基于能量有效性的协作节点配置问题研究

无线通信的能耗主要由功放能耗和电路能耗两部分组成。在大距离传输中,通信能耗由功放能耗主导,电路能耗往往被忽略不计。而在以短距离传输为主的传感器网络中,电路能耗成为不可忽略的一部分,甚至有可能超过功放能耗成为通信能耗的主导。本文就如何通过节点间协作降低网络的通信能耗展开研究,拟解决协作通信中的协作节点配置问题。本文将信源-协作节点间距离纳入协作通信系统模型,提出一种针对调制参数、协作中继数、信源-协作簇距离对协作通信能耗进行联合优化的策略,并在无线传感器网络环境下对该模型的能耗进行了仿真。仿真结果表明,在传输距离一定的情况下,通过协作节点的数量、调制参数和信源-协作簇距离的联合优化配置,可以更有效地提高协作传输的节能效果。      

Target localization based on energy considerations in distributed sensor networks

Wireless distributed sensor networks are important for a number of strategic applications such as coordinated target detection, surveillance, and localization. Energy is a critical resource in wireless sensor networks and system lifetime needs to be prolonged through the use of energy-conscious sensing strategies during system operation. We propose an energy-aware target detection and localization strategy for cluster-based wireless sensor networks. The proposed method is based on an a posteriori algorithm with a two-step communication protocol between the cluster head and the sensors within the cluster. Based on a limited amount of data received from the sensor nodes, the cluster head executes a localization procedure to determine the subset of sensors that must be queried for detailed target information. This approach reduces both energy consumption and communication bandwidth requirements, and prolongs the lifetime of the wireless sensor network. Simulation results show that a large amount of energy is saved during target localization using this strategy.     

一种改进的基于时间竞争成簇的路由算法

为平衡无线传感器网络中的簇头负载并进一步降低多跳传输能耗,文中提出了一种改进的基于时间竞争成簇的路由算法。该算法通过限制近基站节点成簇入簇,以防止近基站节点成簇入簇的节能收益无法补偿成簇入簇能耗;利用基站广播公共信息和基于时间机制成簇,以减少节点基本信息交换能耗;通过候选簇头中继来平衡簇头负载。候选簇头的评价函数综合考虑了剩余能量和最优跳数的理想路径,以期在保持中继负载平衡的基础上尽量降低多跳能耗。仿真结果显示,该算法较LEACH和DEBUC算法延长了以30%节点死亡为网络失效的网络生存周期,表明该算法在降低节点能耗和平衡负载方面是有效的。     

Optimal load balanced clustering in homogeneous wireless sensor networks

Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster‐based wireless sensor networks. We formulate the network design problem as mixed‐integer linear programming. Our contribution is 3‐fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy‐aware routing model for optimal inter‐cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre‐deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models.     

Cost Modelling and Studies with Different Deployment Strategies for Wireless Multimedia Sensor Network Over Flat and Elevated Terrains

Wireless multimedia sensor networks (WMSNs) is widely used for surveillance application. These multimedia (audio and video) nodes are distributed according to different deployment strategies in a multi-tier heterogeneous architecture environment. In this paper we have modelled the deployment cost of WMSN considering the sensor type (audio or video), sensor configuration such as remaining energy of battery, deployment point, and terrain characteristics for surveillance applications. Using our proposed cost models we have studied the effects of different deployment strategies of WMSN over flat and elevated terrains. Our cost models helps in minimizing the cost of deployment while maintaining Quality-of-Service i.e., the coverage and connectivity of the audio and video sensors separately. We have formulated an integer linear program and proposed a heuristic solution to minimize the placement costs subject to network coverage requirements using our first cost model. Our second cost model is used to propose a scheme that will ensure connectivity of the network. We have done simulations with three network deployment strategies, namely deterministic, random and hybrid and show that the hybrid deployment of sensor nodes yields a balance of performance and cost as compared to the other two. Our study provides guidelines for the network architect to select a particular deployment strategy under performance and cost requirements.     

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.     

Node correlation clustering algorithm for wireless multimedia sensor networks based on overlapped FoVs

In this paper, a clustering algorithm is proposed based on the high correlation among the overlapped field of views for the wireless multimedia sensor networks. Firstly, by calculating the area of the overlapped field of views （FoVs） based on the gird method, node correlations have been obtained. Then, the algorithm utilizes the node correlations to partition the network region in which there are high correlation multimedia sensor nodes. Meanwhile, in order to minimize the energy consumption for transmitting images, the strategy of the cluster heads election is proposed based on the cost estimation, which consists of signal strength and residual energy as well as the node correlation. Simulation results show that the proposed algorithm can balance the energy consumption and extend the network lifetime effectively.     

一种基于网格划分的水下传感器网络多维优化部署策略

针对水下无线传感器网络节点的部署问题,提出一种基于网格划分的多维优化部署策略。首先,将所需探测水下环境划分成相同规格的网格;然后,综合考虑网络节点数量、网络覆盖率、网络冗余度、网络生存率等指标,构建多目标优化数学模型;最后,采用遗传算法对多维优化部署策略加以实现并进行仿真分析。结果显示：所提策略能够有效地减少部署节点数量,提高网络覆盖率和生存效率,降低网络能耗。     

A Tabu Search Algorithm for Cluster Building in Wireless Sensor Networks

The main challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is based on network energy maps and Quality-of-Service (QoS) requirements. The clustering problem is modeled as a hypergraph partitioning and its resolution is based on a tabu search heuristic. Our approach defines moves using largest size cliques in a feasibility cluster graph. Compared to other methods (CPLEX-based method, distributed method, simulated annealing-based method), the results show that our tabu search-based approach returns high-quality solutions in terms of cluster cost and execution time. As a result, this approach is suitable for handling network extensibility in a satisfactory manner.     

Relay characteristic impact on energy consumption in heterogeneous sensor network

Indoor heterogeneous wireless sensor networks are considered in this paper. We analyze the power consumption for multihop communications with non-regenerative relays. Since sensor nodes are battery operated, energy consumption is a crucial issue. We determine the optimal relay gains and transmitted power that minimize the dissipated power for a given quality of service in a narrow band fading channel. Our work includes two main contributions: firstly, we study the energy consumption taking into account hardware aspects, especially the relays’ efficiency. In an AWGN channel, carefully analyzing the energy gain as a function of the position, we show that relay characteristics have an important impact on the multihop link consumption budget. We then use a Rice channel model based on simulations and further study the hardware impact on energy saving.     

Distributed Energy Optimization for Target Tracking in Wireless Sensor Networks

Energy constraint is an important issue in wireless sensor networks. This paper proposes a distributed energy optimization method for target tracking applications. Sensor nodes are clustered by maximum entropy clustering. Then, the sensing field is divided for parallel sensor deployment optimization. For each cluster, the coverage and energy metrics are calculated by grid exclusion algorithm and Dijkstra's algorithm, respectively. Cluster heads perform parallel particle swarm optimization to maximize the coverage metric and minimize the energy metric. Particle filter is improved by combining the radial basis function network, which constructs the process model. Thus, the target position is predicted by the improved particle filter. Dynamic awakening and optimal sensing scheme are then discussed in dynamic energy management mechanism. A group of sensor nodes which are located in the vicinity of the target will be awakened up and have the opportunity to report their data. The selection of sensor node is optimized considering sensing accuracy and energy consumption. Experimental results verify that energy efficiency of wireless sensor network is enhanced by parallel particle swarm optimization, dynamic awakening approach, and sensor node selection.     

Performance Analysis of Adaptive Routing Structure for Wireless Sensor Network Based on Load Balancing

Wireless sensor network consists of sensor nodes with battery operated device. The key challenges in the wireless sensor network are energy consumption and routing optimization. This work presents the cluster based load balancing (CBLB) routing protocol. The proposed routing protocol is used to minimize the energy consumption and increase the routing performance. It avoids the routing robustness, delay and increases the delivery rate and network performance. In existing techniques, different routing protocols such as LEACH, HEED and MESTER were used to increase the network performance and to decrease the energy consumption. But these existing techniques did not satisfy the performance requirements of wireless sensor networks. Hence, there is a requirement to develop a technique that meets the QoS requirements and needs of wireless sensor network. The proposed CBLB routing protocol creates a cluster head in the decentralized network and the cluster head will be used to distribute the workload evenly to the cluster members for reducing the energy consumption in wireless sensor network. Experimental results analyze the performance of the proposed protocol with the different existing protocols. The proposed protocol achieves high throughput, delivery rate and reduces the energy consumption, delay and routing overhead.     

基于信号幅度衰减测距的水下定位方法

无线传感器网络中节点规模大、能量有限、可靠性差、随机部署,无线模块的通信距离有限,虽然运用全球定位系统是个很好的选择,但是其体积大、成本高、能耗多而且需要基础设施,不适用于低成本、自组织的无线传感器网络。通过研究发现,基于信号幅度衰减测距的水下定位方法不仅能够满足无线传感器网络节点定位的要求,而且其成本较低,易理解及操作,精度高。     

A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization

Energy consumption of sensor nodes is one of the crucial issues in prolonging the lifetime of wireless sensor networks. One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. We also take into account the mobility factor when defining the cluster membership, so that the sensor nodes can join the cluster that has the similar mobility pattern. The performance of the proposed protocol is compared with well-known clustering protocols developed for wireless sensor networks such as LEACH (low-energy adaptive clustering hierarchy) and protocols designed for sensor networks with mobile nodes called CM-IR (clustering mobility-invalid round). In addition, we also modify the improved version of LEACH called MLEACH-C, so that it is applicable to the mobile sensor nodes environment. Simulation results demonstrate that the proposed protocol using PSO algorithm can improve the energy consumption of the network, achieve better network lifetime, and increase the data delivered at the base station.     

Traffic-Aware Density-Based Sleep Scheduling and Energy Modeling for Two Dimensional Gaussian Distributed Wireless Sensor Network

Sleep scheduling of sensors in network domain is considered to be the most fundamental way of achieving higher life expectancy of wireless sensor networks. In this paper we have proposed density-based sleep scheduling strategy with traffic awareness in Gaussian distributed sensor network for minimizing energy consumption. In uniform distributed sensor network, it has been found that nodes in the nearest belt around the sink consume more energy. The reason behind is that the nodes near the sink involve more packet relaying load than the distant nodes. Consequently, the energy of these sensors get exhausted rapidly, thereby creating connectivity breaks known as energy hole. For this purpose, Gaussian distribution is used by densely deploying nodes around the sink which well-balances the relaying load. In addition, we have developed the analytical model for computing the energy consumption and coverage analysis in the sensor network. The performance of our sleep scheduling method is evaluated with respect to the Randomized Scheduling and Linear Distance-based Scheduling protocols. The simulation results of our proposed work show commendable improvement in network lifetime.     

General Network Lifetime and Cost Models for Evaluating Sensor Network Deployment Strategies

In multihop wireless sensor networks that are often characterized by many-to-one (convergecast) traffic patterns, problems related to energy imbalance among sensors often appear. Sensors closer to a data sink are usually required to forward a large amount of traffic for sensors farther from the data sink. Therefore, these sensors tend to die early, leaving areas of the network completely unmonitored and reducing the functional network lifetime. In our study, we explore possible sensor network deployment strategies that maximize sensor network lifetime by mitigating the problem of the hot spot around the data sink. Strategies such as variable-range transmission power control with optimal traffic distribution, mobile-data-sink deployment, multiple-data-sink deployment, nonuniform initial energy assignment, and intelligent sensor/relay deployment are investigated. We suggest a general model to analyze and evaluate these strategies. In this model, we not only discover how to maximize the network lifetime given certain network constraints but also consider the factor of extra costs involved in more complex deployment strategies. This paper presents a comprehensive analysis on the maximum achievable sensor network lifetime for different deployment strategies, and it also provides practical cost-efficient sensor network deployment guidelines.     

Energy Optimization in Multihop Wireless Embedded and Sensor Networks

This paper provides an analytical model for the study of energy consumption in multihop wireless embedded and sensor networks where nodes are extremely power constrained. Low-power optimization techniques developed for conventional ad hoc networks are not sufficient as they do not properly address particular features of embedded and sensor networks. It is not enough to reduce overall energy consumption, it is also important to maximize the lifetime of the entire network, that is, maintain full network connectivity for as long as possible. This paper considers different multihop scenarios to compute the energy per bit, efficiency and energy consumed by individual nodes and the network as a whole. The analysis uses a detailed model for the energy consumed by the radio at each node. Multihop topologies with equidistant and optimal node spacing are studied. Numerical computations illustrate the effects of packet routing, and explore the effects of coding and medium access control. These results show that always using a simple multihop message relay strategy is not always the best procedure.     

A Survey of Energy-Efficient Scheduling Mechanisms in Sensor Networks

Sensor networks have a wide range of potential, practical and useful applications. However, there are issues that need to be addressed for efficient operation of sensor network systems in real applications. Energy saving is one critical issue for sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime. To extend the lifetime of a sensor network, one common approach is to dynamically schedule sensors' work/sleep cycles (or duty cycles). Moreover, in cluster-based networks, cluster heads are usually selected in a way that minimizes the total energy consumption and they may rotate among the sensors to balance energy consumption. In general, these energy-efficient scheduling mechanisms (also called topology configuration mechanisms) need to satisfy certain application requirements while saving energy. In this paper, we provide a survey on energy-efficient scheduling mechanisms in sensor networks that have different design requirements than those in traditional wireless networks. We classify these mechanisms based on their design assumptions and design objectives. Different mechanisms may make different assumptions about their sensors including detection model, sensing area, transmission range, failure model, time synchronization, and the ability to obtain location and distance information. They may also have different assumptions about network structure and sensor deployment strategy. Furthermore, while all the mechanisms have a common design objective to maximize network lifetime, they may also have different objectives determined by their target applications. A preliminary was presented in BROADNETS 2006 [29]     

无线传感器网络拓扑控制策略研究

节能设计是无线传感器网络的首要设计目标,拓扑控制是实现该目标的重要技术之一,其主要目标是在保证网络连通和覆盖的前提下剔除不必要的通信链路,降低节点能耗和减少通信干扰,为MAC协议和路由协议的顺利执行提供基础。文中对传感器网络拓扑控制策略进行了的分析。最后针对目前传感器节点成本仍然很高这一特点,通过仿真得出了在节点随机配置的情况下,保证网络连通和覆盖所需的至少节点数目。并通过仿真分析证明了方案的可行性。     

Deployment strategy for static chargers in WRSN

The traditional deployment strategy of static chargers in wireless rechargeable sensor networks (WRSN) covers all the area.The basic idea is to cover all the positions of nodes.A mathematical model of distance between a charger and the farthest node was established,the relationship between the number of nodes and the mathematical expectation of minimum radius of charging was analyzed,and deployment strategy for static chargers was proposed.The method based on the locations of all nodes that need to be charged in the area,used the smallest enclosing circle (SEC) algorithm and finds the optimal location of the charger through Euclidean delivery boy algorithm.It will decrease charging radius,reduce the minimum required transmitted power,thereby saving the average charging energy consumption.The experimental results demonstrated that the less the number locations that the nodes existed,the more energy will be saved.