Abstract. Cloud computing provides user utility-oriented IT services, yet accompanied with huge energy consuming, which contributes to the high operational cost as well as CO 2 emission. Making Cloud computing energy efficient can lead to a better tradeoff between profit and environmental impact. In this paper, we formulate the energy efficient VM placement problem in Cloud architecture with multidimensional resources and introduce the objective of this problem. Heuristic algorithms including three traditional local search algorithms and generic algorithm (GA) are presented to provide possible optimized solution. We conduct experiments based on Cloudsim. The result shows that GA sometimes provide the best solution, but with poor stabability. Although the BF provide neither the best nor the worst solution most of time, it have the best stabability.Keywords: Cloud computing, energy efficient, VM placement, heuristic algorithm. IntroductionRecent year, the rapid growth in demand for computational power driven by modern service applications led to the proliferation of Cloud computing [1], resulting in the establishment of large-scale data centers consuming enormous energy. High-energy consumption not only translates to high-energy cost reducing the profit of Cloud providers, but also high carbon emissions that are not environmentally sustainable [2]. Power has become one of the major limiting factors for a data center [3]. However, the reason for this extremely high-energy consumption is not just lies in the amount of computing resources used and the power inefficiency of hardware, but rather lies in the inefficient usage of these resources. Many data centers often operate at low utilization. Data collected from more than 5000 production servers over a six-month period showed that servers operate only at 10-50% of their full capacity most of the time [4]. But even at a very low load, such as 10% CPU utilization, the power consumed of a server is over 50% of the peak power, because the power needed to run the OS and to maintain hardware peripherals is not negligible [5]. Similarly, if the disk, network, etc. is the performance bottleneck, the idle power wastage in other * Corresponding author.

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Automatic grafting and cutting machines can be employed to satisfy the increasing demand for seedlings without soil-borne diseases in a short period. The main approach used to feed seedlings for automatic grafting and cutting machines is artificial, which limits the improvement of grafting and cutting machine productivity. The separation system with a subdivision air stream can stably feed seedlings for cutting and grafting machines; however, the separation efficiency is low when a few seedlings are in the separator. To solve this problem, a feedback monitoring device with a photosensitive sensor as the sensing element and feedback functions on the status of seedlings in the separator was developed. Through experiments using a photosensitive sensor to monitor the separation process of tomato seedlings, the results showed that the effect on the effective seedling blowing rate varied from large to small depending on the seedling size, light intensity, and sensor diameter. The results of separation experiment showed that the productivity of the entire system was 8784 plants/h, which satisfies the productivity needs of the grafting and cutting machine. Compared with the separation device without feedback monitoring, the productivity increased by 39%, the damage rate decreased by 4%, and the number of subdivided air stream operations was reduced by 47%.

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