A Novel Predictive Approach to Trajectory-aware Online Service Allocation in Mobile Edge Environment

The mobile edge computing (MEC) paradigm places traditional digital infrastructure next to mobile networks and thus drives substantial improvements in performance and latency for mobile computing cases like gaming, video streaming, and IoT. However, it remains a great challenge to provide a effictive and performance guaranteed strategies for services offloading and migration in the MEC environment. Most existing solutions in this direction tend to consider task offloading as a offline decision making process by employing transient positions of users as model inputs. In this work instead, we consider a predictive-trajectory-aware task offloading strategy called PreMig. Simulations clearly demonstrate that our proposed strategy outperforms traditional ones in terms of effective service rate and migration overhead.