Fig. 1

The framework of time-varying context-aware offloading based on neutrosophic set. We consider a three-tier cloud-edge hybrid computation offloading environment (which is depicted in the right part), consisting of a central cloud, some cloudlets and some mobile devices. Computational tasks can be executed at these three locations. The framework, from bottom to top, has three levels: (1) Obtaining historical contextual time-varying data. These contextual data includes four types, include CPU utilization, load, network latency and the expected residence time within the cloudlet. (2) A novel presentation model of time-varying context. The time-varying data of contextual attributes are dynamic and imprecise. We use a neutrosophic set (NS) model to describe such uncertain fuzzy information and generate a single-valued NS for each contextual attribute of cloudlets. (3) The best cloudlet selection through a series operations of NS. That is, first, we calculate the weight of each context attribute. we calculate the weight of each context attribute. Then, we use the single valued NS weighted average aggregation operator to aggregate the SVNS of cloudlets into the single-valued neutrosophic number of cloudlets. Finally, we select the best cloudlet using the NS score function