Workload-Adaptive Management of Energy-Smart Disk Storage Systems

Recent studies have identified disk storage systems as one of the major consumers of power in data centers. Many disk power management (DPM) schemes were suggested where the power consumed by disks is reduced by spinning them down during long idle periods. Spinning the disks down and up results in additional energy and response time costs. For that reason, DPM schemes are effective only if the disks experience relatively long idle periods and the scheme does not introduce a severe response time penalty. In this paper we introduce a dynamic block exchange algorithm which switches data between disks based on the observed workload such that frequently accessed blocks end up residing on a few"hot" disks thus allowing the majority of disks to experience longer idle periods. We validate the effectiveness of the algorithm with trace-driven simulations showing power savings of up to 60percent with very small response time penalties

Analysis of Trade-Off Between Power Saving and Response Time in Disk Storage Systems

It is anticipated that in the near future disk storage systems will surpass application servers and will become the primary consumer of power in the data centers. Shutting down of inactive disks is one of the more widespread solutions to save power consumption of disk systems. This solution involves spinning down or completely shutting off disks that exhibit long periods of inactivity and placing them in standby mode. A file request from a disk in standby mode will incur an I/O cost penalty as it takes time to spin up the disk before it can serve the file. In this paper, we address the problem of designing and implementing file allocation strategies on disk storage that save energy while meeting performance requirements of file retrievals. We present an algorithm for solving this problem with guaranteed bounds from the optimal solution. Our algorithm runs in O(nlogn) time where n is the number of files allocated. Detailed simulation results and experiments with real life workloads are also presented

Molecular signature of clinical severity in recovering patients with severe acute respiratory syndrome coronavirus (SARS-CoV)

BACKGROUND: Severe acute respiratory syndrome (SARS), a recent epidemic human disease, is caused by a novel coronavirus (SARS-CoV). First reported in Asia, SARS quickly spread worldwide through international travelling. As of July 2003, the World Health Organization reported a total of 8,437 people afflicted with SARS with a 9.6% mortality rate. Although immunopathological damages may account for the severity of respiratory distress, little is known about how the genome-wide gene expression of the host changes under the attack of SARS-CoV. RESULTS: Based on changes in gene expression of peripheral blood, we identified 52 signature genes that accurately discriminated acute SARS patients from non-SARS controls. While a general suppression of gene expression predominated in SARS-infected blood, several genes including those involved in innate immunity, such as defensins and eosinophil-derived neurotoxin, were upregulated. Instead of employing clustering methods, we ranked the severity of recovering SARS patients by generalized associate plots (GAP) according to the expression profiles of 52 signature genes. Through this method, we discovered a smooth transition pattern of severity from normal controls to acute SARS patients. The rank of SARS severity was significantly correlated with the recovery period (in days) and with the clinical pulmonary infection score. CONCLUSION: The use of the GAP approach has proved useful in analyzing the complexity and continuity of biological systems. The severity rank derived from the global expression profile of significantly regulated genes in patients may be useful for further elucidating the pathophysiology of their disease

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Taxonomy and Evaluation of TCP-Friendly Congestion-Control Schemes on Fairness, Aggressiveness, and Responsiveness

Many TCP-friendly congestion control schemes have been proposed to pursue the TCP-equivalence criterion, which states that a TCP-equivalent flow should have the same throughput with TCP if it experiences identical network conditions as TCP. Additionally, the throughput should converge as fast as TCP when the packet-loss conditions change. This study classifies eight typical TCP-friendly schemes according to their underlying policies on fairness, aggressiveness, and responsiveness. The schemes are evaluated to verify whether they meet TCP-equivalence and TCPequal share. TCP-equal share is a more realistic but more challenging criterion than TCP-equivalence and states that a flow should have the same throughput with TCP if competing with TCP for the same bottleneck. Simulation results indicate that one of the selected schemes, TCP-friendly rate control (TFRC), meets both criteria under more testing scenarios than the others. Additionally, the results under nonperiodic losses, low-multiplexing, two-state losses, and bursty losses reveal the causes that bring fault cases to the schemes. Finally, appropriate policies ar

Pre-order De®cit Round Robin: a new scheduling algorithm for packet-switched networks q

Responsible Editor: E. Knightly In recent years, many packet fair queueing algorithms have been proposed to approximate generalized processor sharing (GPS). Most of them provide a low end-to-end delay bound and ensure that all connections share the link in a fair manner. However, scalability and simplicity are two signi®cant issues in practice. De®cit Round Robin (DRR) requires only O(1) work to process a packet and is simple enough to be implemented in hardware. However, its large latency and unfair behavior are not tolerated. In this work, a new scheme, Pre-order De®cit Round Robin, is described, which overcomes the problems of DRR. A limited number, Z,ofpriority queues are placed behind the DRR structure to reorder the transmission sequence to approximate packet by packet generalized processor sharing (PGPS). We provide an analysis on latency and fairness, which shows our scheme as a better alternative to DRR. In most cases PDRR has a per-packet time complexity of O(1), and O…log Z † in other speci®c cases. Simulation results are also provided to furthe

On-the-fly TCP

path selection algorithm in access link load balancin