Prognostic and Health Management with Autonomic Computing for Cloud Systems
Dongfeng Hu, Xiwei Qiu, Xin Jin · 2022
Cloud computing is one of the most popular technology in recent years. The cloud system, different from some traditional systems, provides Virtual Machines (VM) to users, and the users can run any application or program in the provided VM. However, this service manner brings a critical risk to the health of the cloud system. That is, the program or application from the user may be infected with viruses or malware. Therefore, the VM even and the host server may suffer from virus infection or malicious attacks. It is important to implement a Prognostic and Health Management (PHM) system for the cloud system. This paper presents a novel PHM system with an autonomic computing technique, which is an ongoing challenge. The proposed PHM system is capable of self-diagnosis, self-healing, and self-learning, which is very suitable for the cloud system with the representative and distinctive VM technique. Illustrative examples demonstrate that the proposed PHM system can automatically deal with index anomaly, which can effectively keep the cloud system remain health.