Tariq Ahamed Ahanger

Internet of Things (IoT) technology has uncovered a wide range of possibilities in several industrial sectors where smart devices are capable of exchanging real-time data. Machine-to-machine (M2M) data exchange provides a new method for connecting and exchanging data among machine-oriented communication entities (MOCE). Conspicuously, network services will be severely affected if the underneath IoT infrastructure is disrupted. Moreover, it is difficult for MOCEs to re-establish connectivity automatically. Conspicuously, in the current paper, an analysis is performed regarding potential technologies including unmanned aerial vehicles, blockchain, and mobile edge computing (MEC) that can enable the secure establishment of M2M communications networks that have been compromised to maintain the secure transmissible data. Furthermore, a Markov decision process-based joint optimization approach is proposed for blockchain systems that aims to elevate computational power and performance. Additionally, the dueling deep Q-network (DDQ) is incorporated to address the dynamic and complex optimization issue so that UAV selection is ensured to maximize performance. The results of experimental simulation with several statistical attributes suggest that the proposed framework can increase throughput optimally in comparison to state-of-the-art techniques. Additionally, a performance measure of reliability and stability depicts significant enhancement for the proposed framework.

The Blockchain (BCT) is the first decentralized ledger to include a trust mechanism in its design. It establishes a trustworthy framework for distributed commands by using data redundancy at several nodes. Conspicuously, the current study presents a BCT-based lightweight IoT information exchange security architecture for data exchange. The proposed technique uses a dual chain methodology, namely transaction and data BCT working together to provide distributed storage and tamper-proofing of data. Moreover, Transaction BCT is enhanced by a consensus algorithm using a practical Byzantine fault-tolerant (PBFT) mechanism. The proposed algorithm can increase data registering efficiency, transactions, and privacy protection BCT. It is deduced that local dominance can be avoided using the dynamic game strategy of node cooperation. Furthermore, by reporting the node’s global reputation value, the status of the unknown node may be approximated. The high-trust measure is utilized to adjust the weight of the affected node in the combined node-set, leading to the Bayesian equilibrium. The proposed model is validated in several experimental simulations and results are compared with state-of-the-art techniques. Based on the results, enhanced performance is registered for the proposed techniques in terms of temporal delay, statistical efficiency, reliability, and stability.