Improvement and hardware design of sleep mode in IEEE 802.16e

doi:10.3778/j.issn.1002-8331.2010.06.031

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (6): 107-111.DOI: 10.3778/j.issn.1002-8331.2010.06.031

• 网络、通信、安全 • Previous Articles Next Articles

Improvement and hardware design of sleep mode in IEEE 802.16e

ZHANG Yan，ZHANG Chun-ye，ZHAO Li，QU Hong-wei

School of Information Science and Engineering，Shandong University，Jinan 250100，China

Received:2008-09-10 Revised:2008-12-17 Online:2010-02-21 Published:2010-02-21
Contact: ZHANG Yan

IEEE802.16e睡眠模式的改进和硬件设计

张燕，张春业，赵莉，曲宏伟

山东大学信息科学与工程学院，济南 250100

通讯作者: 张燕

Abstract

Abstract: The IEEE 802.16e support mobility.Energy saving becomes important.So，sleep mode mechanism comes up to conserve the power of the Mobile Stations（MS）.The exponential increase algorithm of sleep mode consumes long response time in low traffic scenario.This paper presents exponential weight smooth increase algorithm to solve this problem.Average response time and average energy consumption are two performance measurements.The hardware design of sleep_time_caculator and the whole system’s hardware framework are designed.By simulation，the two algorithms are compared and the conclusion is that the latter one has better performance，and then the above two performance measurements are analyzed over each parameter of sleep mode and experimental results are given.The conclusion will be helpful to select the value of parameters．

Key words: IEEE802.16e, sleep-mode, energy consumption

摘要： IEEE802.16e标准支持终端的移动性，能量消耗成为非常重要的问题，因此，标准提出了节能机制睡眠模式减少移动站点（MS）的功率消耗。草案中提出的睡眠窗口指数增长算法在低业务量情况下，响应时间过长。提出了指数加权滑动增长算法解决这一问题，理论分析了新算法的平均响应时间和平均消耗能量两性能指标，对算法进行了硬件设计和整体系统的硬件结构设计，通过仿真对比了这两种算法的性能，证实后者在现实应用环境下具有较好的性能。进一步分析了睡眠模式各参数对上述性能指标的影响，对参数值的选取有参考价值。

关键词: IEEE802.16e, 睡眠模式, 能量消耗

CLC Number:

TN925

ZHANG Yan，ZHANG Chun-ye，ZHAO Li，QU Hong-wei. Improvement and hardware design of sleep mode in IEEE 802.16e[J]. Computer Engineering and Applications, 2010, 46(6): 107-111.

张燕，张春业，赵莉，曲宏伟. IEEE802.16e睡眠模式的改进和硬件设计[J]. 计算机工程与应用, 2010, 46(6): 107-111.

[1]	ZHANG Chi, WANG Yuxin, FENG Zhen, GUO He. Energy-Efficient Task Scheduling Algorithm in Two-Layer Virtualized Cloud Architecture [J]. Computer Engineering and Applications, 2021, 57(3): 103-111.
[2]	DAI Jiangtao, HAN Xiaolong. Coordinated Scheduling of Equipment in Container Terminals Considering Energy Consumption Under Different Job Status [J]. Computer Engineering and Applications, 2021, 57(19): 290-298.
[3]	CUI Caixia, BI Chaochao, FAN Qinqin. Self-Adaptive MODE Based on Hidden Markov Chain and Application [J]. Computer Engineering and Applications, 2021, 57(14): 83-94.
[4]	AN Likui, HAN Liyan. Instruction Prefetching and Cache Partitioning for Multicore Cache WCEC Optimization [J]. Computer Engineering and Applications, 2020, 56(1): 69-75.
[5]	LIU Liang, ZHANG Lin, YANG Liu, PANG Ruiqin, WANG Tao. Correlation-Aware Traffic Consolidation Algorithm in Data Center Networks [J]. Computer Engineering and Applications, 2019, 55(24): 62-67.
[6]	WANG Yanjiao, TANG Qi. Improved Routing Energy Algorithm for Heterogeneous Wireless Sensor Networks [J]. Computer Engineering and Applications, 2019, 55(22): 80-85.
[7]	ZHANG Yuanyuan, WU Huafeng, XIAN Jiangfeng, MEI Xiaojun. Adaptive Clustering Algorithm in Ocean Wireless Sensor Network Under Double Constraints [J]. Computer Engineering and Applications, 2019, 55(19): 128-133.
[8]	GENG Haijun, ZHANG Shuang. Energy-Efficient Scheme in Green Networks：A Survey [J]. Computer Engineering and Applications, 2019, 55(16): 1-9.
[9]	HOU Qinglong, YANG Dong, GUO Shijie. Review on energy consumption optimization methods of industrial robots [J]. Computer Engineering and Applications, 2018, 54(22): 1-9.
[10]	DING Chengjun1, LIU Qiang1, FENG Yubo1, 2, GAO Xue1. Online monitoring of university computer room based on IoT and edge computing [J]. Computer Engineering and Applications, 2018, 54(21): 257-264.
[11]	PENG Liping, LV Xiaodan, JIANG Chaohui. Study of Ceph cluster based energy consumption management strategy [J]. Computer Engineering and Applications, 2018, 54(10): 66-72.
[12]	HU Yuan1, BAO Yu1，2, WANG Yuanping1. Energy-efficient node deployment strategy for band-type wireless sensor networks [J]. Computer Engineering and Applications, 2017, 53(23): 77-81.
[13]	WANG Renqun, PENG Li. Topology-aware energy consumption optimization in data center networks [J]. Computer Engineering and Applications, 2017, 53(17): 117-122.
[14]	GUO Dong1, XIAO Qingtai1，2, XU Jianxin1，2. Cloud computing energy consumption optimization model research based on Weibull distribution [J]. Computer Engineering and Applications, 2017, 53(15): 77-84.
[15]	ZHAO Liquan, CHEN Nan, WANG Yanjiao. Improved routing algorithm for heterogeneous wireless sensor networks [J]. Computer Engineering and Applications, 2017, 53(14): 99-104.

Improvement and hardware design of sleep mode in IEEE 802.16e

IEEE802.16e睡眠模式的改进和硬件设计

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics