Abstract

Wireless Sensor Networks (WSNs) is an emerging field that enables them to work in complex scenarios with enough flexibility. The WSN systems are improved in terms of network flexibility by integrating Software Defined Network (SDN) to obtain SDWSN environment. However, security and energy efficiency are the major issues in the SDWSN environment which leads to low network lifetime. To resolve the existing issues, we proposed DAG-based BLOCKchain-Routing and Load Balancing Model (DBLOCK-RLB). The proposed approach performs routing and load balancing in the SDWSN environment in an energy efficient manner with high security. The SDWSN environment is composed of four major planes as data plane, switch plane, control plane, and application plane. The sensor nodes in the data plane are authenticated priory to ensure legitimacy and reduce unwanted network traffics by adopting Camellia Encryption Algorithm (CAE) which provides secret key to the user by considering several metrics. The authenticated sensor nodes are clustered to reduce energy consumption using Adaptive Threshold based Network Partitioning in which the circular SDWSN environment is split into equal parts and optimal Cluster Head selection is done by considering clustering metrics. From the clustered network, the CH is responsible for intelligent routing. For intelligent routing, we utilize Dual Agent-Twin Delayed Deep Deterministic Policy Gradient (DA-TD3) in which one agent for optimal forwarder selection and another agent for optimal route selection. After routing, the load balancing is done to reduce the network overhead and scalability issues. The proposed work performs trading based load balancing by utilizing Stackelberg Game Model in which all the local controllers are considered as followers and global controller is considered as leaders. All the transactions are stored in the DAG blockchain to reduce the scalability and Proof-of Authentication (PoAH) used to verify the transactions. The proposed work is simulated using NS-3.26 simulation tool and compared with several existing works by validation metrics like throughput at 2.55(mbps), latency at 27.1(ms), packet delivery ratio at 91.5(%), network Lifetime at 546.5(s), and energy consumption at 14.5 (J). The results show that the proposed work outperforms better than the existing works.

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