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We present what we believe to be the first thorough characterization of <i>live</i> streaming media content delivered over the Internet. Our characterization of over 3.5 million requests spanning a 28-day period is done at three increasingly granular levels, corresponding to clients, sessions, and transfers. Our findings support two important conclusions.(More)
The previous research on cluster-based servers has focused on homogeneous systems. However, real-life clusters are almost invariably heterogeneous in terms of the performance, capacity, and power consumption of their hardware components. In this paper, we argue that designing efficient servers for heterogeneous clusters requires defining an efficiency(More)
Recent technological advances have produced network interfaces that provide users with very low-latency access to the memory of remote machines. We examine the impact of such networks on the implementation and performance of software DSM. Specifically, we compare two DSM systems---Cashmere and TreadMarks---on a 32-processor DEC Alpha cluster connected by a(More)
The peak power consumption of hardware components affects their powersupply, packaging, and cooling requirements. When the peak power consumption is high, the hardware components or the systems that use them can become expensive and bulky. Given that components and systems rarely (if ever) actually require peak power, it is highly desirable to limit power(More)
Online social networks (OSNs) have become popular platforms for people to connect and interact with each other. Among those networks, Pinterest has recently become noteworthy for its growth and promotion of visual over textual content. The purpose of this study is to analyze this imagebased network in a gender-sensitive fashion, in order to understand (i)(More)
Decision tree classifiers perform a greedy search for rules by heuristically selecting the most promising features. Such greedy (local) search may discard important rules. Associative classifiers, on the other hand, perform a global search for rules satisfying some quality constraints (i.e., minimum support). This global search, however, may generate a(More)
Due to the increasing amount of information present on the Web, Automatic Document Classification (ADC) has become an important research topic. ADC usually follows a standard supervised learning strategy, where we first build a model using preclassified documents and then use it to classify new unseen documents. One major challenge for ADC in many scenarios(More)
Understanding the nature and characteristics of e-business workloads is a crucial step to improve the quality of service offered to customers in electronic business environments. However, the variety and complexity of the interactions between customers and sites make the characterization of ebusiness workloads a challenging problem. Using a multilayer(More)