OSPN: Optimal Service Provisioning with Negotiation for Bag-of-Tasks Applications

Cloud service selection is becoming more complex with the arrival of a large number of cloud providers offering various service packages on the market. These cloud service packages are generally provisioned by Spot, On-demand and Reserved Instances. Typically, a user's service requirements contain many independent sub-tasks (Bag-of-Tasks), and have budget limitations and additional constraints. To select reasonable cloud instances to run the user's sub-tasks, we propose a strategy, OSPN (Optimal Service Provisioning with Negotiation), to support the allocation of tasks to services offered by multi-cloud providers. OSPN consists of two phases: in the first phase, a one-to-many parallel Spot Instance pricing negotiation is applied; in the second phase, service provisioning strategy profiles on the three types of cloud instances are calculated. Specifically, the first phase employs an improved double auction in which the price and availability of providers' instances are taken into account; then the second phase gives the utility Nash equilibrium model and derives the optimal provisioning strategy profiles. The experimental results show that our service provisioning strategy is more cost-effective, namely, the most gains of both the user and providers in the changing scenes, and the least payments of the user than the existing relevant strategies.