Caching Assisted Correlated Task Offloading for IoT Devices in Mobile Edge Computing

The fast-growing Internet of Thing (IoT) has generated a vast number of tasks which need to be performed efficiently. Owing to the drawback of the sensor-to-cloud computing paradigm in IoT, mobile edge computing (MEC) has become a hot topic recently. Against this backdrop, we focus on the offloading of tasks characterized by intrinsic correlations in this paper, which have not been considered in most of existing works. For the sequential arrival of such correlated tasks, the future workload can be efficiently reduced by caching the current computational result. Specifically, we resort to the Lyapunov optimization to handle the long-term constraint on energy consumption. Simulation results reveal that our approach is superior to other approaches in the optimization of response latency and energy consumption.