Taming tail latency for erasure-coded, distributed storage systems

Nowadays, in distributed storage systems, long tails of responsible time are of particular concern. Modern large companies like Bing, Facebook and Amazon Web Service show that 99.9th percentile response times being orders of magnitude worse than the mean. With the advantages of maintaining high data reliability and ensur- ing enough space eciency, erasure code has become a popular storage method in distributed storage systems. However, due to the lack of mathematical models for analyzing erasure-coded based distributed storage systems, taming tail latency is still an open problem. In this research, we quantify tail latency in such systems by deriving a closed upper bounds on tail latency for general service time distribution and heterogeneous files. Later we specified service time to shifted exponentially distributed. Based on this model, we developed an optimization problem to minimize weighted tail latency probability of deriving all files. We propose an alternating minimization algorithm for this problem. Our simulation results have shown significant reduction on tail latency of erasure-coded distributed storage systems with realistic environment workload

Determinants of Developing Stroke Among Low-Income, Rural Residents: A 27-Year Population-Based, Prospective Cohort Study in Northern China

Although strokes are the leading cause of death and disability in many countries, China still lacks long-term monitoring data on stroke incidence and risk factors. This study explored stroke risk factors in a low-income, rural population in China. The study population was derived from the Tianjin Brain Study, a population-based stroke monitoring study that began in 1985. This study documented the demographic characteristics, past medical histories, and personal lifestyles of the study participants. In addition, physical examinations, including measurements of blood pressure (BP), height, and weight, were performed. Hazard ratios (HRs) were estimated for the risk factors for all subtypes of stroke using multivariate Cox regression analyses. During the study with mean following-up time of 23.16 years, 3906 individuals were recruited at baseline, and during 27 years of follow-up, 638 strokes were documented. The multivariate Cox regression analyses revealed a positive correlation between age and stroke incidence. Limited education was associated with a 1.9-fold increase in stroke risk (lowest vs. highest education level). Stroke risk was higher among former smokers than among current smokers (HR, 1.8 vs. 1.6; both, P < 0.05). Moreover, stroke risk was significantly associated with sex (HR, 1.8), former alcohol drinking (HR, 2.7), baseline hypertension (HR, 3.1), and overweight (HR, 1.3). In conclusion, this study identified uncontrollable (sex and age) and controllable (education, smoking, alcohol drinking, hypertension, and overweight) risk factors for stroke in a low-income, rural population in China. Therefore, it is critical to control BP and weight effectively, advocate cessation of smoking/alcohol drinking, and enhance the education level in this population to prevent increase in the burden of stroke in China

Taming tail latency for erasure-coded, distributed storage systems

Nowadays, in distributed storage systems, long tails of responsible time are of particular concern. Modern large companies like Bing, Facebook and Amazon Web Service show that 99.9th percentile response times being orders of magnitude worse than the mean. With the advantages of maintaining high data reliability and ensur- ing enough space eciency, erasure code has become a popular storage method in distributed storage systems. However, due to the lack of mathematical models for analyzing erasure-coded based distributed storage systems, taming tail latency is still an open problem. In this research, we quantify tail latency in such systems by deriving a closed upper bounds on tail latency for general service time distribution and heterogeneous files. Later we specified service time to shifted exponentially distributed. Based on this model, we developed an optimization problem to minimize weighted tail latency probability of deriving all files. We propose an alternating minimization algorithm for this problem. Our simulation results have shown significant reduction on tail latency of erasure-coded distributed storage systems with realistic environment workload

Performance analysis for high-speed railway distributed antenna systems with imperfect channel state information

Abstract This paper studies the performance of antenna selection for high-speed railway (HSR) distributed antenna systems with imperfect channel state information (CSI). In HSR systems, distributed antennas mounted on top of the train carriage are connected to a mobile relay, which serves as an intermediate node between the base station (BS) and the users inside the train. An important feature of high mobility networks is the fast time-variation of the fading channel caused by the large Doppler spread. It is difficult to accurately estimate, track, and predict the fast time-varying fading coefficients; thus, channel estimation error is usually inevitable and it may seriously degrade system performance. In order to offer a good tradeoff between system performance, cost, and overhead, antenna selection is performed by considering the impacts of both channel estimation errors and noise, such that the antenna with the best link to the BS will be selected to serve users inside the train. The channel estimation error is quantified through the estimation mean squared error (MSE), which is expressed as a closed-form function of the maximum Doppler spread and signal-to-noise ratio (SNR). Several performance metrics, such as outage probability, symbol error rate, spectral efficiency lower bound, and switching rate, are developed as a function of the channel estimation MSE and the geometric layout of the antennas. The analytical and simulation results quantify the significant impacts of imperfect CSI on antenna selection for HSR systems in practical applications

How Does Licensing Remanufacturing Affect the Supply Chain Considering Customer Environmental Awareness?

As sustainability issues are receiving increasing attention in society, in recent years many manufacturers have been adopting remanufacturing via technology licensing. This paper uses a game theory approach to investigate this strategy of a manufacturer under a closed-loop supply chain consisting of one supplier, one manufacturer, and one third-party remanufacturer (TPR), with the consideration of customer environmental awareness. In particular, the supplier supplies the components to the manufacturer and the manufacturer adopts technology licensing remanufacturing via the TPR. We explicitly characterize the reactions between the supplier and the manufacturer as being in equilibrium after adopting the technology licensing. We find that only when remanufacturing is a potential threat to the supplier is the performance of the supply chain improved and the double marginalization effect effectively eliminated. Moreover, remanufacturing by technology licensing only increases the profit of the manufacturer, but decreases the profit of the supplier. Interestingly, contrary to traditional wisdom, the existence of remanufactured products does not reduce the quantity of new products. Furthermore, remanufacturing by technology licensing may not always improve the environment, but customers in the market have environmental awareness that facilitates remanufacturing