An Adaptive Redundant Reservation Strategy in Distributed High- performance Computing Environments

In distributed high-performance computing environments, resource reservation mechanism is an effective approach to provide desirable quality of service for large-scale applications. However, conventional reservation service might result in lower resource utilization and higher rejection rate if it is excessively applied. Furthermore, redundant reservation policy has been widely applied in many practical systems with aiming to improve the reliability of application execution at runtime. In this paper, we proposed an adaptive redundant reservation strategy, which uses overlapping technique to implement reservation admission and enable resource providers dynamically determine the redundant degree at runtime. By overlapping a new reservation with an existing one, a request whose reservation requirements can not be satisfied in traditional way might be accepted. Also, by dynamically determining the redundant degree, our strategy can obtain optimal tradeoff between performance and reliability for distributed high-performance computing systems. Experimental results show that the strategy can bring about remarkably higher resource utilization and lower rejection rate when using redundant reservation service at the price of a slightly increasing of reservation violations.