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- W2019469969 abstract "The most serious drawback nowadays is the power management because the web applications are becoming more sophisticated and their processing power is gradually increasing. Current cluster are designed to handle peak loads, where all servers are equally utilized. In practice, peak load conditions barely happen and clusters are most of the time underutilized. This paper aims to optimize the performance (in terms of execution time) of a multi-tier system and decrease the power consumption of the servers. To achieve these objectives, an Energy Optimizing Genetic Algorithm (EOGA) technique is applied on a three-tier web cluster system. This technique has proved to be successful in decreasing the power consumption and increasing the performance of the system." @default.
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- W2019469969 date "2015-04-22" @default.
- W2019469969 modified "2023-09-25" @default.
- W2019469969 title "An Optimizing Technique based on Genetic Algorithm for Power Management in Heterogeneous Multi-Tier Web Clusters" @default.
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- W2019469969 doi "https://doi.org/10.5120/20243-2598" @default.
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