The presence of high-performance multicore embedded architectures, energy efficiency remains a research black hole. Previous algorithms like Dynamic-based Frequency Scaling models and mapping-based thread models were implemented in microarchitecture to efficiently use clock frequency and energy. Unfortunately, these methods raise the problem of data traffic and high execution time. To overcome these drawbacks, a solution model analyzed load in the multiprocessor and migrated them to the proper Core to give an efficient data transfer rate. To perform this, an African Buffalo Load Migration Communication (ABLMC) system model has been presented in this paper. This unit analyses the workload characteristics of the multicore processor in the dynamic IoT environment application layer. Workload parameters are taken as features and computed for their similarity with minimum execution time using optimization. The predicted score value has been then given to the ABLMC model to take migrating decisions on loads. Communication requires a high data transfer rate that was achieved in a multicore processor using this ABLMC model. The proposed framework has been implemented and tested in a MATLAB environment with the performance matrices of high Data transfer rate and minimum execution time of 1.6 s. Thus, the proposed framework has excellence in real-time applications.