  Offloading high-demanding applications to the edge provides better quality of
experience (QoE) for users with limited hardware devices. However, to maintain
a competitive QoE, infrastructure, and service providers must adapt to users'
different mobility patterns, which can be challenging, especially for
location-based services (LBS). Another issue that needs to be tackled is the
increasing demand for user privacy protection. With less (accurate) information
regarding user location, preferences, and usage patterns, forecasting the
performance of offloading mechanisms becomes even more challenging. This work
discusses the impacts of users' privacy and mobility when offloading to the
edge. Different privacy and mobility scenarios are simulated and discussed to
shed light on the trade-offs (e.g., privacy protection at the cost of increased
latency) among privacy protection, mobility, and offloading performance.
