High-Availability Computing Platform with Sensor Fault Resilience

Abstract

Modern computing platforms usually use multiple sensors to report system information. In order to achieve high availability (HA) for the platform, the sensors can be used to efficiently detect system faults that make a cloud service not live. However, a sensor may fail and disable HA protection. In this case, human intervention is needed, either to change the original fault model or to fix the sensor fault. Therefore, this study proposes an HA mechanism that can continuously provide HA to a cloud system based on dynamic fault model reconstruction. We have implemented the proposed HA mechanism on a four-layer OpenStack cloud system and tested the performance of the proposed mechanism for all possible sets of sensor faults. For each fault model, we inject possible system faults and measure the average fault detection time. The experimental result shows that the proposed mechanism can accurately detect and recover an injected system fault with disabled sensors. In addition, the system fault detection time increases as the number of sensor faults increases, until the HA mechanism is degraded to a one-system-fault model, which is the worst case as the system layer heartbeating.

An Enhanced Lightweight Security Gateway Protocol for the Edge Layer

“…Transient faults are very hard to prevent because they occur for a limited duration due to many reasons (including malfunctioning, power outage, a network being busy, and so on), and the system comes back to normal when the fault disappears [50]. No prevention mechanism was introduced into our distributed computing model.…”