Type-2 Neutrosophic Set and Their Applications in Medical Databases Deadlock Resolution

Electronic patient data gives many advantages, but also new difficulties. Deadlocks may delay procedures like acquiring information. Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties. Soft computing-based have been developed solve this challenge. In a single framework, ambiguous, vague, incomplete, and inconsistent attribute information has received minimal attention. The work presented in paper employed type-2 neutrosophic logic, an extension of type-1 handle real-time deadlock-resolving systems. proposed method is structured reflect multiple types knowledge relations among transactions’ features that include validation factor degree, slackness degree deadline-missed based on the membership truthiness, indeterminacy, falsity. Here, footprint (FOU) for truth, falsity represents level exists value grade membership. We distributed processing simulator (DRTTPS) conduct simulations conducted experiments using benchmark Pima Indians diabetes dataset (PIDD). As results showed, there increase detection rate large drop rollback when strategy used. performance Type-2 neutrosophic-based better than Type-1 approach execution ratio scale. improvement reached 10% 20%, depending number arrived transactions.