  To support the stringent requirements of the future intelligent and
interactive applications, intelligence needs to become an essential part of the
resource management in the edge environment. Developing intelligent
orchestration solutions is a challenging and arduous task, where the evaluation
and comparison of the proposed solution is a focal point. Simulation is
commonly used to evaluate and compare proposed solutions. However, the
currently existing, openly available simulators are lacking in terms of
supporting the research on intelligent edge orchestration methods. To address
this need, this article presents a simulation platform called Edge Intelligence
Simulator (EISim), the purpose of which is to facilitate the research on
intelligent edge orchestration solutions. EISim is extended from an existing
fog simulator called PureEdgeSim. In its current form, EISim supports
simulating deep reinforcement learning based solutions and different
orchestration control topologies in scenarios related to task offloading and
resource pricing on edge. The platform also includes additional tools for
creating simulation environments, running simulations for agent training and
evaluation, and plotting results.

Distributed, Parallel, and Cluster Computing;Multiagent Systems