  The vast data deluge at the network's edge is raising multiple challenges for
the edge computing community. One of them is identifying edge storage servers
where data from edge devices/sensors have to be stored to ensure low latency
access services to emerging edge applications. Existing data placement
algorithms mainly focus on locality, latency, and zoning to select edge storage
servers under multiple environmental constraints. This paper uses a data
placement framework to compare distance-based, latency-based, and
spatial-awareness-based data placement strategies, which all share a
decision-making system with similar constraints. Based on simulation
experiments, we observed that the spatial-awareness-based strategy could
provide a quality of service on par with the latency-based and better than the
distance-based strategy.
