DescriptionA well-known challenge in Edge Computing is strategic placement of cloudlets. The fundamental goals of this challenge are to minimize the cloudlet deployment cost and to guarantee minimum latency to the users of edge services. We address this challenge by designing a cost-aware cloudlet placement approach that that ensures user latency requirements while covering all devices in the service region. We first mathematically formulate the problem as a multi-objective integer programming model in a general deployment scenario, which is computationally NP-hard. We then propose a genetic algorithm-based approach, GACP, to find heuristic solutions in significantly reduced time. We investigate the effectiveness of GACP by performing extensive experiments on multiple deployment scenarios based on New York City OpenData. The results presented in the poster show that our approach obtains close to optimal cost solutions with significant time reduction.