76 research outputs found

    Proactive and politically skilled professionals: What is the relationship with affective occupational commitment?

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    The aim of this study is to extend research on employee affective commitment in three ways: (1) instead of organizational commitment the focus is on occupational commitment; (2) the role of proactive personality on affective occupational commitment is examined; and (3) occupational satisfaction is examined as a mediator and political skills as moderator in the relationship between proactive personality and affective occupational commitment. Two connected studies, one in a hospital located in the private sector and one in a university located in the public sector, are carried out in Pakistan, drawing on a total sample of over 400 employees. The results show that proactive personality is positively related to affective occupational commitment, and that occupational satisfaction partly mediates the relationship between proactive personality and affective occupational commitment. No effect is found for a moderator effect of political skills in the relationship between proactive personality and affective occupational commitment. Political skills however moderate the relationship between proactive personality and affective organizational commitment

    Cheap data analytics on cold storage

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    Energy smart management of scientific data

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    Abstract. Scientific data centers comprised of high-powered computing equipment and large capacity disk storage systems consume considerable amount of energy. Dynamic power management techniques (DPM) are commonly used for saving energy in disk systems. These involve powering down disks that exhibit long idle periods and placing them in standby mode. A file request from a disk in standby mode will incur both energy and performance penalties as it takes energy (and time) to spin up the disk before it can serve a file. For this reason, DPM has to make decisions as to when to transition the disk into standby mode such that the energy saved is greater than the energy needed to spin it up again and the performance penalty is tolerable. The length of the idle period until the DPM decides to power down a disk is called idleness threshold. In this paper, we study both analytically and experimentally dynamic power management techniques that save energy subject to performance constraints on file access costs. Based on observed workloads of scientific applications and disk characteristics, we provide a methodology for determining file assignment to disks and computing idleness thresholds that result in significant improvements to the energy saved by existing DPM solutions while meeting response time constraints. We validate our methods with simulations that use traces taken from scientific applications

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    A reliable power management scheme for consistent hashing based distributed key value storage systems

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    Distributed key value storage systems are among the most important types of distributed storage systems currently deployed in data centers. Nowadays, enterprise data centers are facing growing pressure in reducing their power consumption. In this paper, we propose GreenCHT, a reliable power management scheme for consistent hashing based distributed key value storage systems. It consists of a multi-tier replication scheme, a reliable distributed log store, and a predictive power mode scheduler (PMS). Instead of randomly placing replicas of each object on a number of nodes in the consistent hash ring, we arrange the replicas of objects on nonoverlapping tiers of nodes in the ring. This allows the system to fall in various power modes by powering down subsets of servers while not violating data availability. The predictive PMS predicts workloads and adapts to load fluctuation. It cooperates with the multi-tier replication strategy to provide power proportionality for the system. To ensure that the reliability of the system is maintained when replicas are powered down, we distribute the writes to standby replicas to active servers, which ensures failure tolerance of the system. GreenCHT is implemented based on Sheepdog, a distributed key value storage system that uses consistent hashing as an underlying distributed hash table. By replaying 12 typical real workload traces collected from Microsoft, the evaluation results show that GreenCHT can provide significant power savings while maintaining a desired performance. We observe that GreenCHT can reduce power consumption by up to 35%–61%
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