Cache-Aware Computation Offloading in IoT Systems

In the Internet of Things (IoT) environment, due to the limited computing power of terminal equipment, edge-cloud computing is a good solution for sharing the computation resources. Terminals can offload partial computations to the edge servers for energy saving and reduce the data transmission delays since the edge servers are usually deployed near the terminal devices. However, in the existing solutions, there is still a lot of unnecessary data transmission when the data used in the offloading jobs of several terminals are related. Adding a shareable cache to the edge server and allowing different computing jobs to share the related data can further reduce the data transmission cost and job delay. In this paper, we study the computation offloading method with cached data and propose a novel cache-aware computation offloading strategy for edge-cloud computing in IoT. First, we formulize the cache-aware computation offloading location problem, our goal is to minimize the equivalent weighted response time of all jobs with computing power and cache capacity constraints. Then, we derive the global optimum solution based on transforming the problem to the transportation problem. Next, since the terminal device is difficult to obtain global status information, we propose an online computation offloading strategy, which is convenient in practical deployment. Finally, experiments show that our online offloading strategy approximates the global optimal solution and it reduces the weighted response time by about 26.13% on average compared to other competing algorithms.