In order to save energy with preventing the lack of the resources on servers in data centers, we address the dynamic optimization of virtual machine placement. A decision problem of the virtual machine placement has been formulated as Bin Packing problem. Conventional methods repeat to solve the problem at regular intervals. Live migration is used for changing the virtual machine placement, but some of live migrations are unnecessary; the virtual machine is migrated repeatedly between the physical servers. For the purpose of reducing the unnecessary live migrations, we propose a dynamic optimization of virtual machine placement by resource usage prediction. The proposed method predicts the future resource usage by Auto Regressive Model. The proposed method decides the virtual machine placement by solving the Bin Packing problem with the predicted resource usage.
In this paper we apply the established 'neo-contingency approach' from organizational theory into the field of community-led social ventures which, by necessity, have to be embedded within their local community context in order to achieve their social mission.Through our analysis of three heterogeneous case studies from around rural Japan, we show how the external environment and contingencies affect leadership style and the pattern of social capital, influencing the type of community development apparent in each setting. We propose that local contingencies, such as external environment, leadership and social capital, play a role in influencing organizational culture in community-led social ventures and, indeed, the form that the social venture takes. We conclude by arguing that if the neo-contingency approach is to fulfil its potential then further theoretical and conceptual development is required.
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