Dynamic Task Offloading for Mobile Edge Computing with Hybrid Energy Supply

Mobile edge computing (MEC), as a new distributed model, satisfies the low energy consumption and latency requirements of computation-intensive services. The task offloading MEC has become an important research hotspot, it solves problems insufficient capability battery capacity Internet things (IoT) devices. This study investigates scheduling in dynamic system. By integrating harvesting technology into IoT devices, we propose hybrid supply model. We jointly optimize local computing, duration, decisions to minimize system cost. On basis stochastic optimization theory, design online algorithm for with called DTOME. DTOME can make by weighing cost queue stability. quote programming theory obtain optimal strategy. Simulation results verify effectiveness DTOME, show that entails lower than two baseline strategies.