Storage efficiency

Abstract: Carbon capture and storage (CCS) is vital to reduce CO2 emissions to the atmosphere, potentially providing 20% of the needed reductions in global emissions. Research and demonstration projects are important to increase scientific understanding of CCS, and making processes and results widely available helps to reduce public concerns, which may otherwise block this technology. The Otway Project has provided verification of the underlying science of CO2 storage in a depleted gas field, and shows that the support of all stakeholders can be earned and retained. Quantitative verification of long-term storage has been demonstrated. A direct measurement of storage efficiency has been made, confirming that CO2 storage in depleted gas fields can be safe and effective, and that these structures could store globally significant amounts of CO2.

Abstract: Quantum memory is an important component in the long-distance quantum communication based on the quantum repeater protocol. To outperform the direct transmission of photons with quantum repeaters, it is crucial to develop quantum memories with high fidelity, high efficiency and a long storage time. Here, we achieve a storage efficiency of 92.0 (1.5)% for a coherent optical memory based on the electromagnetically induced transparency scheme in optically dense cold atomic media. We also obtain a useful time-bandwidth product of 1200, considering only storage where the retrieval efficiency remains above 50%. Both are the best record to date in all kinds of schemes for the realization of optical memory. Our work significantly advances the pursuit of a high-performance optical memory and should have important applications in quantum information science.

Abstract: Erasure codes, such as Reed-Solomon (RS) codes, are being increasingly employed in data centers to combat the cost of reliably storing large amounts of data. Although these codes provide optimal storage efficiency, they require significantly high network and disk usage during recovery of missing data. In this paper, we first present a study on the impact of recovery operations of erasure-coded data on the data-center network, based on measurements from Facebook's warehouse cluster in production. To the best of our knowledge, this is the first study of its kind available in the literature. Our study reveals that recovery of RS-coded data results in a significant increase in network traffic, more than a hundred terabytes per day, in a cluster storing multiple petabytes of RS-coded data. To address this issue, we present a new storage code using our recently proposed "Piggybacking" framework, that reduces the network and disk usage during recovery by 30% in theory, while also being storage optimal and supporting arbitrary design parameters. The implementation of the proposed code in the Hadoop Distributed File System (HDFS) is underway. We use the measurements from the warehouse cluster to show that the proposed code would lead to a reduction of close to fifty terabytes of cross-rack traffic per day.