Toward an Autonomic and Adaptive Load Management Strategy for Reducing Energy Consumption under Performance Constraints in Data Centers

摘要

The future vision of IT-industry is shifting toward a utility-based offering of computing power using the concepts of pay-per-use. However, the elasticity and scalability characteristics of cloud computing massively increased the complexity of IT-system landscapes, since market leaders extensively expanding their IT-infrastructure. Accordingly, the carbon-footprint of data centers operations is estimated to be the fastest growing footprint among different IT fields. The majority of contribution in the examined literature that address IT resources management in data centers exhibits either a specific or a generic nature. The specific solutions are designed to solve specific problems, but yet neglecting the dynamic nature of IT-systems. The design of generic solutions usually overlooks many details of the investigated problems that have an impact on the possible optimization potential. One can argue that an optimized combination of different algorithms used during a specified time span would outperform a single specific or generic algorithm for the management of IT recourses in data centers. Therefore, a conceptual design for an autonomic and adaptive load management strategy is presented to investigate the aforementioned hypothesis. Our initial experimental results showed considerable improvement when multiple algorithms are used for the allocation of virtual machines.