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Articles by Lejiang Guo
Total Records ( 5 ) for Lejiang Guo
  Zhuo Liu , Bingwen Wang and Lejiang Guo
  In Wireless Sensor Network (WSN), all nodes are energy constrained. Clustering is a kind of energy efficient algorithm, while using a virtual backbone to organize the nodes is a better way. Although, there is no physical backbone infrastructure, a virtual backbone can be formed by constructing a Connected Dominating Set (CDS). The CDS of a graph representing a network has a significant impact on an efficient design of routing algorithms in WSN. A good CDS should first and foremost be small, additionally, it should have other characteristics such as robustness to node failures and low stretch. In this paper, we present a taxonomy and general classification of CDS construction algorithms. We survey different CDS construction algorithms for WSNs.
  Lejiang Guo , Bingwen Wang , Zhuo Liu and Wei Wang
  Because of the limited energy in wireless sensor networks, the research on routing technology on the network layer is pivotal in the architecture of wireless sensor networks. Aiming at the defect problem of the clustering network, this study presents an energy equilibrium routing algorithm based on Cluster-head Prediction for Wireless Sensor Networks (CP-EERP). The algorithm uses the cluster-head prediction mechanism which improves cluster-head lifetime, balances the energy between nodes and prolongs the network lifetime. CP-EERP includes network initialization phase, cluster building phase, data transmission phase and cluster-head prediction phase. The simulation result shows that the algorithm performs better, in terms of power efficiency and the number of communication neighbors, than the classic routing algorithm.
  Wei Wang , Bingwen Wang , Zhuo Liu and Lejiang Guo
  In Wireless Sensor Networks (WSNs), it is of great importance for fault diagnosis in the WSNs to ensure the accuracy of the information collected from the network, for the low cost and the deployment of a large number of sensor nodes in uncontrolled or harsh or hostile environments. In this study, we have presented a protocol, named CRFDA (Cluster-Based Real-time Fault Diagnosis aggregation algorithm for WSNs), which is based on the comparison approach aiming at achieving a correct and complete diagnosis for hierarchical WSNs. CRFDA is based on clustering in the network which can be carried out simultaneously in all cluster. Besides, it is a real-time diagnosis method and can be spontaneously implemented in each round. It is known from CRFDA that both hard and soft faults can be diagnosed correctly in the finite time. Algorithm correctness, communication complexity and time complexity proofs are presented in this study. Compared with other existing protocols, CRFDA performs better. We have also developed a simulator by NS-2 (using LEACH) to analyze the correctness of our algorithm. The simulation results show that our algorithm is a correct and efficient fault diagnosis algorithm in WSNs.
  Wei Wang , Bingwen Wang , Zhuo Liu , Lejiang Guo and Wei Xiong
  In Wireless Sensor Networks (WSNs), since the network consists of low-cost sensor nodes with finite battery power, power efficient strategies must be applied for data transmission in order to prolong the network lifetime. It is important to minimize the total energy consumption in each round so that the network lifetime is maximized. In this study, we have proposed a new energy efficient protocol, named CTPEDCA (Cluster-Based and Tree-Based Power Efficient Data Collection and Aggregation Protocol for WSNs), which using the full distributed in hierarchical WSNs. CTPEDCA is based on clustering and Minimum Spanning Tree (MST) routing strategy for cluster heads. We use the MST to improve the transmission routing mechanism between the cluster heads so that let only one cluster head communicate directly with the faraway base station in each round. The simulation results show that CTPEDCA is better than LEACH; CTPEDCA can more balance the energy consumption of all nodes, particularly as the cluster head nodes in each round and prolong the lifetime of the networks. It is worth to note that our algorithm is very fast, its time complexity is O(ElogV), where V is the set of cluster heads, therefore, the time complexity is small.
  Lejiang Guo , Bingwen Wang , Wei Wang , Zhuo Liu and Chao Gao
  Wireless sensor network is a complex wireless network (WSN) which has a large number of network nodes. Based on neural network theory and methods, this study uses neuron to describe the WSN node and constructs neural network model for WSN. The neural network model includes three aspects: WSN node neuron model, WSN node control model and WSN node connection model. In order to maximize the network life-cycle, this study analyzes Hopfield method and proposes the general design method and procedure of energy function. It discusses the relationship between network equilibrium and the minimum point of energy function. The result shows that the neural model of wireless sensor networks brings convenience for WSN and provides a certain theoretical foundation for the applications of the neural networks.
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