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Energy efficient chain based routing protocol for orchard wireless sensor network
Huarui Wu,Huarui Wu,Lihong Zhang,Yuling Song 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.5
Wireless sensor network nodes have limited energy, how to employ limited energy efficiently to realize effective data transmission has become a hot topic. Considering the characteristics of orchard planting in rows and shade caused by sparse random features, to improve energy efficiency of the orchard wireless sensor network and prolong network lifetime, we propose an improved chain-based clustering hierarchical routing (ICCHR) algorithm based on LEACH algorithm. The ICCHR algorithm investigates the formation of clusters, cluster head election, chain formation as well as the data transmission process, and further simulated with E-LEACH, PEGASIS-E, LEACH-1R PEGASIS and P-LEACH algorithms through MATLAB. The simulation results show that for BS at (50, 175), from the point of view of all sensor nodes death metric, the network lifetime for ICCHR algorithm prolongs about 3.29, 8.78, 35.53, and 43.11% compared with E-LEACH, PEGASIS-E, LEACH-1R PEGASIS and P-LEACH algorithms. The average energy consumption per round of the ICCHR algorithm is lower than E-LEACH, PEGASIS-E, LEACH-1R PEGASIS and P-LEACH algorithms about 4.73, 9.04, 35.60, and 43.31%. This research can provide theoretical references for the orchard complex environment wireless networking.
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A Coverage Strategy Based on Probability-aware Model in Wireless Sensor Networks
Huarui Wu,Li Zhu 보안공학연구지원센터 2014 International Journal of Future Generation Communi Vol.7 No.6
Energy limited become a key and hot point problems of wireless sensor networks. This paper proposes a Coverage Strategy Based on probability-aware Model in Wireless Sensor Networks. The strategy using the probability-aware Model, Combining with the node coverage situation, eliminate redundant nodes, establish the optimal work node set, designed to reduce the network energy consumption, set a reasonable number of working nodes. The simulation results show that the new strategy not only to improve the network coverage, but also effectively prolong the network lifetime, improve the quality of network ,Meanwhile network coverage optimization control is realized.
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( Zhili Chen ),( Chunjiang Zhao ),( Huarui Wu ),( Yisheng Miao ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.6
In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.
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