Measuring the impact of data center failures on a cloud‐based emergency medical call system

Abstract

Summary Emergency call services are expected to be highly available in order to minimize the loss of urgent calls and, as a consequence, minimize loss of life due to lack of timely medical response. This service availability depends heavily on the cloud data center on which it is hosted. However, availability information alone cannot provide sufficient understanding of how failures impact the service and users' perception. In this paper, we evaluate the impact of failures on an emergency call system, considering service‐level metrics such as the number of affected calls per failure and the time an emergency service takes until it recovers from a failure. We analyze a real data set from an emergency call center for a large Brazilian city. From stochastic models that represent a cloud data center, we evaluate different data center architectures to observe the impact of failures on the emergency call service. Results show that changing data center's architecture in order to improve availability from two to three nines cannot decrease the average number of affected calls per failure. On the other hand, it can decrease the probability to affect a considerable number of calls at the same time.

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

“…For more detailed information about data center tiers, see Reference . Please note that, in this article, we consider the tiers from I to III, once we have estimated the reliability values of these tiers in our previous work …”

“…Table presents the MTTF and MTTR values of hardware resources, power and cooling components. The MTTF and MTTR of the power supply and cooling source refer to a power and cooling subsystem under TIA‐942 Tier I to Tier III configurations.…”

DCAV: A software system to evaluate next‐generation cloud data center availability through a friendly graphical interface

“…Many enterprises have migrated their applications to the cloud infrastructure due to its flexibility, scalability, and high availability . Delivering this high availability level means keeping the service running 99.999% (five 9's) of the time during a year, ie, the service downtime should be less than 5.25 minutes per year . Service downtime not only negatively effects in user experience and brand loyalty but also directly translates into revenue loss; that is why cloud availability has been one of the biggest challenges for cloud providers.…”

“…The cooling subsystem of a data center can be implemented in several ways and using different technologies . However, in this work, we are considering a chilled water system, as used in some papers in literature, which consists of four main components: computer room air conditioning units (CRACs), chiller, cooling tower, and pipes. The chilled water system has a low cost for a data center that operates in 100 kW of electrical loads or less and are extremely reliable…”