异步传感器网络随机事件捕获在线调度方案

doi:10.16180/j.cnki.issn1007-7820.2019.02.015

Abstract

Abstract:

Aiming at off-line problem of sensor node sleeping scheduling based on event random property in existing asynchronous sensor networks, Bayesian estimations were given for the distributed parameters of random variables describing random property of random events. The relationship among the instantaneous capture probability, the energy efficiency of the sensor capture event, and the Bayesian estimates was discussed to obtain the relationship between sensor's sleeping scheduling and Bayesian estimation of distributed parameters. Based on the above analysis, the real time adjustment scheduling schemes were obtained for the sensor node sleep. Finally, the study conducted the online scheduling and offline scheduling simulation experiments. Experimental results showed that compared with the offline scheduling scheme, online scheduling scheme had better adaptability.

Key words: random event, distribution parameters, bayesian estimation, off line periodic scheduling scheme, on line adjustable periodic scheduling schemes

CLC Number:

TP393

YU Zhixiang,CHENG Zongmao,XU Xianghua. An Online Scheduling Scheme for Random Event Capture in Asynchronous Sensor Networks[J].Electronic Science and Technology, 2019, 32(2): 70-74.

Figures/Tables 5

Table 1

Table 2

Figure 1.

Figure 2.

Figure 3.

References 17

[1]	Anisi M H, Abdul-Salaam G, Abdullah A H . A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture[J]. Precision Agriculture, 2015,16(2):216-238. doi: 10.1007/s11119-014-9371-8
[2]	Tokekar P, Hook J V, Mulla D , et al. Sensor planning for a symbiotic UAV and UGV system for precision agriculture[J].IEEE Transactions on Robotics, 2016(99):1-11. doi: 10.1109/TRO.2016.2603528
[3]	Delamo M, Felici-Castell S, Foster A . Designing an open source maintenance-free environmental monitoring application for wireless sensor networks[J]. Journal of Systems & Software, 2015,103(C):238-247. doi: 10.1016/j.jss.2015.02.013
[4]	Mou Wu, Liansheng Tan, Naixue Xiong . Data prediction, compression, and recovery in clustered wireless sensor networks for environmental monitoring applications[J]. Information Sciences, 2016,329(C):800-818. doi: 10.1016/j.ins.2015.10.004
[5]	魏鹏, 路赞赞 . 无线传感器网络分布式多传感器目标检测[J]. 电子科技, 2014,27(3):143-146. doi: 10.3969/j.issn.1007-7820.2014.03.043
	Wei Peng, Lu Zanzan . Wireless sensor networks distributed multi-sensor target detection[J]. Electronic Science and Technology, 2014,27(3):143-146. doi: 10.3969/j.issn.1007-7820.2014.03.043
[6]	Xiao K, Wang R, Fu T , et al. Divide-and-conquer architecture based collaborative sensing for target monitoring in wireless sensor networks[J]. Information Fusion, 2017, ( 36):162-171. doi: 10.1016/j.inffus.2016.11.014
[7]	Ahmadi A, Shojafar M, Hajeforsh S F , et al. An efficient routing algorithm to preserve k-coverage in wireless sensor networks[J]. Journal of Supercomputing, 2014,68(2):599-623. doi: 10.1007/s11227-013-1054-0
[8]	Islam M M, Ahasanuzzaman M, Razzaque M A , et al. Target coverage through distributed clustering in directional sensor networks[J]. Eurasip Journal on Wireless Communications & Networking, 2015,2015(1):167-175. doi: 10.1186/s13638-015-0394-2
[9]	Tian J, Gao M, Ge G . Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm[J].Eurasip Journal on Wireless Communications & Networking, 2016(1):104-115. doi: 10.1186/s13638-016-0605-5
[10]	Ren Z, Cheng P, Chen J , et al. Dynamic activation policies for event capture in rechargeable sensor network[J]. IEEE Transactions on Parallel & Distributed Systems, 2014,25(12):3124-3134. doi: 10.1109/TPDS.2013.2297096
[11]	Wang J, Hu X, Xu X, et al. Event inter-arrival time weighted activation policies for rechargeable wireless sensors [C].Changchun:International Conference on Computer Science and Network Technology,IEEE, 2013.
[12]	Dai H, Wu X, Xu L, et al. Practical scheduling for stochastic event capture in wireless rechargeable sensor networks [C].Shanghai:Wireless Communications and Networking Conference,IEEE, 2013.
[13]	Cheng P, He S, Jiang F , et al. Optimal scheduling for quality of monitoring in wireless rechargeable sensor networks[J]. IEEE Transactions on Wireless Communications, 2013,12(6):3072-3084. doi: 10.1109/TWC.2013.050313.121691
[14]	Liu J, Zhao B, Ning Z . Mobile sensors oriented random event capturing[J].Chinese Journal of Sensors & Actuators, 2014(7):257-261. doi: 10.3969/j.issn.1004-1699.2014.02.021
[15]	Dai H, Wu X, Xu L , et al. Practical scheduling for stochastic event capture in energy harvesting sensor networks[J]. International Journal of Sensor Networks, 2015,18(1/2):85-99. doi: 10.1504/IJSNET.2015.069862
[16]	He S, Chen J,, Yau D K Y ,et al.Energy-efficient capture of stochastic events by global and local periodic network coverage [C].New Orleans:10 ^th ACM International Symposium on Mobile Ad Hoc Networking and Computing,ACM , 2009.
[17]	Mao Shishong, Wang Jinglong, Pu Xiaolong. Advanced mathematical statistics [M]. Beijing: China Higher Education Press, 1988.

参数	取值
传感器感知半径/m	1
传感器在工作状态下单位时间内消耗的能量/J	2.369
传感器在休眠状态下单位时间内消耗的能量/J	0.17
传感器工作和休眠状态互相转换一次消耗能量/J	0.05
单位时间/h	1

到达事件数 n /个	指数分布参数θ^-1/h^-1	指数分布参数 β^-1/h-1	泊松分布参数 γ^-1/个
0	1	2	4
200	0.972	0.972	3.891
400	0.964	1.191	3.846
600	0.975	1.340	3.906
800	0.996	1.455	3.937
1 000	0.984	1.550	3.922
1 200	0.991	1.578	3.953

An Online Scheduling Scheme for Random Event Capture in Asynchronous Sensor Networks

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 5

References 17

Related Articles 1

Metrics

Comments

Recommended 10