A swarm-inspired data center consolidation methodology
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
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Virtualization and consolidation are two complementary techniques widely adopted in a global strategy to reduce system management complexity. In this paper we show how two simple and well-known techniques can be combined to dramatically increase the energy efficiency of a virtualized and consolidated data center. This result is obtained by introducing a new approach to the consolidation strategy that allows an important reduction in the amount of active nodes required to process a web workload without degrading the offered service level. Furthermore, when the system eventually gets overloaded and no energy can be saved without loosing performance, we show how these techniques can still improve the overall value obtained from the workload. The two techniques are memory compression and request discrimination, and were separately studied and validated in a previous work to be now combined in a joint effort. Our results indicate that an important improvement can be achieved by deciding not only how resources are allocated, but also how they are used. Moreover, we believe that this serves as an illustrative example of a new way of management: tailoring the resources to meet high level energy efficiency goals