19,546 research outputs found

    Multi-capacity bin packing with dependent items and its application to the packing of brokered workloads in virtualized environments

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    Providing resource allocation with performance predictability guarantees is increasingly important in cloud platforms, especially for data-intensive applications, in which performance depends greatly on the available rates of data transfer between the various computing/storage hosts underlying the virtualized resources assigned to the application. Existing resource allocation solutions either assume that applications manage their data transfer between their virtualized resources, or that cloud providers manage their internal networking resources. With the increased prevalence of brokerage services in cloud platforms, there is a need for resource allocation solutions that provides predictability guarantees in settings, in which neither application scheduling nor cloud provider resources can be managed/controlled by the broker. This paper addresses this problem, as we define the Network-Constrained Packing (NCP) problem of finding the optimal mapping of brokered resources to applications with guaranteed performance predictability. We prove that NCP is NP-hard, and we define two special instances of the problem, for which exact solutions can be found efficiently. We develop a greedy heuristic to solve the general instance of the NCP problem , and we evaluate its efficiency using simulations on various application workloads, and network models.This work was done while author was at Boston University. It was partially supported by NSF CISE awards #1430145, #1414119, #1239021 and #1012798. (1430145 - NSF CISE; 1414119 - NSF CISE; 1239021 - NSF CISE; 1012798 - NSF CISE

    SLO-aware Colocation of Data Center Tasks Based on Instantaneous Processor Requirements

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    In a cloud data center, a single physical machine simultaneously executes dozens of highly heterogeneous tasks. Such colocation results in more efficient utilization of machines, but, when tasks' requirements exceed available resources, some of the tasks might be throttled down or preempted. We analyze version 2.1 of the Google cluster trace that shows short-term (1 second) task CPU usage. Contrary to the assumptions taken by many theoretical studies, we demonstrate that the empirical distributions do not follow any single distribution. However, high percentiles of the total processor usage (summed over at least 10 tasks) can be reasonably estimated by the Gaussian distribution. We use this result for a probabilistic fit test, called the Gaussian Percentile Approximation (GPA), for standard bin-packing algorithms. To check whether a new task will fit into a machine, GPA checks whether the resulting distribution's percentile corresponding to the requested service level objective, SLO is still below the machine's capacity. In our simulation experiments, GPA resulted in colocations exceeding the machines' capacity with a frequency similar to the requested SLO.Comment: Author's version of a paper published in ACM SoCC'1

    Influence of organic films on the evaporation and condensation of water in aerosol

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    Uncertainties in quantifying the kinetics of evaporation and condensation of water from atmospheric aerosol are a significant contributor to the uncertainty in predicting cloud droplet number and the indirect effect of aerosols on climate. The influence of aerosol particle surface composition, particularly the impact of surface active organic films, on the condensation and evaporation coefficients remains ambiguous. Here, we report measurements of the influence of organic films on the evaporation and condensation of water from aerosol particles. Significant reductions in the evaporation coefficient are shown to result when condensed films are formed by monolayers of long-chain alcohols [C(n)H((2n+1))OH], with the value decreasing from 2.4 × 10(−3) to 1.7 × 10(−5) as n increases from 12 to 17. Temperature-dependent measurements confirm that a condensed film of long-range order must be formed to suppress the evaporation coefficient below 0.05. The condensation of water on a droplet coated in a condensed film is shown to be fast, with strong coherence of the long-chain alcohol molecules leading to islanding as the water droplet grows, opening up broad areas of uncoated surface on which water can condense rapidly. We conclude that multicomponent composition of organic films on the surface of atmospheric aerosol particles is likely to preclude the formation of condensed films and that the kinetics of water condensation during the activation of aerosol to form cloud droplets is likely to remain rapid

    Outsourcing labour to the cloud

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    Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area

    We Mean Green Environmental Science Club

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    Lesson Plans for an Environmental Science Club. This club seeks to promote environmental awareness to elementary students through hands-on activities, videos, and discussion

    Constraint-based Autonomic Reconfiguration

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    Skin Deep

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    Analysis and Observations from the First Amazon Picking Challenge

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    This paper presents a overview of the inaugural Amazon Picking Challenge along with a summary of a survey conducted among the 26 participating teams. The challenge goal was to design an autonomous robot to pick items from a warehouse shelf. This task is currently performed by human workers, and there is hope that robots can someday help increase efficiency and throughput while lowering cost. We report on a 28-question survey posed to the teams to learn about each team's background, mechanism design, perception apparatus, planning and control approach. We identify trends in this data, correlate it with each team's success in the competition, and discuss observations and lessons learned based on survey results and the authors' personal experiences during the challenge
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