A Dynamic Resource Allocation based on Multi Attributes Scoring in Collaborative Cloud Computing
Collaborative cloud computing involves providing cloud services on globally distributed resources belonging to different organizations in a cooperative manner. Resource management and allocation in Collaborative Cloud is challenging because of the heterogeneity of the resources. The other challenge is guaranteeing the Quality of Service (QOS) and availability of these resources. Users’ resource demands have to be managed properly to ensure acceptable QOS. In this paper, we propose a method for effective management and allocation of resources using machine learning and using multi attribute tuning. The method has been simulated in cloud-sim as well as implemented on Amazon work space and results show that the proposed method performs better than reputation based algorithms.
