Research On Cloud Workflow Scheduling Method With Privacy Protection

Nowadays, business or scientific processes with a massive of data are springing up in the cloud over Internet. Cloud service providers(CSPs) can easily obtain and access customers data in the cloud since they have the right to manage the data. Thus, customer private information stored in the cloud may be easily exposed and lead to serious privacy leak issues. Customers need to consider the balance between highly utilizing the cloud resources and protection of their data privacy and security.Cloud workflow systems as an automated tool to support business process management and scientific processes, whose optimization scheduling has become the industrial and academic research focus, and domestic and foreign counterparts also has carried out numerous research. However, in terms of privacy protection in conjunction with the cloud workflow scheduling optimization is still a blind spot, In this paper, we research on the problem of cloud workflow scheduling with privacy protection, makes the following contributions:(1) A scheduling model that considers users' privacy is constructed, which can meet the needs of protecting users' privacy in practical cloud workflow applications. We model the cloud and virtual resources, and define the workflow description language P-WSL which considers the needs of privacy protection, and present a constraint conflilct detection method with the needs of privacy protection based on P-WSL.(2) A privacy-aware and cost-aware cloud workflow scheduling algorithm named CP-PSO is designed, Based on the intelligent optimization algorithms of PSO and SA,. It firstly uses the summation of upward and downward rank values that considers execution cost in clouds for prioritizing tasks, which is inspired by the classical list-based CPOP scheduling algorithm. Then, searching the optimization scheduling scheme with combining the user's privacy protection needs. Finally, the result of simulation experiments shows its effectiveness.(3) A privacy and cost aware method based on genetic algorithm for data intensive workflow applications has been studied, in which takes into account computation cost, data transmission cost and data storage cost in cloud to solve this problem on finding the best scheduling solution. The proposed algorithm uses the summation of upward and downward rank values for prioritizing workflow tasks, then merges it to make an optimal initial population to obtain a good solution quickly. Besides, a series of operations like selection, crossover and mutation have been used to optimize the scheduling. Finally, we demonstrate the potential and the good performance of proposed algorithm for optimizing economic cost with user privacy protection requirement in Cloud Sim.