Day by day the numbers of Internet of Everything (IoE) devices are increasing which produce massive amounts of data every day. Cloud computing handles such massive amount of data. Cloud computing is a model that provides on-demand computing, storage, and network resources with little or no interaction from service providers. A challenging issue in the cloud is resource scheduling and delay optimization to enhance cloud service providers' profits by ensuring the quality of services (QoS) demanded by users. Particularly in smart health care the response time plays an important role. In this paper, a task scheduling algorithm is proposed which assigns the resources based on the priority. The requests are classified into three categories highly delay sensitive, moderate delay sensitive and low delay sensitive based on the attribute values like blood pressure, heart rate and temperature. The execution time is then optimized by setting a threshold value in order to provide services with less delay. The overall performance is increased by 40.1% compared to other scheduling methods
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