Schall, DanielHärder, Theo2018-01-102018-01-1020142014https://dl.gi.de/handle/20.500.12116/11726Due to their narrow power spectrum between idle and full utilization [2], satisfactory energy efficiency of servers can only be reached in the peak-performance range, whereas energy efficiency obtained for lower activity levels is far from being optimal. Hence, this hardware property obviates a desired energy proportionality or minimal energy use for the entire range of system utilization. To approximate energy proportionality for all activity levels, we developed various versions of WattDB, a distributed DBMS, which runs on a dynamic cluster of wimpy computing nodes. In this survey, we sketch important design decisions and implementation steps towards the final state of WattDB. For these reasons, we discuss our findings on a cluster with dedicated storage nodes and static data allocation, on dynamic data repartitioning and allocation, and on a dynamic cluster where each node can serve as storage and processing node in a symmetric way. Our experiments show that WattDB dynamically adjusts to the workload present and reconfigures itself to satisfy performance demands while keeping its energy consumption at a minimum. Finally, we compare the performance and energy results of the WattDB software running on the cluster of wimpy nodes with that of a brawny server.Cluster of wimpy computing nodesData partitioningDistributed database managementEnergy efficiencyEnergy proportionalityText/Journal Article1610-1995