically and through simulations.