After the advent of the Internet of Things and 5G networks, edge computing became the center of attraction. The tasks demanding high computation are generally offloaded to the cloud since the edge is resource-limited. The Edge Cloud is a promising platform where the devices can offload delay-sensitive workloads. In this regard, scheduling holds great importance in offloading decisions in the Edge Cloud collaboration. The ultimate objectives of scheduling are the quality of experience, minimizing latency, and increasing performance. An abundance of efforts on scheduling has been done in the past. In this paper, we have surveyed proposed scheduling strategies in the context of edge cloud computing in various aspects such as advantages and demerits, QoS parameters, and fault tolerance. We have also surveyed such scheduling approaches to evaluate which one is feasible under what circumstances. We first classify all the algorithms into heuristic algorithms and meta-heuristics, and we subcategorize algorithms in each class further based on extracted attributes of algorithms. We hope that this survey will be very thoughtful in the development of new scheduling techniques. Issues, challenges, and future directions have also been examined.

翻译：在事物互联网和5G网络的出现之后,边缘计算成为吸引的中心。要求高计算的任务通常会从云层上卸下,因为边缘是有限的资源。 边缘云是一个很有希望的平台, 设备可以卸下延迟敏感的工作量。 在这方面, 排期对于在边云合作中卸载决定非常重要。 排期的最终目标是经验的质量, 尽量减少潜伏, 提高性能。 过去已经做了大量关于排期的努力。 本文中, 我们调查了在边缘云计算方面, 诸如优势和偏差、 QOS 参数和差错容度等各个方面的拟议排期战略。 我们还调查了这种排期方法, 以评估在什么情况下可行的方法。 我们首先将所有算法归为超自然算法和超常法, 然后我们根据抽取的算法属性将算法进一步分解为每个班级。 我们希望这项调查在开发新的排期技术时会非常周到。 我们还研究了问题、 挑战和未来方向。