A Deadline-Constrained Multi-Objective Task Scheduling Algorithm in Mobile Cloud Environments

By leveraging the technology of the mobile cloud computing, resource capacity, and computing capability of mobile devices could be extended. However, it is difficult to schedule tasks submitted by mobile users when the number of tasks and service providers increases and to optimize multiple objectives while satisfying users’ requirements. In this paper, the task scheduling is modeled as a multi-objective optimization problem, and we consider both unconstrained and time deadline constrained cases. To address this problem, a heterogeneous earliest finish time (HEFT) using technique for order preference by similarity to an ideal solution method is proposed, which is named as HEFT-T algorithm. For the unconstrained case, a three-stage strategy based on HEFT-T algorithm is presented to select the optimal solutions by applying non-dominated sorting approach. For the deadline-constrained case, an adaptive weight adjustment strategy based on HEFT-T is proposed to adjust weight value for time. Compared with other of the state-of-the-art algorithms, our proposed algorithm performs better in the criterion of both the optimization for total cost as well as mean load, and the deadline-constraint meeting rate.