Self-Interested Load Announcement by Edge Servers: Overreport or Underreport?

In mobile edge computing (MEC), customers (e.g., mobile devices) can offload computational-intensive tasks to edge servers to achieve low processing latency. However, an edge server can be self-interested as part of the MEC business ecosystem. It may misreport the expected waiting time (at edge servers) to the customers to increase its payoff. In this work, we formulate a two-stage game to investigate the misreporting behavior. In Stage I, the edge server decides a misreporting coefficient for untruthfully announcing the expected waiting time. In Stage II, when a customer has a new task arrival, it decides whether to offload the task or not based on its patience. Overcoming the challenge of the stochastic task arrivals in Stage II, we determine the rate of the task arrivals offloaded to the edge server. Overcoming the challenge of the nonconvexity of Stage I problem, we prove the existence and uniqueness of the optimal misreporting coefficient. Meanwhile, we prove that as the customers' patience increases, the edge server's optimal misreporting coefficient increases, while its optimal payoff remains unchanged. Our experimental results with real-world datasets show that the traffic intensity threshold that separates the situations of overreporting and underreporting is around 0.5 - 0.9.