Fuzzy Logic based Congestion Aware Routing Protocol for Wireless Sensor Network
Keywords:
Fuzzy Logic, Wireless Sensor Networks (WSN), Congestion Aware Routing, Fuzzy Inference System, Energy Efficiency, Packet Delivery RatioAbstract
Wireless Sensor Networks (WSNs) consist of resource-constrained sensor nodes that collaboratively monitor environmental and physical conditions. Due to limited bandwidth, energy constraints, and dynamic traffic patterns, congestion remains a critical challenge in WSNs, leading to packet loss, increased delay, and reduced network lifetime. Traditional congestion control and routing protocols often rely on fixed threshold mechanisms, which are insufficient in handling uncertain and dynamic network conditions. To address these limitations, this paper proposes a Fuzzy Logic-Based Congestion Aware Routing Protocol for Wireless Sensor Networks. The proposed approach utilizes fuzzy inference systems to evaluate congestion levels based on multiple input parameters such as buffer occupancy, packet arrival rate, queue length, residual energy, and channel load. By applying fuzzy rules and membership functions, the protocol dynamically selects optimal routing paths while avoiding congested nodes. This adaptive decision-making mechanism enhances packet delivery ratio, reduces end-to-end delay, and balances energy consumption across the network. Simulation results demonstrate that the proposed fuzzy-based routing protocol outperforms conventional congestion-aware and shortest-path routing algorithms in terms of throughput, network lifetime, and energy efficiency. The integration of fuzzy logic enables robust performance under uncertain traffic conditions, making it suitable for real-time and large-scale WSN deployments.
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