Workflow is a prototype that executes the behavior of scientific and engineering applications for which the sequence of tasks needs to be automated based on the input parameters specified. Difficulties arise for CSPs primarily during the execution environment due to its direct impact on various QoS parameters. Existing workflow scheduling techniques has research focus with dimensions that include undetermined demands, task failure,l delay cost, ambiguous deadlines, bandwidth, cache inclusion, scheduler policies, VM cycles, QoS impact, OS support, fault-tolerant and virtualization level. The comparative analysis made in this paper for workflow scheduling strategies and tools used in the cloud environment towards QoS parameters would have a greater impact on industry task automation which in turn provides the researchers to set their objectives and tools to be used in-order to bring forth new approaches and solutions. This paper can be extended considering the research scope given in the comparative analysis and the data size pertaining to each task in workflow and data migration issues which cannot be done without cost, legal policies and technical issues.