SRA-E-ABCO: Terminal Task Offloading for Cloud-Edge-End Environments

Abstract With the rapid development of Internet technology, the cloud-edge-end computing model has gradually become an essential new computing model. Under this model, terminal task offloading is crucial to task allocation and processing. Existing terminal task offloading solutions mainly focus on optimizing the offloading strategy to minimize system delay, transmission energy consumption, and computation energy cost. However, there are some problems such as the lack of a basis for judging whether to offload or not, the lack of analysis on the attributes of the terminal devices and the edge nodes, and the lack of optimization of load balancing. To address these issues, a Service Reliability Analysis and Elite-Artificial Bee Colony Offloading model (SRA-E-ABCO) is proposed for cloud-edge-end environments. Specifically, a Service Reliability Analysis (SRA) method is proposed to assist in predicting the offloading necessity of terminal tasks and analyzing the attributes of terminal devices and edge nodes. Subsequently, a set of vectors is derived based on the analysis. An Elite Artificial Bee Colony Offloading (E-ABCO) method is proposed, which optimizes offloading decisions by combining elite populations with improved fitness formulas, position update formulas, and population initialization methods. Experiments show that the proposed model has better performance in convergence, delay and energy consumption.