Energy-aware memory management through database buffer management

Energy consumption in modern data center trends to be in-creasing, which gives pressure to limit power consumption in servers. There is an opposite side trend that needs more memory resources to load increasing application data. Once a system is designed with capacity for peak time usage, it inefficiently consumes more energy in an idle state. So in this paper we propose a dynamically adaptie application-driven memory management scheme. Our example is on a database application with an online transactional work-load. We design and implement a simple heuristic scheme, which determines the state of either expanding or shrinking the size of memory. Our experimental results show that sig-nificant amount of energy saving (4–8%) is achieved with-out any visible performance penalty. Although we acknowl-edge that the overall amount of energy reduction varies to the amount of memory in a system, we believe that this is equally achievable over high-end server machines that are similar to our test machine. 1