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Regime Change: Sampling Rate vs. Bit-Depth in Compressive Sensing
The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demonstrated that structured signals can be acquired with just a small number of linear measurements, on the order of the signal complexity. In practice, this enables lower ...
Workload shaping for QoS and power efficiency of storage systems
The growing popularity of hosted storage services and shared storage infrastructure in data centers is driving the recent interest in resource management and QoS in storage systems. The bursty nature of storage workloads raises significant performance and provisioning challenges, leading to increased resource requirements, management costs, and energy ...
Nested QoS: Providing flexible SLAs in shared storage systems
The increasing popularity of storage and server consolidation introduces new challenges for resource management, capacity provisioning, and application performance guaranteeing. In addition, the bursty nature of storage workloads results in a large gap between the peak and the average capacity required to meet response time bounds, leading to low ...
A storage architecture for data-intensive computing
The assimilation of computing into our daily lives is enabling the generation of data at unprecedented rates. In 2008, IDC estimated that the "digital universe" contained 486 exabytes of data . The computing industry is being challenged to develop methods for the cost-effective processing of data at these large scales. The MapReduce programming ...