This is one of the best survey papers I have ever come across. It provides a thorough review of resource scheduling algorithms (RSAs) with a particular focus on cloud computing. While the paper does not excel as a survey of RSAs, it does excel in providing a research methodology on how to conduct surveys of related work for a specific problem or research question, as well as a methodology and evaluation framework on how to make comparisons.

Given that cloud computing is well established, with its widespread adoption as one of the main computational platforms of the future, this paper is very timely. Scheduling the allocation of available resources to submitted workloads and establishing a well-balanced and fair distribution environment for all stakeholders are extremely difficult challenges as evidenced by the plethora of approaches and research conducted in this area. Although algorithms for optimizing resource allocation can be found in other areas and problems, perhaps with more details about the algorithmic design and performance analysis, this paper offers an evolutionary history of these RSA algorithms for resource scheduling of cloud computing resources.

The paper is very well structured in the following sections: introduction and motivation; background, stating the significance of resource scheduling as part of the resource management process for cloud computing environments; an excellent review approach and technique, providing data on how the final 114 research papers have been selected to be further considered for the survey; and a discussion of the results, including an excellent taxonomy of related RSAs with non-contextual comparisons and related RSA tools.

The paper concludes with discussions about open issues and challenges, benefits of cloud resource scheduling, and implications for research and practice. Therefore, the paper is highly recommended for all researchers and practitioners in cloud computing facing a resource scheduling challenge. However, those interested in more details about the underlying algorithms with regard to their design and performance analysis may feel a bit disappointed.