Abstract
The use of cloud computing for the better health care is more and more important. Patient's real-time physiological signals, such as electrocardiogram (ECG) and blood pressure, should be transmitted to hospital servers for remote monitoring, and stored in Data Centers (DCs) so that the authorized doctors are able to access the patient's disease history. This implies challenges in brokering between the cloud consumers and providers when a huge number of people gets the real-time services from the distributed medical organizations. This paper proposes a probability-based bandwidth model in a telehealth cloud system, which helps cloud broker to allocate the most efficient computing nodes and links. This brokering mechanism considers the location of Personal Health Record (PHR) in cloud and schedules the real- time signal with a low information transfer between different hosts. Furthermore, our broker uses a bandwidth evaluation for the model, and we also compare various predicting methods to obtain the best bandwidth allocating algorithm. We simulate an inter-host environment for measuring the performance of our bandwidth allocating method with various data coherence protocols, which controls the domain of PHR in cloud, and the results show that our model is effective at determining the best performing service, and the inserted service validates the utility of our approach.
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