, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices. Categories and Subject Descriptors: H.2.3 [Database Management

, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices. 1.

. This results in a significant reduction in the number of routing messages. We present two algorithms to determine the request zone, and also suggest potential optimizations to our algorithms.

the increase in the average tree size in AdaBoost trials and its success in reducing the error. We compare the mean-squared error of voting methods to non-voting methods and show that the voting methods lead to large and significant reductions in the mean-squared errors. Practical problems

/packet of routing packets by 5-30% over shortest-hop routing (this cost reduction is on top of a 40-70% reduction in energy consumption obtained by using PAMAS, our MAC layer protocol). Furthermore, using these new metrics ensures that the mean time to node failure is increased significantly. An interesting

Abstract Reduction Systems

-parameterized fashion for high performance. Trace-driven simulations show that with the appropriate cost definition, GreedyDual-Size outperforms existing web cache replacement algorithms in many aspects, including hit ratios, latency reduction and network cost reduction. In addition, GreedyDual-Size can potentially

Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our

hierarchical reduction scheme whereby entire control con-structs are reduced to an object similar to an operation in a basic block. With this scheme, all innermost loops, including those containing conditional statements, can be software pipelined. It also diminishes the start-up cost of loops with small

) effective use of priors in conditional loglinear models, and (iv) fine-grained modeling of unknown word features. Using these ideas together, the resulting tagger gives a 97.24% accuracy on the Penn Treebank WSJ, an error reduction of 4.4% on the best previous single automatically learned tagging