How to identify an emergent property in a social system is a challenging topic. Social system modeling is an effective way to understand and explain the emergence phenomena. A reversed process of Role-Based Collaboration (RBC) is proposed for emergence studies. The Environments–Classes, Agents, Roles, Groups, and Objects (E-CARGO) model is the fundamental model of RBC. A well extended E-CARGO (EE-CARGO) model is proposed to modeling a social system with emergent properties. The system is abstracted into agent-role level, roles are modeled as a tree structure and role emergence is identified and analyzed at multiple scales. Then we derive that the masses are primary, and the individual agent is secondary to understanding the emergence forming. A case study is accomplished to verify the effectiveness of proposed approach (i.e., the reversed RBC process and EE-CARGO model). The results are revealed that the role emergence fits a cubic curve estimation by time and at a moderate scale, the role emergence happens easily. Role performances at a small scale affect super-role emergence at a large scale statistically, and vice versa. The proposed approach can be applied to investigate emergence in a variety of areas, such as social evolution.

With the widespread adoption of Cloud computing system, more and more application services based on cluster computing adopt this new computing paradigm. Live snapshot technology is usually used to ensure the reliability of data and high availability of the running virtual machines. This technology is essential to bring abilities of fault recovery and rollback to virtual clusters. Existing virtual machine live snapshot technologies are not enough to cope with the following challenges induced by taking live snapshots for a virtual cluster. One is keeping communication status among virtual machines belonging to a virtual cluster, and the other is minimizing the downtime of virtual machines when taking snapshot for a virtual cluster consisting of a large number of virtual machines. To address both challenges, this paper proposes a virtual cluster live snapshot framework which aims to preserve communication status among virtual machines belonging to a virtual cluster and to minimize the virtual machines downtime and performance overhead of live snapshot. Our experiments show that there is no lost package during taking live snapshot or restoring live snapshot, and that the average downtime of eight virtual machines in a virtual cluster is just 3% longer than that of individual virtual machine during taking live snapshot.