A Workload-Based Approach to Partition the Volunteer Cloud

The growing demand of computational resources has shifted users towards the adoption of cloud computing technologies. Cloud allows users to transparently access to remote computing capabilities as an utility. The volunteer computing paradigm, another ICT trend of the last years, can be considered a companion force to enhance the cloud in fulfilling specific domain requirements, such as computational intensive requests. Combining the spared resources provided by volunteer nodes with few data centers is possible to obtain a robust and scalable cloud platform. The price for such benefits relies in increased challenges to design and manage a dynamic complex system composed by heterogeneous nodes. Task execution requests submitted in the volunteer cloud are usually associated with Quality of Service requirements e.g., Specified through an execution deadline. In this paper, we present a preliminary evaluation of a cloud partitioning approach to distribute task execution requests in volunteer cloud, that has been validated through a simulation-based statistical analysis using the Google workload data trace.