海水养殖监测系统无线传感器网络节点数据传输研究

文章将无线传感器网络应用于海水养殖监测系统,根据海上养殖监测的特点,提出一种适合于海水养殖的节点数据传输机制,对应于正常数据和异常数据,采用自适应的数据传输机制进行数据传输,降低传输数据量,进行了网络能量优化。仿真结果表明,在异常数据率较小的情况下,自适应的数据传输中节点产生的平均数据量和平均冗余数据量比普通的事件驱动型数据传输要小很多,大大降低了能耗,提高了传输效率。在信道传输质量比较差的情况下,自适应的数据传送机制提高传输效率更明显。     

一维无线传感器网络分簇通信方案能量效率研究

为了提高无线传感器网络的能量有效性,该文在分析基于分簇的传统方案和协作分集数据传输方案的能量效率基础上,提出了一维传感器网络分簇多用户分集数据传送方案(CMDDTS)。理论分析表明能量开销依赖于数据融合比、簇内通信的发送功率、簇间通信的接收功率以及电路消耗的功率和簇内传感器的数目,仿真结果验证了所提方案的能量效率优于传统方案和协作分集数据传送方案。     

无线传感器网络中基于剩余能量的联合选举动态成簇路由算法

针对无线传感器网络中突发事件监测等响应式网络应用,提出了一种基于能量的联合选举动态成簇算法。基于节点剩余能量,在事件区域内周期性地进行簇首选举,建立以簇首为根的簇树结构对事件区域内的数据进行搜集融合,从而减少网络中传输的数据量。仿真结果表明:该算法降低了节点平均能耗,具有良好的能量均衡效果,延长了网络生存时间。     

无线传感器网络能量高效混合MAC算法

针对无线传感器网络MAC协议中存在的能耗问题,提出了能量高效的无线传感器网络混合MAC(EEH-MAC)算法,采用基于TDMA机制的时槽系数动态调整簇内节点的时槽大小来降低数据的传输时延;同时,对部分不需要数据传输的节点不分配时槽来减少能耗;按簇内节点剩余能量系数形成时槽分配顺序来减少状态转换的能耗;在簇头之间采用CSMA/CA机制的随机分配策略进行通信.仿真结果表明,EEH-MAC协议能有效减少能耗并延长网络生命周期.     

一种多媒体传感器网络低能耗分簇协议

多媒体传感器网络面临的主要挑战是在能量受限的情况下传输大量数据。在经典分簇协议LEACH的基础上,提出一种考虑数据量的多媒体传感器网络低能耗分簇协议。在簇头选举阶段,选择剩余能量多和数据量大的节点作为簇头;在成簇阶段,同时考虑节点到簇头的通信距离和节点的数据量让节点加入簇。仿真结果表明,提出的协议能有效提高网络的生命周期。     

一种无线传感器网络中的簇头变化机制

针对无线传感器网络节点密集和节点能量有限等特点,提出了一种簇头变化机制,数据业务节点使用指数退避算法来竞争本簇的簇头,而原簇头转入休眠状态。网络仿真结果表明该机制可提高能量效率和降低传输时延。     

无线传感器网络LEACH协议的研究与改进

无线传感器网络(WSN)的数据传输不能与路由协议分离,高效的能量传输是无线传感器网络中最重要的因素之一。针对LEACH簇头分布的不均匀以及与基站距离的不同,提出了一种改进的LEACH算法,该算法考虑剩余能量和最优簇头,与现有的LEACH协议相比,该协议降低了能耗。     

基于最优阶估计与分布式分簇的传感器网络数据压缩方法研究

在无线传感器网络的诸多应用中,被监测区域发生异常情况的概率通常较小,正常情况下,同一传感器节点在前后连续时刻所采集的数据具有时间相关性,处于相邻区域的不同传感器节点在同一时刻所采集的数据具有空间相关性,发送存在时间、空间冗余的数据至基站必将耗费节点大量的能量。该文提出了基于最优阶估计和分布式分簇的传感器网络数据压缩方法,利用节点采集数据的时空相关性,基于最优阶估计在基站处建立相关系数,经分布式分簇,节点仅需传送少量数据,基站根据时空相关性恢复原始数据。仿真结果表明应用该算法,可以有效减少传感器网络中冗余数据传输量和节点能耗,进而延长系统寿命。     

无线传感器网络数据收集方案改进方法研究

当前,无线传感器网络成为研究热点,其数据的传输安全性受到广泛关注。文章提出了一种基于改进的LEACH协议的无线传感器网络数据收集方案,降低了数据传输过程中的能量损耗。     

物联网中基于无线能量传输的能量均衡路由算法

本文提出了一种基于无线能量传输的能量均衡路由算法(WPTRA).该算法结合传统的分簇路由协议,采用基于剩余能量级别的簇头选取策略进行分簇.在数据传输阶段,当网络中某一节点能量低于预设的临界能量值TEMIN时,通过计算无线能量传输效率和传输距离之间的关系,选择其附近能量较高的节点,通过无线能量传输技术对其进行能量补充.     

Distributed Transmission Power Control for Network Programming in Wireless Sensor Networks

In wireless sensor networks, the necessity of network programming becomes more and more important due to the inaccessibility of the sensor nodes. Because the network programming produces a large amount of data, it consumes a great deal of energy and causes the network to suffer from much interference. Many conventional studies regarding the network programming attempted to reduce the energy consumption and the interference effect. However, they overlook transmission power effect on the energy-efficiency and the interference problem. In this paper, we present a novel network programming protocol that controls the transmission power at each sender node in a distributed manner. The protocol deals not only with the energy consumption of individual sensor node but also the network load distribution. Moreover, it reduces the interference effect on the network by decreasing the average transmission power of the sensor nodes. We verify that our protocol extends the lifetime of the sensor network and decreases the packet losses through simulation results.     

一种适用于Ad hoc网络的DCF协议自适应功率控制机制

该文对载波检测无线网络中的冲突干扰问题进行了分析,在此基础上提出了一种适用于Ad hoc网络的DCF协议自适应功率控制机制。该机制能根据各个接收节点的通信状况,自适应的调整接收节点的CTS帧发送功率和收方决定的数据帧发送功率。仿真证明,在DCF协议中引入该机制后,不仅能有效节省节点能耗,延长网络的生存时间,还能同时增大网络的频率空间复用度,提高网络的平均吞吐量。     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

Monitoring power transmission lines using a wireless sensor network

Power transmission is the bulk transfer of electrical energy from power plants to sub‐stations. A wireless sensor network is a promising technology for transmission line monitoring due to its low cost, easy installation, large‐scale coverage, and fault tolerance characteristics. A wireless sensor network is application‐specific; therefore, we investigate the new features and requirements of the wireless sensor network used in transmission line monitoring. Then, we propose an efficient wireless sensor network framework, which includes a clustering algorithm to simplify network management and to balance the network's energy consumption and a hybrid media access control (MAC) (H‐MAC) protocol to handle traffic variability. The framework takes advantage of the features of network topology and traffic pattern to optimize the protocols' performance on real time and energy efficiency. The results indicate that the H‐MAC shows a significant improvement in the network's reliability, real‐time performance, and energy efficiency, and the cluster hierarchy can balance the network's energy consumption. Furthermore, the cluster hierarchy also prolongs the network's lifetime. Copyright © 2014 John Wiley & Sons, Ltd.     

无线传感器网络S-MAC协议的能耗改进

无线传感器节点由于能量的耗尽而失效或者废弃,造成相应监测区域的空白,能耗问题一直是传感器网络介质访问控制（MAC）协议研究的重点问题之一。在S-MAC协议采用周期性侦听和睡眠机制、自适应侦听机制等方式改善网络能耗的基础上提出选择性睡眠、动态调整占空比、发送功率控制三种改进方法。通过NS2仿真实验,改进后S-MAC协议的能耗明显得到优化。     

Energy Efficient Four Level Cooperative Opportunistic Communication for Wireless Personal Area Networks (WPAN)

For wireless sensor networks (WSNs), energy is a scarce resource. Due to limited battery resources, the energy consumption is the critical issue for the transmission as well as reception of the signals in the wireless communication. WSNs are infrastructure-less shared network demanding more energy consumption due to collaborative transmissions. This paper proposes a new cooperative opportunistic four level model for IEEE 802.15.4 wireless personal area network. The average per node energy consumption is observed merely about 0.17 mJ for the cooperative wireless communication which proves the proposed mechanism to be energy efficient. This paper further proposes four levels of cooperative data transmission from source to destination to improve network coverage with energy efficiency.     

面向混合业务的无线传感器网络能量有效接入策略

研究了在实时业务和非实时业务同时存在的混合背景下,非实时业务的无线传感器节点自适应侦听和睡眠的动态接入机制。网络节点处于睡眠状态时所需的能量很低,节约了无线传感器网络节点的平均能量消耗;但是,过长的睡眠时间可能使得网络节点错失传输机会。因此,根据信道的使用情况,合理地设定无线传感器网络节点的睡眠时间,能够在网络能量消耗和传输效率之间进行调整,从而最大化无线传感器网络的能量传输效率。首先,利用连续时间 Markov 方法对问题进行建模,并利用基于摄动分析理论对系统模型进行分析,获得求解无线传感器网络能量效率最大化的最优睡眠时间梯度算法。最后通过理论结果和计算机仿真模拟的对比,验证了推荐方法的可行性。     

A fault‐tolerant energy‐efficient clustering protocol of a wireless sensor network

Energy efficiency in specific clustering protocols is highly desired in wireless sensor networks. Most existing clustering protocols periodically form clusters and statically assign cluster heads (CHs) and thus are not energy efficient. Every non‐CH node of these protocols sends data to the CH in every time slot of a frame allocated to them using the time division multiple access scheme, which is an energy‐consuming process. Moreover, these protocols do not provide any fault tolerance mechanism. Considering these limitations, we have proposed an efficient fault‐tolerant and energy‐efficient clustering protocol for a wireless sensor network. The performance of the proposed protocol was tested by means of a simulation and compared against the low energy adaptive clustering hierarchy and dynamic static clustering protocols. Simulation results showed that the fault‐tolerant and energy‐efficient clustering protocol has better performance than both the low energy adaptive clustering hierarchy and dynamic static clustering protocols in terms of energy efficiency and reliability. Copyright © 2012 John Wiley & Sons, Ltd.     

Energy-efficient data sensing and routing in unreliable energy-harvesting wireless sensor network

Energy-harvesting wireless sensor network (WSN) is composed of unreliable wireless channels and resource-constrained nodes which are powered by solar panels and solar cells. Energy-harvesting WSNs can provide perpetual data service by harvesting energy from surrounding environments. Due to the random characteristics of harvested energy and unreliability of wireless channel, energy efficiency is one of the main challenging issues. In this paper, we are concerned with how to decide the energy used for data sensing and transmission adaptively to maximize network utility, and how to route all the collected data to the sink along energy-efficient paths to maximize the residual battery energy of nodes. To solve this problem, we first formulate a heuristic energy-efficient data sensing and routing problem. Then, unlike the most existing work that focuses on energy-efficient data sensing and energy-efficient routing respectively, energy-efficient data sensing and routing scheme (EEDSRS) in unreliable energy-harvesting wireless sensor network is developed. EEDSRS takes account of not only the energy-efficient data sensing but also the energy-efficient routing. EEDSRS is divided into three steps: (1) an adaptive exponentially weighted moving average algorithm to estimate link quality. (2) an distributed energetic-sustainable data sensing rate allocation algorithm to allocate the energy for data sensing and routing. According to the allocated energy, the optimal data sensing rate to maximize the network utility is obtained. (3) a geographic routing with unreliable link protocol to route all the collected data to the sink along energy-efficient paths. Finally, extensive simulations to evaluate the performance of the proposed EEDSRS are performed. The experimental results demonstrate that the proposed EEDSRS is very promising and efficient.     

Design and deployment of a smart system for data gathering in aquaculture tanks using wireless sensor networks

The design of monitoring systems for marine areas has increased in the last years. One of the many advantages of wireless sensor networks is the quick process in data acquisition. The information from sensors can be processed, stored, and transmitted using protocols efficiently designed to energy saving and establishing the fastest routes. The processing and storing of data can be very useful for taking intelligent decisions for improving the water quality. The monitoring of water exchange in aquaculture tanks is very important to monitor the fish welfare. Thus, this paper presents the design, deployment, and test of a smart data gathering system for monitoring several parameters in aquaculture tanks using a wireless sensor network. The system based on a server is able to request and collect data from several nodes and store them in a database. This information can be postprocessed to take efficient decisions. The paper also presents the design of a conductivity sensor and a level sensor. These sensors are installed in several aquaculture tanks. The system was implemented using Flyport modules. Finally, the data gathering system was tested in terms of consumed bandwidth and the delay Transmission Control Protocol (TCP) packets delivering data from the sensors.