Handling workloads generated by a large number of users, data-stream-processing systems also require large amounts of energy. To reduce their energy footprint, such systems typically rely on the operating systems of their servers to adjust processor speeds depending on the current workload by performing dynamic voltage and frequency scaling (DVFS). In this paper, we show that, although effective, this approach still leaves room for significant energy savings due to DVFS making conservative assumptions regarding its impact on application performance. To leverage the unused potential we present Strome, an energyaware technique to minimize energy demand in data-stream-processing systems by dynamically adapting upper limits for the power demand of hardware components. In contrast to DVFS, Strome exploits information on application performance and is therefore able to achieve energy savings while minimizing its effects on throughput and latency. Our evaluation shows that Strome is particularly effective in the face of varying workloads, reducing power demand by up to 25 % compared with the state-of-the-art data-stream-processing system Heron relying on DVFS.
We explore the advantages of using Erasure Codes (ECs) in a very challenging sensor networking scenario, namely, monitoring and tracking bats in the wild. The mobile bat nodes collect contact information that needs to be transmitted to stationary base stations whenever they are in communication range. We are particularly interested in improving the overall communication reliability of the wireless communication. The mobile nodes are capable of storing a few 100kB of data and to exchange contact information in aggregated form. Due to the continuous flight of the bats and the forest environment, the wireless channel quality varies quickly and, thus, the communication is in general assumed to be highly unreliable. Given the very strict energy constraints of the mobile node and the inherently asymmetric channels, conventional techniques such as full data replication or Automatic Repeat Request to improve the communication reliability are prohibitive. In this work, we investigate the tradeoff between reliability achieved and the cost in form of additional transmissions, that is, the additional energy costs. Our energy measurements on a real platform combined with larger-scale simulation of the wireless communication clearly indicate the advantages of using ECs in our scenario. The results are also applicable in other configurations when unreliable communication channels meet tight energy budgets.
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