適用於行動裝置之高效率節能機制

我們提出一個高能源效率，具有適應性之動態能源管理演算法。為了能夠適應具爆發性與自我相似之需求到達模式及具多重閒置狀態之裝置，我們先分別求得需求爆發(ON)時期和無需求(OFF)時期的平均裝置閒置時間。接著，為了達到更好的節能效率，我們利用需求爆發時期的平均裝置閒置時間來調整將裝置切入低耗能狀態前的等待時間。實驗結果顯示，針對行動式硬碟，我們所提出的演算法之平均能源消耗量低於動態等待時間調整(Adaptive Timeout)，機器學習(Machine Learning)，預測閒置時間(Predictive)，固定等待時間調整(Static Timeout)，及隨機狀態切換(Stochastic)等演算法。另外，本演算法之平均裝置回應時間也低於標準行動式硬碟的規範。至於無線網路裝置，其平均能源消耗量也接近先知型(Oracle，理論上最精確)，動態等待時間調整，及預測閒置時間等演算法，並且優於機器學習，固定等待時間，及隨機狀態切換等演算法。但是，本演算法之平均封包傳輸延遲優於動態等待時間調整及預測閒置時間等演算法。所以，本演算法提供了較佳的平均能源消耗量與平均裝置回應時間(或平均封包傳輸延遲)，而使得本演算法非常適合用於延長具有行動式硬碟與無線網路裝置之行動裝置的電池使用時間。

關鍵字

硬碟；行動裝置；能源管理；自我相似；無線網路介面卡

並列摘要

We propose a power efficient adaptive hybrid dynamic power management (AH-DPM) algorithm. To adapt to bursty request arrival patterns with self-similarity and a service provider (SP, i.e., hard disk or WLAN NIC, in this paper) with multiple inactive states, the proposed AH-DPM first derives the average idle time of the SP in the bursty (ON) period and non-bursty (OFF) period separately. Then, to achieve better power saving, we use the average idle time in the ON period to adjust the timeout value more precisely and use the average idle time in the OFF period to decide which inactive state the SP should be switched to. Experimental results based on real traces show that, for the hard disk, the average power consumption of the proposed AH-DPM is better than that of the Adaptive Timeout (ATO), Machine Learning (ML), Predictive, Static Timeout (STO), and Stochastic algorithms. In addition, the average response time of the proposed AH-DPM algorithm is still lower than that specified in a typical hard disk specification. As to the WLAN NIC, experimental results show that the average power consumption of the proposed AH-DPM is comparable to that of the Oracle (theoretically optimal), ATO, and Predictive algorithms, and is better than that of the ML, STO, and Stochastic algorithms. However, the average packet transmission delay of the proposed AH-DPM is better than that of ATO and Predictive algorithms. Therefore, by providing a better tradeoff between average power consumption and average response time (or average packet transmission delay), the proposed AH-DPM algorithm is very feasible for extending the battery lifetime of mobile devices that are equipped with hard disks and WLAN NICs.

並列關鍵字

Hard disk ； mobile device ； power management ； self-similarity ； WLAN NIC

參考文獻

[1] Y. H. Lu and G. De Micheli, “Comparing system level power management policies,” IEEE Des. Test. Comput., vol. 18, pp. 10-19, March-April 2001.

[3] K. Zhang, X. Ge, C. Liu, and L. Xiang, “Analysis of frame traffic characteristics in IEEE 802.11 networks,” in Proc. IEEE ChinaCOM, Aug. 2009, pp. 1-5.

[4] L. Xiang, X. Ge, K. Zhang, and C. Liu, "A self-similarity frame traffic model based on the frame components in 802.11 networks," in Proc. IEEE CSE, 2009, vol. 2, pp. 955-960.

[5] M. E. Gomez and V. Santonja, "Self-similarity in I/O workload: analysis and modeling," in Proc. IEEE WWC, 1998, pp. 97-104.

[6] M. E. Gomez and V. Santonja, "Analysis of self-similarity in I/O workload using structural modeling," in Proc. IEEE MASCOT, 1999, pp. 234-242.

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適用於行動裝置之高效率節能機制

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