Life Cycle Of Wireless Sensor Networks Research Articles

Research on Wireless Sensor Network Coverage Path Optimization Based on Biogeography-Based Optimization Algorithm

Path selection is one of the key technologies of wireless sensor network (WSN). A reasonable choice of coverage path can improve the service quality of WSN and extend the life cycle of WSN. Biogeography-based optimization (BBO) is widely used in the field of cluster intelligent optimization because its search method has a better incentive mechanism for population evolution. In this paper, the move-in and move-out operation and mutation operation of the BBO algorithm enable WSN to find an efficient routing path. In this paper, simulation experiments are carried out in two scenarios of regular deployment and random deployment of WSN nodes. The experimental results show that the quality of the WSN coverage path solution optimized by the BBO algorithm in the two scenarios is better than that of the particle swarm algorithm and genetic algorithm.

Optimal Energy Resources Allocation Method of Wireless Sensor Networks for Intelligent Railway Systems.

The rapid increase of train speed has brought greater challenges to the safety and reliability of railway systems. Therefore, it is necessary to monitor the operation status of trains, infrastructure, and their operating environment in real time. Because the operation environment of railway systems is complex, the construction cost of wired monitoring systems is high, and it is difficult to achieve full coverage in the operation area of harsh environments, so wireless sensor networks are suitable for the status monitoring of railway systems. Energy resources of nodes are the basis of ensuring the lifecycle of wireless sensor networks, but severely restrict the sustainability of wireless sensor networks. A construction method of special wireless sensor networks for railway status monitoring, and an optimal energy resources allocation method of wireless sensor networks for intelligent railway systems are proposed in this paper. Through cluster head selection and rotating probability model, clustering generation and optimization model, and partial coverage model, the energy consumption of nodes can be minimized and balanced. The result of simulation experiment proved that the lifetime of wireless sensor networks can be maximized by the optimal energy resources allocation method based on clustering optimization and partial coverage model, based on polynomial time algorithm.

An improved CSMA/CA algorithm based on WSNs of the drug control system

A new improved CSMA/CA algorithm for wireless sensor networks (WSNs) is proposed in this paper to save energy and prolong the life cycle of WSNs. This algorithm is combined with the artificial neural network and Bayesian algorithm according to the practical applications of the drug control system of the Internet of Things. The algorithm is divided into two parts: first, the artificial neural network algorithm is used to estimate the data of WSNs, the results are the reference for the conversion of routing node frequency; second, by using the Bayesian formula, valuation method, and the CSMA/CA’s collision detection mechanism, the algorithm adjusts the frequency of the routing node and the relevant node frequency to establish the normal communication of packets sent by nodes and the aggregation node packets. In this way, it will reduce the collision detection and the back off time and avoid data packet duplication. The simulation tool-NS2 is used to configure an appropriate simulation scene for the experiment, which analyses and compares the received packet rate, the overall energy consumption of the network, and so on. The results demonstrate that the proposed algorithm ensures high energy efficiency and balanced energy consumption. Therefore the results show that the improved algorithm increases the efficiency, so that the network has the function of intelligent learning.

A Clustering Routing Protocol for Energy Balance of Wireless Sensor Network based on Simulated Annealing and Genetic Algorithm

The LEACH is a popular protocol used in wireless sensor network analysis and simulation. This paper analyses the advantages and disadvantages of LEACH protocol and then puts forward a clustering routing protocol for energy balance of wireless sensor network based on simulated annealing and genetic algorithm. When the sensor nodes are deployed randomly in the area, Firstly, we cluster the sensor nodes by simulated annealing and genetic algorithm and then calculate the cluster center of each cluster. If the energy of the node in the cluster is higher than the average energy of the cluster, it will become the candidate cluster head; at last the candidate cluster head becomes the cluster head according to the distance from the cluster center of the cluster. Simulations show that the new program could improve Energy Hotspot caused by the uneven distribution of cluster head in LEACH protocol, thus it can balance the wireless sensor network load balance and extend the lifecycle of wireless sensor network.

Erasure-Coding Algorithm in Mobile Low-Duty-Cycle Opportunistic Networks Based on Energy-Aware

PDF HTML阅读 XML下载 导出引用 引用提醒 基于能量感知的移动低占空比机会网络纠删编码算法 DOI: 10.3724/SP.J.1001.2013.04232 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(60933011);国家重点基础研究发展计划(973)(2011CB302902);国家科技重大专项(2010ZX03004-002-01);四川省科技支撑计划(2010GZ0170);四川大学青年教师科研启动基金(2011SCU11091) Erasure-Coding Algorithm in Mobile Low-Duty-Cycle Opportunistic Networks Based on Energy-Aware Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:低占空比(low-duty-cycle,简称LDC)技术是当前延长无线传感器网络生命周期的最关键技术,为了有效延长机会网络生命周期,将低占空比技术引入机会网络,形成LDC机会网络.但是,现有机会网络路由算法不能很好地适应LDC环境,其性能会大幅度下降.为了解决该问题,提出一种基于能量感知的移动低占空比机会网络纠删编码算法E-EC.仿真实验结果表明,与现有的典型机会网络路由算法相比,E-EC算法在延长移动机会网络生命周期以及增加数据传输成功率等方面带来明显的性能提升. Abstract:Low-Duty-Cycle (LDC) is the most important technique in increasing the lifecycle of wireless sensor networks. This paper imports low duty cycle technology into opportunistic networks to extend the lifecycle of opportunistic networks effectively. However, the existing routing algorithms for opportunistic networks perform poorly in LDC environment. To solve this problem, this paper proposes an erasure-coding algorithm based on energy-aware (E-EC) for LDC opportunistic networks. Simulation results show that, compared with existing classical algorithms, E-EC algorithm achieves significant performance improvement in terms of life cycle and data success rate. 参考文献 相似文献 引证文献

Distributed Data Aggregation Algorithm in Wireless Sensor Networks

Considering the limited resources and data transmission redundancy of wireless sensor networks, this paper proposes a distributed data aggregation algorithm based on lifting wavelet transform (DDAA-LWT), and carries out the rational design. The algorithm distributes the computing quantity which the lifting wavelet transform requires to all network nodes, eliminates the additional computing and wireless transmission, reduces the information redundancy of network, greatly prolongs the lifecycle of wireless sensor networks. Simulation results demonstrate that the distributed data aggregation algorithm based on lifting wavelet transform (DDAA-LWT) can effectively aggregate the original sensed data and decrease the energy consumption, it significantly outperforms the data aggregation algorithm based on traditional wavelet transform (DAA-WT).

Energy Optimization through Position ResponsiveRouting Protocol (PRRP) in Wireless Sensor Network

Wireless Sensor Networks (WSNs) are consist of very tiny nodes structure, with very small batteries without having facility to recharge it. It works under any hard circumstances, hence this type of network is gaining high importance day by day. Maximum focus of researchers is to enhance or optimized its energy efficiency level. Routing protocol is the main energy expensive operation of sensor networks which utilize maximum energy resources of sensor network. Already a good number of routing protocols has been designed for energy efficiency or optimization with different approaches under controlled conditions. With this research we try to propose energy optimization of wireless sensor network through our proposed position response routing protocol (PRRP), under certain controlled parametric consideration. Research results shows a significant energy optimization in the life cycle of WSN. Index Terms—WSN, energy efficient, WSN routing protocol, GPS, PRRP, energy optimization