Self-Tuning Wireless Network Power Management

被引:0
|
作者
Manish Anand
Edmund B. Nightingale
Jason Flinn
机构
[1] University of Michigan,Department of Electrical Engineering and Computer Science
来源
Wireless Networks | 2005年 / 11卷
关键词
power management; self-tuning; 802.11;
D O I
暂无
中图分类号
学科分类号
摘要
Current wireless network power management often substantially degrades performance and may even increase overall energy usage when used with latency-sensitive applications. We propose self-tuning power management (STPM) that adapts its behavior to the access patterns and intent of applications, the characteristics of the network interface, and the energy usage of the platform. We have implemented STPM as a Linux kernel module—our results show substantial benefits for distributed file systems, streaming audio, and thin-client applications. Compared to default 802.11b power management, STPM reduces the total energy usage of an iPAQ running the Coda distributed file system by 21% while also reducing interactive file system delay by 80%. Further, STPM adapts to diverse operating conditions: it yields good results on both laptops and handhelds, supports 802.11b network interfaces with substantially different characteristics, and performs well across a range of application network access patterns.
引用
收藏
页码:451 / 469
页数:18
相关论文
共 50 条
  • [41] Principle and simulation of the self-tuning passive filter
    Liu, ZZ
    Yang, ZJ
    Zhang, X
    Conference Record of the 2005 IEEE Industry Applications Conference, Vols 1-4, 2005, : 1884 - 1887
  • [42] Design and Application of Self-tuning PI Controller
    Kong, Xiaohong
    Zhang, Baojian
    Mao, Xinhua
    Chen, Yanfeng
    Song, Changyuan
    ADVANCES IN MECHATRONICS TECHNOLOGY, 2011, 43 : 160 - 164
  • [43] Self-tuning Intel Restricted Transactional Memory
    Diegues, Nuno
    Romano, Paolo
    PARALLEL COMPUTING, 2015, 50 : 25 - 52
  • [44] Self-tuning Multivariate Variational Mode Decomposition
    Lang, Xun
    Wang, Jiayi
    Chen, Qiming
    He, Bingbing
    Mao, Rukai
    Xie, Lei
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2024, 46 (07): : 2994 - 3001
  • [45] Better Power Management of Wireless Sensor Network
    Li, Ke
    Zeng, Chunnian
    Liang, Hong
    2009 INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS, VOL 2, PROCEEDINGS, 2009, : 103 - 106
  • [46] Self-Tuning Control Using an Online-Trained Neural Network to Position a Linear Actuator
    Hernandez-Alvarado, Rodrigo
    Rodriguez-Abreo, Omar
    Manuel Garcia-Guendulain, Juan
    Hernandez-Diaz, Teresa
    MICROMACHINES, 2022, 13 (05)
  • [47] Self-Tuning MPPT Scheme Based on Reinforcement Learning and Beta Parameter in Photovoltaic Power Systems
    Lin, Dingyi
    Li, Xingshuo
    Ding, Shuye
    Wen, Huiqing
    Du, Yang
    Xiao, Weidong
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2021, 36 (12) : 13826 - 13838
  • [48] A Self-Tuning Congestion Tracking Control for TCP/AQM Network for Single and Multiple Bottleneck Topology
    Bisoy, Sukant Kishoro
    Pattnaik, Prasant Kumar
    Sain, Mangal
    Jeong, Do-Un
    IEEE ACCESS, 2021, 9 : 27723 - 27735
  • [49] A Fuzzy Self-Tuning PID Controller with a Derivative Filter for Power Control in Induction Heating Systems
    Chakrabarti, Arijit
    Chakraborty, Avijit
    Sadhu, Pradip Kumar
    JOURNAL OF POWER ELECTRONICS, 2017, 17 (06) : 1577 - 1586
  • [50] Self-Tuning for Short-Term Memory Consumers
    Ludger C. Overbeck
    Karsten Schmidt
    Datenbank-Spektrum, 2011, 11 (1) : 37 - 41