Energy-Efficient Strategy for Placement of Online Services on Dynamic Availability Resources in Volunteer Cloud

Cloud computing is regarded as the best generation of computation that relies on shared computing resources rather than having local servers or personal devices to handle different applications. Knowing that, from one side, computing resources can be dynamically allocated according to consumer requirements and from the other side, virtual machine deployment preferences has an important role in Cloud computing for improving resource use. In this paper, we propose an online placement strategy of services on dynamic availability resources in order to reduce energy consumption. Dynamic deployment of services is a key issue of Cloud computing; there are still many areas to be studied, especially for dynamic environments. Unlike the infrastructure topology of the traditional Clouds, i.e. the data centers to which users are connected, in the volunteer Cloud, users and data centers can process multiple requests. Indeed, the volunteer nodes are useful for the Cloud elasticity. However, they are not usually available. The dynamic availability is one of the biggest concerns for the consumers. In addition, live migration of services is a widely used technique for dynamically allocating resources in a volunteer Cloud to overcome such issue. In this work, we investigate the problem of energy efficient online task allocation in volunteer Cloud environment, where the dynamic services can be allocated to a set of dynamic availability resources. We propose through this paper an online heuristic called Dynamic Shortest Path Strategy (DSPS) in order to generate a good planning that minimizes the energy consumption of applications. Our contribution respects various constraints such as availability, capacity of machines and duplications factor of applications. A series of experiments are illustrated to validate the potential of our approach.