D2D Computation Offloading Optimization for Precedence-Constrained Tasks in Information-Centric IoT

This paper proposes a computation offloading scheme for precedence-constrained tasks in a base station-assisted device-to-device (D2D) scenario for the information-centric Internet of Things (IC-IoT). When specified precedence among subtasks cannot be described as simple sequential or parallel relations in a task, the selection of task execution helper for subtasks offloading becomes complex due to the constraints of latency and resources. We define this type of precedence and aim to minimize the time and financial cost of computation task offloading for the user by optimizing subtask-helper pairs. This problem is modeled as a dynamic generalized multi-resource-constrained assignment problem. The optimal offloading policy is offered by searching minimum weight matchings in a bipartite graph. Computer simulations indicate the effectiveness of the proposed approach compared with the random helper selection and priority-based offloading scheme.