Computer Science ›› 2015, Vol. 42 ›› Issue (7): 162-164, 181.doi: 10.11896/j.issn.1002-137X.2015.07.035

Previous Articles     Next Articles

Adaptive Sampling Algorithm Based on TCP Congestion Strategy

YANG Ming-xia, WANG Wan-liang and SHAO Peng-fei   

  • Online:2018-11-14 Published:2018-11-14

Abstract: We presented the design of a novel adaptive sampling technique based on TCP congestion strategy,in which the temporal data correlations provide an indication of the prevailing environmental conditions and are used to adapt to the sensing rate of a sensor node.It uses irregular data series prediction to reduce sampling rate in combination with change detection to maintain data fidelity.The prediction method employs Wright’s extension to Holt’s method of exponential double sampling (EDS) coupled with a change detection mechanism based on exponentially weighted moving averages (EWMA).The main advantages are that it does not require heavy computation,incurs low memory and communication overhead and the prediction model can be implemented with ease on resource constrained sensor nodes.

Key words: Wireless sensor networks,Adaptive sampling,Exponential double smoothing,Sampling fraction,Miss ratio

[1] Gupta M,Shum L V,Bodanese E,et al.Design and evaluation of an adaptive sampling strategy for a wireless air pollution sensor network[C]∥2011 IEEE 36th Conference on Local Computer Networks (LCN).IEEE,2011:1003-1010
[2] Werner-Allen G,et al.Monitoring volcanic eruptions with awireless sensor network[C]∥Proceedings of the Second European Workshop on Wireless Sensor Networks,2005.2005:108-120
[3] Alippi C,et al.Energy management in wireless sensor networks with energy-hungry sensors[J].Instrumentation & Measurement Magazine,IEEE,2009,12(2):16-23
[4] Alippi C,et al.Adaptive Sampling for Energy Conservation inWireless Sensor Networks for Snow Monitoring Applications[C]∥IEEE International Conference on Mobile Adhoc and Sensor Systems(MASS 2007).2007:1-6
[5] Alippi C,Roveri M.An adaptive CUSUM-based test for signalchange detection[C]∥Proceedings of 2006 IEEE International Symposium on Circuits and Systems(ISCAS 2006).2006:5752-5755
[6] Wright D J.Forecasting Data Published at Irregular Time Intervals Using an Extension of Holt’s Method[J].Management Scie-nce,1986,32(4):499-510

No related articles found!
Full text



[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .