A Simulation Study of Response Times in Cloud Environment for IoT-Based Healthcare Workloads

Internet-of-Things (IoT) is revolutionizing the healthcare by providing high-quality services, lowering the costs, and increasing the efficiency of management by allowing the physical objects to integrate with computer systems to collect the sensed data and process as per the need. Healthcare industries will also get benefited due to reduced investments and management, automated services, better disease diagnosis/analysis, and minimum operations and maintenance. Wireless Body Area Network (WBAN), an element of IoT, enables several sensor nodes attached to a body that generates enormous volumes of healthcare data over the period of a patient. In life-critical pervasive healthcare applications, the data rates from the WBAN is unpredictable, requiring uneven resources in short time intervals to provide qualitative services. Cloud is abundant with pooled resources ready to meet such unpredictable workloads and rapidly deployable to handle massive amounts of data. This paper presents a mechanism that assesses the default resource allocation strategy regarding its response time in simulated IoT healthcare workloads which will raise irregular requirements of the resources from the cloud to handle massive amounts of data. Several experiments are conducted to study the optimal virtual machine allocation to meet the irregular resource requirements from cloud to suit to WBAN, the IoT scenario. Finally, the paper concludes with the reported results.