Distributed trajectory design for data gathering using mobile sink in wireless sensor networks

Several studies have demonstrated the benefits of using a mobile sink (MS) to reduce energy consumption resulting from multi-hop data collection using a static sink in wireless sensor networks (WSNs). However, using MS may increase data delivery latency as it needs to visit each sensor node in the network to collect data. This is a critical issue in delay-sensitive applications where all sensed data must be gathered within a given time constraint. In this paper, we propose a distributed data gathering protocol utilizing MS for WSNs. The proposed protocol designs a trajectory for the MS, which minimizes energy consumption and delay. Our protocol operates in four main phases: data sensing, rendezvous point (RP) selection, trajectory design, and data gathering. In data sensing, a number of deployed sensor nodes keep sensing the target field for a specific period of time to capture events. Then, using a cluster-based RP selection algorithm, some sensor nodes are selected to become RPs based on local information. The selected RPs are then used to determine a trajectory for the MS. To do so, we propose three trajectory design algorithms that support different types of applications, namely reduced energy path (REP), reduced delay path (RDP), and delay bound path (DBP). The MS moves through the constructed path to accomplish its data gathering according to an effective scheduling technique that is introduced in this work. We validate the proposed protocol via extensive simulations over several metrics such as energy, delay, and time complexity.     

Novel service protocol for supporting remote and mobile users in wireless sensor networks with multiple static sinks

A wireless sensor network typically consists of users, a sink, and a number of sensor nodes. The users may be remotely connected to a wireless sensor network and via legacy networks such as Internet or Satellite the remote users obtain data collected by the sink that is statically located at a border of the wireless sensor network. However, in practical sensor network applications, there might be two types of users: the traditional remote users and mobile users such as firefighters and soldiers. The mobile users may move around sensor fields and they communicate with the static sink only via the wireless sensor networks in order to obtain data like location information of victims in disaster areas. For supporting the mobile users, existing studies consider temporary structures. However, the temporary structures are constructed per each mobile user or each source nodes so that it causes large energy consumption of sensor nodes. Moreover, since some of them establish the source-based structure, sinks in them cannot gather collective information like mean temperature and object detection. In this paper, to effectively support both the remote users and the mobile users, we propose a novel service protocol relying on the typical wireless sensor network. In the protocol, multiple static sinks connect with legacy networks and divide a sensor field into the number of the multiple sinks. Through sharing queries and data via the legacy networks, the multiple static sinks provide high throughput through distributed data gathering and low latency through short-hops data delivery. Multiple static sinks deliver the aggregated data to the remote users via the legacy networks. In case of the mobile users, when a mobile user moves around, it receives the aggregated data from the nearest static sink. Simulation results show that the proposed protocol is more efficient in terms of energy consumption, data delivery ratio, and delay than the existing protocols.     

Nature inspired discrete firefly algorithm for optimal mobile data gathering in wireless sensor networks

Nowadays wireless sensor networks enhance the life of human beings by helping them through several applications like precision agriculture, health monitoring, landslide detection, pollution control, etc. The built-in sensors on a sensor node are used to measure the various events like temperature, vibration, gas emission, etc., in the remotely deployed unmanned environment. The limited energy constraint of the sensor node causes a huge impact on the lifetime of the deployed network. The data transmitted by each sensor node cause significant energy consumption and it has to be efficiently used to improve the lifetime of the network. The energy consumption can be reduced significantly by incorporating mobility on a sink node. Thus the mobile data gathering can result in reduced energy consumption among all sensor nodes while transmitting their data. A special mobile sink node named as the mobile data transporter (MDT) is introduced in this paper to collect the information from the sensor nodes by visiting each of them and finally it sends them to the base station. The Data collection by the MDT is formulated as a discrete optimization problem which is termed as a data gathering tour problem. To reduce the distance traveled by the MDT during its tour, a nature-inspired heuristic discrete firefly algorithm is proposed in this paper to optimally collect the data from the sensor nodes. The proposed algorithm computes an optimal order to visit the sensor nodes by the MDT to collect their data with minimal travel distance. The proposed algorithm is compared with tree-based data collection approaches and ant colony optimization approach. The results demonstrate that the proposed algorithm outperform other approaches minimizing the tour length under different scenarios.     

基于ARMA模型的无线传感器网络可信数据采集方法

在传感器节点受到能量和带宽严重制约的情况下,如何合理、有效地利用有限的资源来采集有效、可信的数据,成为当前无线传感器网络（Wireless Sensor Network,WSN）研究的热点问题之一。在分析了大量WSN感知数据的基础上,利用时间序列对数据进行建模处理,得出了适合WSN的数据处理模型ARMA（1,1）,同时利用基于移动Agent的中间件技术,提出了基于ARMA的无线传感器网络可信数据采集方法。理论和实验结果表明,该方法可保证采集数据的高度可信,同时显著提高了网络的整体性能,有效的减少网络的能耗,延长了网络的生命周期。     

一种无线社区医疗监护网络的设计

临床护理中的很多医疗监护设备,需要实时采集病人的血压、心电、血氧和体温等指标,但这些设备一般存在体积大、耗电高、设备固定以及接线繁多等缺点。设计了一种部署在居民社区、小区的无线传感器网络,并提出一种MHDC-LEACH(改进的多跳分簇路由)算法。仿真结果表明,与传统的LEACH算法相比,该算法可减少网络中节点与基站通信的次数,均衡网络负载,优化数据传输路由,延长网络的生命周期,有效减少死亡节点个数。当网络覆盖区域增大时,最多可节约网络能量约20%。     

移动协助传感器网络中Sink的路径优化策略

在无线传感器网络中引入移动Sink来解决。静态无线传感器网络(所有节点均为静止)存在的能量空洞、冗余覆盖和热点等问题。传感器节点将数据发送给汇聚节点(CP,collection point),移动Sink访问CP节点收集数据。提出了一种最短移动距离最小能耗的路径优化模型(MEMD)。证明了该模型是一个NP-hard问题,给出了一种基于效用的贪心启发式方法用于确定最佳的CP节点队列。为了在规定的最大传输延时的范围内访问尽可能多的CP节点,提出了一种基于CP节点访问概率的路径选择算法。通过模拟实验以及实验床的真实数据,提出的算法能很好地在满足延时要求的同时节约网络的能量。     

基于最优簇头数的无线传感器网络安全LEACH路由协议

提出一种基于最优簇头数的无线传感器网络安全LEACH路由协议,该协议模拟真实传感器网络情况建立了三维空间模型,通过理论分析和仿真实验方法得到LEACH协议的最优簇头数,使网络能耗达到最优。在能量优化的同时把增强安全性作为设计目标,根据LEACH协议的特点,采用预置共享密钥对的方法,在簇头选举和数据传输阶段采用在数据包尾部捎带加密信息的方法,实现数据加密,在只增加少量能量开销的情况下数据机密性得到了实现。仿真验证了新协议的有效性,在能量优化的同时提高了路由安全性,延长了网络生命期。     

无线传感器网络的分区异构分簇协议研究

针对无线传感器网络能量受限和路由协议中节点能量消耗不均衡的问题,提出一种新的无线传感器网络的分区异构分簇协议(PHC协议).该协议的核心是将3种不同能量等级的节点根据能量的不同分别部署在不同区域,能量较高的高级节点和中间节点使用聚类技术通过簇头直接传输数据到汇聚点,能量较低的普通节点则直接传输数据到汇聚点.仿真结果表明,该协议通过对节点合理的分配部署,使簇头分布均匀,更好地均衡了节点的能量消耗,延长了网络的稳定期,提高了网络的吞吐量,增强了网络的整体性能.     

能量有效的多级无线传感网络数据采集方法

The majority of the energy consumption by the sensors is the energy requirement for data transmission in Wireless Sensor Networks (WSNs). Therefore, introducing mobile collectors to collect data instead of multi-hop data relay is essential. However, for many proposed data gathering approaches, long data delay is the main problem. Hence, the problem of how to decrease the energy consumption and the data delay needs to be solved. In this paper, a low delay data collection mechanism using multiple mobile collectors is proposed. First, a self-organization clustering algorithm is designed. Second, sensor nodes are organized into three-level clusters. Then a collection strategy based on the hierarchical structure is proposed, which includes two rules to dispatch mobile collectors rationally. Simulation results show that the proposed mechanism is superior to other existing approaches in terms of the reduction in energy expenditure and the decrease in data delay.     

M‐RPSS: A modified RPSS for path scheduling of mobile sink in wireless sensor network

In wireless sensor networks (WSNs), data gathering is the main concern, since it directly affects the network lifetime and data latency. Rendezvous Point Selection Scheme (RPSS) is a mobile sink node approach; it offers superior performance than its preceding mobile sink schemes like Rendezvous Design for Variable Track (RD‐VT), RD‐VT with Steiner Minimum Tree (RD‐VT‐SMT), and Weight Rendezvous Planning with Steiner Minimum Tree (WRP‐SMT). However, a more uniform distribution of the rendezvous node leads to less energy consumption in WSNs. The more optimum path offers less data latency. In the proposed approach, we use particle swarm optimization (PSO) to find the optimum rendezvous point and adaptive PSO (APSO) to find an optimum path by solving the travelling salesman problem. By rigorous simulation, we prove that modified RPSS (M‐RPSS) increases the network lifetime by more than 10% and decreases the data latency.     

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

Wireless sensor and actuator networks are composed of sensor and actuator nodes interconnected via wireless links. The actuators are responsible for taking prompt decisions and react accordingly to the data gathered by sensor nodes. In order to ensure efficient actions in such networks, we propose a new routing protocol that provides QoS in terms of delay and energy consumption. The network is organized in clusters supervised by CHs (Cluster-Heads), elected according to important metrics, namely the energy capability, the riches of connectivity, which is used to select the CH with high node density, and the accessibility degree regarding all the actuators. The latter metric is the distance in number of hops of sensor nodes relative to the actuator nodes. This metric enhances more the network reliability by reducing the communication delay when alerting the actuator nodes, and hence, reducing the energy consumption. To reach efficiently the actuator nodes, we design a delay and energy sensitive routing protocol based on-demand routing approach. Our protocol incurs less delay and is energy efficient. We perform an evaluation of our approach through simulations. The obtained results show out performance of our approach while providing effective gain in terms of communication delay and energy consumption.     

Communication Coverage in Wireless Passive Sensor Networks

System lifetime of wireless sensor networks (WSN) is inversely proportional to the energy consumed by critically energy-constrained sensor nodes during RF transmission. In that regard, modulated backscattering (MB) is a promising design choice, in which sensor nodes send their data just by switching their antenna impedance and reflecting the incident signal coming from an RF source. Hence, wireless passive sensor networks (WPSN) designed to operate using MB do not have the lifetime constraints of conventional WSN. However, the communication performance of WPSN is directly related to the RF coverage provided over the field the passive sensor nodes are deployed. In this letter, RF communication coverage in WPSN is analytically investigated. The required number of RF sources to obtain interference-free communication connectivity with the WPSN nodes is determined and analyzed in terms of output power and the transmission frequency of RF sources, network size, RF source and WPSN node characteristics.     

无线传感网络中基于蚁群的路由算法

In the wireless sensor networks, high efficient data routing for the limited energy resource networks is an important issue. By introducing Ant-colony algorithm, this paper proposes the wireless sensor network routing algorithm based on LEACH. During the construction of sensor network clusters, to avoid the node premature death because of the energy consumption, only the nodes whose residual energy is higher than the average energy can be chosen as the cluster heads. The method of repeated division is used to divide the clusters in sensor networks so that the numbers of the nodes in each cluster are balanced. The basic thought of ant-colony algorithm is adopted to realize the data routing between the cluster heads and sink nodes, and the maintenance of routing. The analysis and simulation showed that the proposed routing protocol not only can reduce the energy consumption, balance the energy consumption between nodes, but also prolong the network lifetime.     

一种基站可移动传感器网络再编程协议

 本文针对基站可移动传感器网络实现了一再编程协议MovPro.该协议可以将新的二进制程序通过多跳的形式下发到网络内的节点上并使之运行.该协议的大致过程描述为,当基站在网络内移动时,基站将数据发送给它移动轨迹上的节点.节点收到部分二进制代码后通过窗口交换的形式将二进制代码传播到整个网络.MovPro是第一个在基站可移动传感器网络的真实系统.本文通过多种方式减少通信开销,并通过二级存储的方式减少外部flash的写次数.实验表明MovPro适用于基站可移动传感器网络.     

传感器网络中节点能量有效均衡的Top-k查询技术

无线传感器网络中top-k查询处理的节点能量高效以及实现各节点的能量消耗均衡,可以有效延长网络的生命周期。该文提出一种基于采样技术和节点空间相关性,来实现节点的能量均衡和高效的查询处理算法,称为能量均衡采样(,)近似top-k算法EBSTopk(,)。首先对传感器网络进行分区处理,利用区域内两两节点间的空间相关性对其建立线性回归预测模型和高斯预测模型;然后根据用户给定的相对误差界和置信水平1-建立节点高相关性预测准则;最后根据上述预测模型和准则,提出基于反复随机采样的能量均衡算法EBSTopk(,)-LR和EBSTopk(,)-MG。实验表明,所提出的EBSTopk(,)算法减少了无线传感器网络中的全局能量消耗,且在多次top-k查询后各节点的能量消耗达到均衡。     

无线传感器网络中移动sink节点的路径规划

在无线传感器网络中,大量感知数据汇集到sink节点的采集方法会导致sink节点附近的节点能量耗尽,造成能量空洞。针对该问题,利用移动的sink节点进行数据收集是一种解决方法,其中移动sink的路径规划成为一个重要的问题。提出了一个移动sink路径规划算法,将无线传感器中随机分布的节点划分为不同的子区域,寻找sink节点移动的最佳转向点,最终得到最优的移动路径,以实现无线传感器网络生命周期最大化。仿真实验表明,与现有方案相比,该算法能显著延长网络的生命周期。     

On reducing delay in mobile data collection based wireless sensor networks

In a wireless sensor network, battery power is a limited resource on the sensor nodes. Hence, the amount of power consumption by the nodes determines the node and network lifetime. This in turn has an impact on the connectivity and coverage of the network. One way to reduce power consumed is to use a special mobile data collector (MDC) for data gathering, instead of multi-hop data transmission to the sink. The MDC collects the data from the nodes and transfers it to the sink. Various kinds of MDC approaches have been explored for different assumptions and constraints. But in all the models proposed, the data latency is usually high, due to the slow speed of the mobile nodes. In this paper, we propose a new model of mobile data collection that reduces the data latency significantly. Using a combination of a new touring strategy based on clustering and a data collection mechanism based on wireless communication, we show that the delay can be reduced significantly without compromising on the advantages of MDC based approach. Using extensive simulation studies, we analyze the performance of the proposed approach and show that the packet delay reduces by more than half when compared to other existing approaches.     

A Pre-Determined Nodes Deployment Strategy of Two-Tiered Wireless Sensor Networks Based on Minimizing Cost

Nodes deployment is a fundamental factor in determining the connectivity, coverage, lifetime and cost of wireless sensor networks. In this paper, a two-tiered wireless sensor networks consisting of sensor clusters and a base station is considered. Within a sensor cluster, there are many sensor nodes and a relay node. We focus on the deployment strategy for sensor nodes and relay nodes to minimize cost under some constraints. Several means are used. The regular hexagonal cell architecture is employed to build networks. Based on the analysis of energy consumption of sensors and cost of network, an integer programming model is presented to minimize the cost. By the model, number of layers of sensor cluster is determined. In order to balance the energy consumption of sensors on the identical layer, a uniform load routing algorithm is used. The numerical analysis and simulation results show that the waste of energy and cost of wireless sensor networks can be effectively reduced by using the strategy.     

物联网感知层多路径传输策略研究

多路径数据传输是无线传感器网络亟需解决的一个关键问题.本文针对节点故障、链路失效和外界干扰影响网络稳定性和可靠性,提出一种基于混合蛙跳算法的无线传感器网络多路径传输策略.首先我们详细介绍了蛙跳算法及其原理,之后我们将其应用到无线传感器网络多路径传输策略之中,接着运用混合蛙跳算法对传感网络节点其进行更新、划分、重组以便选择出最优节点建立传输最优路径,提高网络的稳定性和可靠性.通过算法仿真与结果对比提出的算法与AODV、粒子群PSO算法相比,在网络能耗、传输时延、丢包率、连通率和可靠度等方面都具有较好的性能.其中网络能耗比AODV、PSO算法降低了62.5％和35.8％.     

WSNs中基于智能水滴的信宿路径规划算法

为了有效避免无线传感网络(WSNs)中的热点问题,常利用移动信宿收集数据。信宿依据预定路线遍历预定的驻留点(RPs)。而其他传感节点就将数据传输至离自己最近的驻留点。因此,构建最优的RPs非常重要。为此,提出基于智能水滴的信宿路径规划(IWD-SPP)算法。提出IWD-SPP算法的目的在于延长网络寿命,并最小化转发数据包的能量消耗。利用智能水滴算法构建最优的RPs,规划信宿的移动路径。仿真结果表明,提出的IWD-SPP算法在能量消耗和网络寿命方面的性能优于同类算法。