Search

The problem of resources management in the cloud environment, focusing on the platform as a service (PaaS), satisfying the demands of users, and relieving the load on the server in high concurrency, requires attention. After analysing the resource orchestration technology on PaaS, this paper presents a dynamic orchestration optimisation framework based on autoregressive integrated moving average model (ARIMA) model. The architecture is based on an OpenStack infrastructure as a service (IaaS), and combines with Cloudify, a resource orchestration software on the PaaS. Adjustments may be made in advance by predicting the resource consumption in the next time period. Experiments showed that this architecture can effectively shorten the concurrent response time and improve the utilisation of memory.

This paper proposes a software behaviours analysis method based on behaviour template (SABT), which according to the context of source code, builds a behaviour template to detect software malicious behaviour based on function transfer map and minimum function blocks. In the present research, many methods used state transfer diagram to build software behaviour model. Our method is based on the corresponding relationship between the functions and system call sequence, which ensures the accuracy of the malicious behaviour detection. Compared with traditional methods, such as N-gram, FSA, and Var-gram, SABT can get higher cover rate of code and detect abnormal behaviour more effectively and efficiently.