Browsing by Author "Kiran M."

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    Baud Rate-Based Hierarchical Multihop Routing Protocol for WSNs
    (2020) Sowmya G.V.; Kiran M.
    In wireless sensor networks (WSNs), the data sensed by the sensor node are forwarded to the sink node either by direct communication or by multihop communication. The disadvantage of direct communication is that the sensor nodes consume more energy to reach the sink node as each sensor node has to work alone to reach the sink node, and if the sink node is too far, condition gets worsens. Contrary to direct communication, the multihop communication saves energy as it forwards the data to the nearest neighbor node which in turn forwards the data toward the sink node. In multihop communication, choosing the best neighbor node for forwarding the data is the most challenging task. Hence, in this article, a novel hierarchical multihop routing protocol for WSNs referred to as “Baud Rate-Based Hierarchical Multihop Routing Protocol for WSNs” has been proposed which uses Shannon channel capacity model ‘C’ and neighbor node distance to choose the best neighbor node; the chosen neighbor node will be capable of transmitting data with high baud rate, thereby increasing the throughput of the network. Further, the proposed model also increases the lifetime of the network as the nearest neighbor node will be chosen for the data transfer which saves the energy of the sensor node. The proposed algorithm is compared against the LEACH routing protocol and multihop LEACH protocol and is implemented in MATLAB. The quantitative and qualitative analysis of the simulation results depicts that the proposed algorithm performs better against the parameters remaining energy of the sensor nodes, network lifetime, and data throughput when compared to LEACH and multihop LEACH protocols. © 2020, Springer Nature Singapore Pte Ltd.
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    Peer Consonance in Blockchain based Healthcare Application using AI-based Consensus Mechanism
    (2020) Kumar N.; Parangjothi C.; Guru S.; Kiran M.
    The term 'Blockchain', commonly referred to as the brain behind the Bitcoin network, works on the simple principle of the presence of a distributed and decentralized ledger in a public or private network. Since blockchain is decentralized, it is the duty of the Consensus Algorithm to substantiate the details in the blockchain. Traditional consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS), although widely used, are a matter of concern due to computationally expensive operations and convergence towards a monopolized system respectively. Though optimizations of PoW and PoS algorithms were subsequently introduced, their features precincts. This paper aims to provide a solution by presenting a consensus algorithm based on Artificial Intelligence (AI) technology while maintaining the fairness of the system. A Healthcare based system was set up on top of the blockchain network to generate the dataset about the miners in order to train our neural network. On the whole, it incorporated the advantages of the state of the art consensus models which can increase the efficiency of the healthcare industry while diminishing their demerits. © 2020 IEEE.