Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications place very different demands on Bigtable, both in terms of data size (from URLs to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). Despite these varied demands, Bigtable has successfully provided a flexible, high-performance solution for all of these Google products. In this article, we describe the simple data model provided by Bigtable, which gives clients dynamic control over data layout and format, and we describe the design and implementation of Bigtable.

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Predicting the time of full discharge of a finite-capacity energy source, such as a battery, is important for the design of portable electronic systems and applications. In this paper we present a novel analytical model of a battery that not only can be used to predict battery lifetime, but also can serve as a cost function for optimization of the energy usage in battery-powered systems. The model is physically justified, and involves only two parameters, which are easily estimated. The paper includes the results of extensive experimental evaluation of the model with respect to numerical simulations of the electrochemical cell, as well as measurements taken on a real battery. The model was tested using constant, interrupted, periodic and non-periodic discharge profiles, which were derived from standard applications run on a pocket computer.