  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.

Distributed, Parallel, and Cluster Computing