Acceptance Test for Fault Detection in Component-based Cloud Computing and Systems

Abstract

Fault Detection is considered as one of the main challenges in large-scale dynamic environments and thus, for maintaining the reliability requirements of Cloud and Mobile Cloud systems. Most of the popular existing techniques for fault detection applied on the Cloud Computing environment in general, are based on system-monitoring despite the extreme difficulty of keeping track of all machines with their huge number in Cloud systems. In this paper, we propose a Fault Detection framework for the Component-based Cloud Computing by using Recovery Blocks’ Acceptance Test. This framework aims to construct Fail-Silent Cloud modules which have the ability of Self-Fault detection. In this, the detection process of transient hardware faults, software faults, and response-time failures is performed locally on each computing machine in the Cloud system. Background of the research issue, our mechanism, thorough analysis, and appropriate case study are presented. The efficiency and practicality of the proposed framework are proved by Safety verification using the model-checker.