University of Bahrain
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Shortest Path Optimization for Determining Nearest Full Node from a Light Node in Blockchain IoT Networks

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dc.contributor.author Anand M, Vivek
dc.contributor.author S, Srinivasan
dc.date.accessioned 2024-06-15T13:54:07Z
dc.date.available 2024-06-15T13:54:07Z
dc.date.issued 2024-06-15
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/5763
dc.description.abstract In a blockchain IoT network, there exists a diversity of devices, including full nodes and light nodes, each with varying capacities and roles. Full nodes have the capability to store the entire ledger, whereas light nodes, constrained by limited memory capacity, cannot store. However, light nodes can efficiently retrieve data from full nodes and actively participate in network transaction approvals, especially in critical applications such as military and healthcare sectors. To enable light nodes to approve transaction by verifying blockchain ledgers we need to determine the nearest distance from a light node to a full node is imperative. While several algorithms exist for this purpose, Routing Protocol for Low-Power and Lossy Networks (RPL) emerges as the optimal choice. In comparison to other algorithms like Dijkstra’s Algorithm, Floyd-Warshall Algorithm, Genetic Algorithms (GA), and Ant Colony Optimization (ACO), RPL stands out with distinct advantages. While Dijkstra’s Algorithm and Floyd-Warshall Algorithm excel in finding shortest paths, they may not be optimized for the unique constraints and dynamics of IoT networks. Genetic Algorithms (GA) offer heuristic solutions but may lack adaptability to real-time changes in network topology, while Ant Colony Optimization (ACO) may face scalability and resource constraints in IoT environments. Conversely, RPL is meticulously tailored for low-power and lossy networks inherent to IoT settings. Its capability to form Directed Acyclic Graphs (DAGs) and dynamically adjust routes based on metrics like hop count and energy efficiency positions it as an ideal choice for determining the nearest distance between light nodes and full nodes in a blockchain IoT network. By capitalizing on its adaptability and efficiency, RPL surpasses other algorithms in enabling efficient data retrieval and facilitating network transaction approvals, thereby ensuring the seamless operation of blockchain IoT systems. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject IoT networks, Directed Acyclic Graph (DAG) topology, DODAG Information Object (DIO) Messages, Destination Advertisement Object (DAO) Messages en_US
dc.title Shortest Path Optimization for Determining Nearest Full Node from a Light Node in Blockchain IoT Networks en_US
dc.identifier.doi http://dx.doi.org/10.12785/ijcds/XXXXXX
dc.volume 16 en_US
dc.issue 1 en_US
dc.pagestart 1 en_US
dc.pageend 10 en_US
dc.contributor.authorcountry India en_US
dc.contributor.authorcountry India en_US
dc.contributor.authoraffiliation Research Scholar, Galgotias University en_US
dc.contributor.authoraffiliation Professor, School of Computing Science and Engineering, Galgotias University en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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