Adaptive Dispatching of Tasks in the Cloud

The increasingly wide application of Cloud Computing enables the consolidation of tens of thousands of applications in shared infrastructures. Thus, meeting the quality of service requirements of so many diverse applications in such shared resource environments has become a real challenge, especially since the characteristics and workload of applications differ widely and may change over time. This paper presents an experimental system that can exploit a variety of online quality of service aware adaptive task allocation schemes, and three such schemes are designed and compared. These are a measurement driven algorithm that uses reinforcement learning, secondly a "sensible" allocation algorithm that assigns jobs to sub-systems that are observed to provide a lower response time, and then an algorithm that splits the job arrival stream into sub-streams at rates computed from the hosts' processing capabilities. All of these schemes are compared via measurements among themselves and with a simple round-robin scheduler, on two experimental test-beds with homogeneous and heterogeneous hosts having different processing capacities.Comment: 10 pages, 9 figure

Toward sustainable data centers: a comprehensive energy management strategy

Data centers are major contributors to the emission of carbon dioxide to the atmosphere, and this contribution is expected to increase in the following years. This has encouraged the development of techniques to reduce the energy consumption and the environmental footprint of data centers. Whereas some of these techniques have succeeded to reduce the energy consumption of the hardware equipment of data centers (including IT, cooling, and power supply systems), we claim that sustainable data centers will be only possible if the problem is faced by means of a holistic approach that includes not only the aforementioned techniques but also intelligent and unifying solutions that enable a synergistic and energy-aware management of data centers. In this paper, we propose a comprehensive strategy to reduce the carbon footprint of data centers that uses the energy as a driver of their management procedures. In addition, we present a holistic management architecture for sustainable data centers that implements the aforementioned strategy, and we propose design guidelines to accomplish each step of the proposed strategy, referring to related achievements and enumerating the main challenges that must be still solved.Peer ReviewedPostprint (author's final draft