The Use of Cloud Computing in Health Care
Open Access
- Author:
- Rauscher, Richard L
- Graduate Program:
- Computer Science and Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- April 02, 2015
- Committee Members:
- Raj Acharya, Dissertation Advisor/Co-Advisor
Raj Acharya, Committee Chair/Co-Chair
Padma Raghavan, Committee Member
Eugene Joseph Lengerich, Committee Member
Wang Chien Lee, Committee Member - Keywords:
- cloud computing
health care
healthcare
virtual machines
VMMA
Bell-LaPadula
data leakage - Abstract:
- Attaining computational efficiency in health care is becoming increasingly important. Currently, 17.9% of the GDP of the United States is spent on health care. It is an information intense industry, and, through private and governmental incentives, is increasingly using digital information to manage care. Cloud computing and computer virtualization have complicated the decision process around how to architect solutions for health care. Health care decision makers must seek to minimize their spending while ensuring sufficient computational capacity, regulatory compliance and security. The intensity of the use of digital information in health care is expected to increase rapidly. This dissertation makes several contributions to the fields of health care informatics and computer science. We first established motivation for studying this area by examining the attitudes of health care technology leaders throughout the United States. This research led us to believe that many health care organizations will continue to make use of private clouds for some time. Given this assumption, we examined how the predictability of health care workloads could be used to improve the use of private cloud computing infrastructures. Using historic resource requirements as a guide, we constructed an algorithm that could be used to by systems architects to make better informed hardware allocation decisions. Continuing to use the concept of predictability, we created a system that dynamically migrated virtual machines within a private cloud in expectation of increased workload. This preemptive migration based on history-generating foresight reduced the overhead associated with other trigger-based migration schemes of up to 99.6%. The original survey also indicated that health care technology leaders were concerned about security and the changing regulations associated with data leakages. Our research focus shifted to reducing the risk of data leakage in hybrid computing clouds. We devised a mechanism that prohibited layer three network communications between different network zones to reduce the risk of data leakage while ensuring, to the extent practical, that traditional multilevel security rules could be implemented. Finally, we proposed mechanisms required to successfully deploy health care data in a dynamic Intercloud such that data could move freely between private and various public cloud providers.