On Optimization of Energy Consumption in a Volunteer Cloud

Abstract

Traditional Cloud computing has emerged as a new paradigm for providing computing resources on demand and outsourcing software and hardware infrastructures. Cloud computing is rapidly changing the way IT services are made available and managed. These services can be requested by several Cloud providers, hence the need for networking between IT service components distributed in geographically diverse locations. Like the traditional Cloud computing, the volunteer computing paradigm has become increasingly important. For this paradigm, the resources on each personal machine are shared, thanks to the will of their owners. Cloud and volunteer paradigms have been recently seen as complementary technologies to better exploit the use of local resources. Besides execution time and cost, energy consumption is also becoming more important in the Cloud computing environments. Thus, it has become a major concern for the widespread deployment of Cloud data centers. Among methods that can overcome this problem, we are interested in planning services that improve the use of data center resources in a dynamic environment. In this context, we propose throughout this paper a heuristic that predicts the allocation of dynamic and independent services to reduce the total energy consumption. Our proposal respects various constraints: availability, capacity of machines and the number of applications duplications. A series of experiments illustrates and validates the potential of our approach.