Optimal base-station locations in two-tiered wireless sensor networks

We consider generic two-tiered wireless sensor networks (WSNs) consisting of sensor clusters deployed around strategic locations, and base-stations (BSs) whose locations are relatively flexible. Within a sensor cluster, there are many small sensor nodes (SNs) that capture, encode, and transmit relevant information from a designated area, and there is at least one application node (AN) that receives raw data from these SNs, creates a comprehensive local-view, and forwards the composite bit-stream toward a BS. This paper focuses on the topology control process for ANs and BSs, which constitute the upper tier of two-tiered WSNs. Since heterogeneous ANs are battery-powered and energy-constrained, their node lifetime directly affects the network lifetime of WSNs. By proposing algorithmic approaches to locate BSs optimally, we can maximize the topological network lifetime of WSNs deterministically, even when the initial energy provisioning for ANs is no longer always proportional to their average bit-stream rate. The obtained optimal BS locations are under different lifetime definitions according to the mission criticality of WSNs. By studying intrinsic properties of WSNs, we establish the upper and lower bounds of maximal topological lifetime, which enable a quick assessment of energy provisioning feasibility and topology control necessity. Numerical results are given to demonstrate the efficacy and optimality of the proposed topology control approaches designed for maximizing network lifetime of WSNs.     

一种用于水声传感网的MAC层协议

针对分簇的水声传感网,提出了一种基于时分多址（TDMA）的MAC层协议——Cluster-TDMA。该协议主要由规划阶段和传输阶段组成。规划阶段,首先由网关节点规划能造成簇间干扰的子节点的传输,其次由各簇头节点分别规划本簇内其他子节点的传输;传输阶段,子节点根据规划表周期性地向簇头节点发送数据,这些数据最终汇聚到网关节点。该协议简单有效地解决了引起簇间干扰子结点的传输规划问题。C++仿真实验表明,该协议具有良好的吞吐率和能量效率性能。     

A Location-less Energy Efficient Algorithm for Load Balanced Clustering in Wireless Sensor Networks

One of the biggest challenges in Wireless Sensor Networks (WSNs) is to efficiently utilise the limited energy available in the network. In most cases, the energy units of sensors cannot be replaced or replenished. Therefore, the need for energy efficient and robust algorithms for load balancing in WSNs is ever present. This need is even more pronounced in the case of cluster-based WSNs, where the Cluster Head (CH) gathers data from its member nodes and transmits this data to the base station or sink. In this paper, we propose a location independent algorithm to cluster the sensor nodes under gateways, as CHs into well defined, load balanced clusters. The location-less aspect also avoids the energy loss in running GPS modules. Simulations of the proposed algorithm are performed and compared with a few existing algorithms. The results show that the proposed algorithm shows better performance under different evaluation metrics such as average energy consumed by sensor nodes vs number of rounds, number of active sensors vs number of rounds, first gateway die and half of the gateways die.

     

An approach for provisioning virtual sensors in sensor clouds

In sensor clouds environments, the provisioning process is a crucial task since it is responsible for selecting physical sensors that will be used to create virtual sensors. However, most works consider the allocation of all sensors within the region of interest, causing serious problems such as the wasting of energy consumption. The objective of this paper is to present ACxSIM, an automatic approach to the provisioning of virtual sensors. ACxSIM includes two algorithms: adaptive clustering algorithm based on similarity (ACASIM) and ant colony optimization for sensor selection based on similarity (ACOSIM). ACASIM first clusters the sensor nodes based on the similarity of its measurements (exploiting the temporal and spatial correlations between them), which may create clusters with nodes not physically close to each other. Therefore, in ACASIM, a cluster represents different geographical areas whose nodes have correlated measurements (according to a defined error threshold). Later, ACOSIM, based on ant colony optimization algorithm, creates virtual sensors by selecting only a subset of nodes from each cluster. In this way, the overall energy consumption of sensor nodes is reduced, prolonging the lifetime of the sensor cloud. Results from experiments in Intel Lab dataset show that the ACxSIM reduces energy consumption by 73.97%, providing a solution to be considered in sensor cloud scenarios.     

A mobile sink path planning for wireless sensor networks based on priority‐ordered dependent nonparametric trees

The professional design of the routing protocols with mobile sink(s) in wireless sensor networks (WSNs) is important for many purposes such as maximizing energy efficiency, increasing network life, and evenly distributing load balance across the network. Moreover, mobile sinks ought to first collect data from nodes which have very important and dense data so that packet collision and loss can be prevented at an advanced level. For these purposes, the present paper proposes a new mobile path planning protocol by introducing priority‐ordered dependent nonparametric trees (PoDNTs) for WSNs. Unlike traditional clustered or swarm intelligence topology‐based routing methods, a topology which has hierarchical and dependent infinite tree structure provides a robust link connection between nodes, making it easier to reselect ancestor nodes (ANs). The proposed priority‐ordered infinite trees are sampled in the specific time frames by introducing new equations and hierarchically associated with their child nodes starting from the root node. Hence, the nodes with the highest priority and energy that belong to the constructed tree family are selected as ANs with an opportunistic approach. A mobile sink simply visits these ANs to acquire data from all nodes in the network and return to where it started. As a result, the route traveled is assigned as the mobile path for the current round. We have performed comprehensive performance analysis to illustrate the effectiveness of the present study using NS‐2 simulation environment. The present routing protocol has achieved better results than the other algorithms over various performance metrics.     

Energy-efficient compressed data aggregation in underwater acoustic sensor networks

In this paper, we propose an energy-efficient compressed data aggregation framework for three-dimensional underwater acoustic sensor networks (UASNs). The proposed framework consists of two layers, where the goal is to minimize the total energy consumption of transmitting the data sensed by nodes. The lower layer is the compressed sampling layer, where nodes are divided into clusters. Nodes are randomly selected to conduct sampling, and then send the data to the cluster heads through random access channels. The upper layer is the data aggregation layer, where full sampling is adopted. We also develop methods to determine the number of clusters and the probability that a node participates in data sampling. Simulation results show that the proposed framework can effectively reduce the amount of sampling nodes, so as to reduce the total energy consumption of the UASNs.     

A collaborative node management scheme for energy-efficient monitoring in wireless multimedia sensor networks

Clustering in sensor networks provides energy conservation, network scalability, topology stability, reducing overhead and also allows data aggregation and cooperation in data sensing and processing. Wireless Multimedia Sensor Networks are characterized for directional sensing, the Field of View (FoV), in contrast to scalar sensors in which the sensing area usually is more uniform. In this paper, we first group multimedia sensor nodes in clusters with a novel cluster formation approach that associates nodes based on their common sensing area. The proposed cluster formation algorithm, called Multi-Cluster Membership (MCM), establishes clusters with nodes that their FoVs overlap at least in a minimum threshold area. The name of Multi-Cluster Membership comes from the fact that a node may belong to multiple clusters, if its FoV intersects more than one cluster-head and satisfies the threshold area. Comparing with Single-Cluster Membership (SCM) schemes, in which each node belongs to exactly one cluster, because of the capability of coordination between intersected clusters, MCM is more efficient in terms of energy conservation in sensing and processing subsystems at the cost of adding complexity in the node/cluster coordination. The main imposed difficulty by MCM, is the coordination of nodes and clusters for collaborative monitoring; SCMs usually assign tasks in a round-robin manner. Then, as second contribution, we define a node selection and scheduling algorithm for monitoring the environment that introduces intra and inter-cluster coordination and collaboration, showing how the network lifetime is prolonged with high lifetime prolongation factors particularly in dense deployments.     

无线传感器网络簇间节能路由算法

针对基于分簇网络的无线传感器网络簇间路由协议,让簇首和Sink节点直接通信或通过簇首节点转发数据造成能耗不均,节点过早死亡的缺陷。文中提出一种基于网关节点模型的无线传感器网络簇间路由算法,通过簇头与网关节点、网关节点自身建立虚电路,制定存储转发路由,将数据转发给Sink节点。并引入延时等待机制,增强了簇间信息的融合度,此算法适用于大规模无线传感器网络,有良好的可扩展性。仿真表明在能量节省等性能上与传统簇间路由算法相较有较大提高。     

一种大规模无线传感器网络的协议框架、网络结构和能耗分析

本文定义了一种适用于大范围数据采集的传感器网络构架DMCH(Directed Multi-Hop Clustering Hierarchy)及相关的媒体接入层和网络层协议,并建立数学模型对该网络结构和能耗状况进行了分析.DMCH通过预先设置在网络探测区域内的功能较强的小基站,将网络划分为分布相对均匀的群,在每个群内又将节点分级,形成分群多级的结构.同时,采用小基站轮流作群首的策略,保证了网络能耗的均衡性.DMCH具有可扩展性强、能耗均匀、协议简单、成本低、连通性好等特点.仿真结果为网络结构和能耗分析提供了依据并验证了各项设计指标,通过仿真与典型的大规模传感器网络协议MINA(Multi-Hop infrastructure Network Architecture)对比显示了DMCH在能耗及可扩展性等方面的优越性.     

一种无线传感器网络异构分簇模型的簇头调度方案

将无线传感器网络划分成簇会有效利用系统资源,近来提出的基于异构分簇模型的无线传感器网络,是指网络中存在多种不同能力的节点,能力强的节点自动成为簇头,这种网络避免了复杂的簇头选举过程并有效降低了普通节点的硬件复杂性和成本。但是,固定簇头的方法会削弱系统的负载均衡以及健壮性。为了解决这个问题,提出了一种基于自适应退避策略的簇头调度方案,该方案通过适当增加冗余度实现传感节点的k覆盖,增强了网络的健壮性。同时,依赖于地理信息和剩余电池能量信息,簇头节点通过自主周期性睡眠来保证系统负载的均衡分配,延长网络生存期。     

Energy-Aware Data Aggregation for Grid-Based Wireless Sensor Networks with a Mobile Sink

Wireless sensor networks (WSNs) are made up of many small and highly sensitive nodes that have the ability to react quickly. In WSNs, sink mobility brings new challenges to large-scale sensor networks. Almost all of the energy-aware routing protocols that have been proposed for WSNs aim at optimizing network performance while relaying data to a stationary gateway (sink). However, through such contemporary protocols, mobility of the sink can make established routes unstable and non-optimal. The use of mobile sinks introduces a trade-off between the need for frequent rerouting to ensure optimal network operation and the desire to minimize the overhead of topology management. In this paper, in order to reduce energy consumption and minimize the overhead of rerouting frequency, we propose an energy-aware data aggregation scheme (EADA) for grid-based wireless sensor networks with a mobile sink. In the proposed scheme, each sensor node with location information and limited energy is considered. Our approach utilizes location information and selects a special gateway in each area of a grid responsible for forwarding messages. We restrict the flooding region to decrease the overhead for route decision by utilizing local information. We conducted simulations to show that the proposed routing scheme outperforms the coordination-based data dissemination scheme (CODE) (Xuan, H. L., & Lee, S. Proceedings of the Sensor Networks and Information Processing Conference, pp. 13–18, 2004).     

Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem of unbalanced energy consumption exists in a particular cluster node in the network. Some more powerful nodes act as cluster head to control sensor network operation when the network is organized into heterogeneous clusters. It is important to assume that energy consumption of these cluster head nodes is balanced. Often the network is organized into clusters of equal size where cluster head nodes bear unequal loads. Instead in this paper, we proposed a new protocol low-energy adaptive unequal clustering protocol using Fuzzy c-means in wireless sensor networks (LAUCF), an unequal clustering size model for the organization of network based on Fuzzy c-means (FCM) clustering algorithm, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime. A heuristic comparison between our proposed protocol LAUCF and other different energy-aware protocol including low energy adaptive clustering hierarchy (LEACH) has been carried out. Simulation result shows that our proposed heterogeneous clustering approach using FCM protocol is more effective in prolonging the network lifetime compared with LEACH and other protocol for long run.     

一种新的无线传感器网络传输机制——RNTA算法的研究与仿真

针对无线传感器网络体积小与能量受限的特点,该文提出了一种新的传输机制RNTA算法,即将无线传感器网络中的部分冗余节点组成中继树,并利用该树作为网络内信息传输的代理,完成了信息从簇头到基站的传输,达到了节省正常节点和簇头能量的目的。仿真结果表明:该机制可以有效提高网络的生命周期。     

A Distributed Multi-competitive Clustering Approach for Wireless Sensor Networks

Wireless sensor networks (WSNs) need simple and effective approaches to reduce energy consumption because of limited energy. Clustering nodes is an effective approach to make WSNs energy-efficient. In this paper we propose a distributed multi-competitive clustering approach (DMCC) for WSNs. First, the nodes with high residual energy are selected to act as cluster head candidates (CHCs). Second, cluster heads (CHs) are selected from the CHCs based on a hybrid of competition. If the distances to the selected CHs are suitable, a CHC with more neighbor nodes and smaller average distance to its neighbor nodes is more likely to become a CH. If the number of CHs selected from the CHCs is insufficient, more CHs are selected from non-CHCs continually according to residual energy until the CHs number is suitable. DMCC makes the CHs number stable and distribute the CHs evenly. Simulation experiments were performed on to compare DMCC with some related clustering approaches. The experimental results suggest that DMCC balances the load among different clusters and reduces the energy consumption, which improves the network lifetime.     

基于移动Agent和WSN的突发事件场景数据收集算法研究

该文针对无线传感器网络应用于突发事件监测场景的能量消耗和网络延迟问题,提出了基于移动Agent的无线传感器网络簇式数据收集算法.动态成簇过程基于事件严重程度,并由其决定簇的生命周期和覆盖范围.Sink和簇头之间形成以Sink节点为簇头的虚拟簇.移动Agent迁移路径规划过程中下一跳节点的选取基于节点剩余能量、路径损耗及受刺激强度.移动Agent通过节点遍历的方式完成对所有簇内成员节点信息的收集.仿真结果表明,相对于C/S数据收集模型,基于移动Agent的模型具有更好的节能效果,并能一定程度地减少网络延迟,尤其适用于大规模无线传感器网络应用.     

Smartphone with Augmented Gateway Functionality as Opportunistic WSN Gateway Device

Sensors and actuators are being increasingly deployed for monitoring and controlling different phenomena and processes in a stand-alone manner or attached to sensor nodes with communication capabilities as part of larger wireless sensor networks (WSN). In addition to the protocols for communication within the WSN, sensor nodes may also provide the gateway functionality towards other networks and/or support communication with other external devices. These devices either represent additional gateways for exposing data and metadata to external networks, or serve as connection points to WSN for instance for the on-site calibration and maintenance. Smartphones as advanced mobile terminals appear particularly suitable for such role. This paper investigates the role a smartphone augmented with WSN gateway functionality can play in WSN with respect to regular dedicated sensor and gateway nodes. As a practical example we show the implementation of a gateway augmented smartphone using a Samsung i8910 phone and a VESNA sensor node connected via Bluetooth. The role of a gateway augmented smartphone is to interface between WSN, which is using a proprietary networking protocol, and the mobile network. The data obtained from WSN can be enriched using smartphone’s embedded sensors before being sent to the remote server. We demonstrate this on an example of geo-tagging the collected data from WSN with the smartphone’s Global Positioning System-based location data.     

联合最小路径和能量调配的路由算法的实现

基于最小耗能路径和路由能量信息的结合,提出了一个新型算法,在节点生命周期上做出改善,同时延长整个无线传感器网络的生存周期.对节点的能量信息划分了等级,相应的等级都匹配对应相应的信息传递概率,并且还对网络进行了分块分层划分.在节点生命周期上有了很大的改善,并且延长了整个无线传感器网络的生存周期,网络节点之间以及网关和节点间的依赖关系更加明显,最佳路径以及结合路径的能量调配得以实现,提高了整个网络效率.所以算法达到了提高网络性能的要求,并且很合理.     

Power‐aware range‐free wireless sensor network localization using neighbor distance distribution

In large‐scale wireless sensor networks, cost‐effective and energy‐efficient localization of sensor nodes is an important research topic. In spite of their coarse accuracy, range‐free (connectivity‐based) localization methods are considered as cost‐effective alternatives to the range‐based localization schemes with specialized hardware requirements.In this paper, we derive closed‐form expressions for the average minimum transmit powers required for the localization of sensor nodes, under deterministic path loss, log‐normal shadowing, and Rayleigh fading channel models. The impacts of propagation environment and spatial density of anchor nodes on the minimum transmit power for node localization are evaluated analytically as well as through simulations. Knowledge of the minimum transmit power requirements for localizability of a sensor node enables improving energy efficiency and prolonging lifetime of the network. We also propose a novel distance metric for range‐free localization in large‐scale sensor networks. The target and anchor nodes are assumed to be positioned according to two statistically independent two‐dimensional homogeneous Poisson point processes. Analytical expression for the average distance from a target node to its kth nearest neighbor anchor node is derived and is used for estimating the target‐to‐anchor node distances for localization. The Cramér–Rao lower bound on the localization accuracy for the new distance estimator is derived. Simulation results show the accuracy of the proposed distance estimate compared with some existing ones for range‐free localization. The results of our investigation are significant for low‐cost, energy‐efficient localization of wireless sensor nodes. Copyright © 2011 John Wiley & Sons, Ltd.     

DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks

Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population.     

Energy efficient clustering algorithms for wireless sensor networks: novel chemical reaction optimization approach

Clustering has been accepted as one of the most efficient techniques for conserving energy of wireless sensor networks (WSNs). However, in a two-tiered cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving data from their member sensor nodes, aggregating them and transmitting that data to the base station (BS). Therefore, proper selection of CHs and optimal formation of clusters play a crucial role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient CH selection and energy balanced cluster formation algorithms, which are based on novel chemical reaction optimization technique (nCRO), we jointly called these algorithms as novel CRO based energy efficient clustering algorithms (nCRO-ECA). These algorithms are developed with efficient schemes of molecular structure encoding and potential energy functions. For the energy efficiency, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes in the CH selection phase. In the cluster formation phase, we consider various distance and energy parameters. The algorithm is tested extensively on various scenarios of WSNs by varying number of sensor nodes and CHs. The results are compared with original CRO based algorithm, namely CRO-ECA and some existing algorithms to demonstrate the superiority of the proposed algorithm in terms of energy consumption, network lifetime, packets received by the BS and convergence rate.