A Proximal Algorithm for Fork-Choice in Distributed Ledger Technology for Context-Based Clustering on Edge Computing

The major challenges of operating data-intensive of Distributed Ledger Technology (DLT) are 1) To reach consensus on the main chain is a set of validators cast public votes to decide on which blocks to finalize and 2) scalability on how to increasing the number of chains which will be running in parallel. In this paper, we introduce a new proximal algorithm that scales DLT in a large scale IoT devices network. We discuss how the algorithm benefits the integrating DLT in IoT by using edge computing technology, taking the scalability and heterogeneous capability of IoT devices into consideration. IoT devices are clustered dynamically into groups based on various proximity context information. A cluster head is used to bridge the IoT devices with the DLT network where the smart contract is deployed. In this way, the security of the IoT is improved and the scalability and latency are solved. We elaborate our mechanism and discuss issues that should be considered and implemented when using the proposed algorithm even we show its behaves when varying parameters like latency or when clustering.