A Joint Offloading and Energy Cooperation Scheme for Edge Computing Networks
Jieyi Zhang, Biling Zhang, Jiahua Liu, Zhu Han · 2022
For edge computing (EC) network, one critical problem is how to process computation-intensive task in time with efficient energy usage. However, existing works mainly study one aspect of the problem by computation offloading or energy cooperation. Considering that the computation offloading strategy and the energy cooperation strategy are coupled with each other, in this paper, we propose a new information-energy collaboration model for the EC network powered by renewable energy and stored energy. In this new model, an EC node can collaborate with the other EC nodes and the cloud for computation offloading. At the same time, the EC is also able to store energy and share energy with other EC nodes. In such a case, since the EC nodes can have a stable power supply to finish the computing tasks within the latency limit, we formulate the problem of deriving the information-energy collaboration strategy as the optimization problem of minimizing the cloud computing cost and the power purchase cost. To find the optimal offloading and energy cooperation strategy, we first analyze the sixteen cases of the offloading strategy depending on the computing tasks and the renewable energy. Then we further summarize four cases of energy collaboration strategy according to the different offloading strategies. To derive the collaboration strategy with low complexity, we propose the practical Hybrid Greedy Iterative Algorithm (HGIA) to the optimization problem. Finally, the simulation results demonstrate that our approach is effective and stable.