基于Bio-PEPA的云计算系统可生存性建模和分析（英文）.docx

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Abstract:
Cloud computing system is a complex and large system, which has various components and interactions between each component. To ensure the survivability of the cloud computing system, it is important to model and analyze its survivability properties. This paper proposes a Bio-PEPA based modeling and analysis method for cloud computing systems survivability. The method can effectively model the cloud computing system and analyze its survivability properties, which can help cloud service providers and system designers to improve the survivability of the cloud computing system.
Introduction:
Cloud computing is a new computing paradigm that enables users to access computing resources on demand over the internet. As the use of cloud computing becomes increasingly widespread, the survivability of cloud computing systems has become a major concern. Cloud computing systems are complex and large systems, with various components and interactions between each component. It is difficult to ensure the survivability of cloud computing systems in such a complex and dynamic environment. Therefore, it is necessary to develop effective modeling and analysis methods to evaluate the survivability of cloud computing systems.
Modeling and Analysis of Cloud Computing Systems Survivability
Bio-PEPA is a modeling language that is used to model the behavior of biological systems. The main advantage of Bio-PEPA is that it allows modeling of system behavior in response to environmental changes. Bio-PEPA is widely used for modeling the behavior of biological systems, but it can also be used to model the behavior of other complex systems.
The Bio-PEPA modeling language allows users to model a system's components, interactions, and the response of the system to varying environmental conditions. It enables users to model the state changes that occur in a system and also represent the interactions among the system's components. Bio-PEPA is particularly useful for modeling cloud computing systems because it can model the dynamic behavior of the system in response to environmental changes.
Bio-PEPA can be used to model the behavior of the cloud computing system under different conditions. For example, it can be used to model the behavior of the cloud computing system under heavy loads, system failures, or attacks. By modeling the behavior of the system under different conditions, it is possible to analyze the system's survivability properties.
The survivability properties of a cloud computing system can be modeled using bio-PEPA. The properties can be classified into different categories, including availability, reliability, fault tolerance, and security. Availability is the ability of the system to be operational and accessible to users. Reliability is the ability of the system to provide services continuously without interruption. Fault tolerance is the system's ability to continue providing services despite component failures. Security is the system's ability to protect against attacks and unauthorized access.
Bio-PEPA modeling language can be used to model the system's state changes and the interactions among different components of the system in response to varying environmental conditions. It can model the behavior of the system when under load, failures, or attacks.
Conclusion:
This paper proposes a Bio-PEPA based modeling and analysis method for the survivability of cloud computing systems. The Bio-PEPA modeling language is effective in modeling the behavior of cloud computing systems in response to changing environmental conditions. It enables users to model the state changes that occur in the system and the interactions among the system's components. The method can also be used to model the survivability properties of cloud computing systems. By using this method, cloud service providers and system designers can improve the survivability of the cloud computing system.