CEDAR: A cluster-based energy-aware data aggregation routing protocol in the internet of things using capuchin search algorithm and fuzzy logic

Over the last decade, the Internet of Things (IoT) has received much interest from the research and industrial communities due to its fundamental role in altering the human lifestyle and giving extraordinary privileges to them. As an ever-expanding ecosystem, the IoT transforms physical items into intelligent objects capable of collecting, exchanging, and processing information. The transmission of huge amounts of data produced by sensor nodes is the most prominent challenge for IoT-enabled networks. The lifetime of nodes is jeopardized due to excessive consumption of communication power. Therefore, offering solutions for network-based problems, including quality of service, security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation, has become critical. Routing protocols are crucial in addressing the aforementioned issues in data transmission among heterogeneous items. In this regard, data aggregation approaches play an essential role in collecting and aggregating information to reduce traffic congestion, overhead, energy consumption, and network lifetime. Developing reliable, energy-efficient, and delay-aware route planning is challenging in data aggregation scenarios for IoT applications. The current study proposes a Cluster-based Energy-aware Data Aggregation Routing (CEDAR) protocol in the IoT to cover these challenges by combining Capuchin Search Algorithm (CapSA) and fuzzy logic system. The proposed hybrid routing algorithm consists of two main phases, including cluster formation and intra/extra cluster routing. The experimental results using the Matlab simulator indicate that CEDAR outperforms previous works regarding network lifetime, packet delivery ratio, end-to-end delay, and energy consumption.