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：随着物联网和5G网络的出现，边缘计算成为关注焦点。由于边缘设备资源受限，高计算需求的任务通常被卸载至云端。边缘云作为一个有前景的平台，使得设备能够卸载对延迟敏感的工作负载。在此背景下，调度在边缘云协同卸载决策中至关重要。调度的最终目标是提升体验质量、最小化延迟并提高性能。过去已有大量关于调度的研究工作。本文从优势与不足、QoS参数和容错性等多个方面，综述了边缘云计算背景下提出的调度策略。我们还评估了这些调度方法在不同情境下的适用性。首先，我们将所有算法分为启发式算法和元启发式算法，并在每个类别中根据算法提取的属性进一步细分。我们希望本综述能为新调度技术的发展提供深入见解。文中还探讨了现存问题、挑战及未来研究方向。