Collaborative beamforming for distributed wireless ad hoc sensor networks

The performance of collaborative beamforming is analyzed using the theory of random arrays. The statistical average and distribution of the beampattern of randomly generated phased arrays is derived in the framework of wireless ad hoc sensor networks. Each sensor node is assumed to have a single isotropic antenna and nodes in the cluster collaboratively transmit the signal such that the signal in the target direction is coherently added in the far-field region. It is shown that with N sensor nodes uniformly distributed over a disk, the directivity can approach N, provided that the nodes are located sparsely enough. The distribution of the maximum sidelobe peak is also studied. With the application to ad hoc networks in mind, two scenarios (closed-loop and open-loop) are considered. Associated with these scenarios, the effects of phase jitter and location estimation errors on the average beampattern are also analyzed.     

Comprehensive event based estimation of sensor node distribution strategies using classical flooding routing protocol in wireless sensor networks

We derive a new investigation for the wireless sensor networks (WSNs) when the underlying sensor node distribution strategies have strong influence on event specific communication performance. In this paper, we inclusively evaluated eight sensor network distributions namely: normal, gamma, exponential, beta, generalized inverse Gaussian, poison, Cauchy and Weibull. We designed and illustrated our proposed model with these node distributions for data dissemination. Moreover, performance evaluation matrices like sense count, receive count and receive redundant count are also evaluated. Additionally, we emphasized over the routing protocol behavior for different distribution strategies in the deployed WSN framework. Finally, simulation analysis has been carried out to prove the validity of our proposal. However, routing protocol for WSNs seems intractable to the sensor node distribution strategies when varied from one to another in the scenario.     

Least-Square Collaborative Beamforming Linear Array for Steering Capability in Green Wireless Sensor Networks

This paper presents a collaborative beamforming (CB) technique to organize the sensor node's location in a linear array for green wireless sensor network (WSN) applications. In this method, only selected clusters and active CB nodes are needed each time to perform CB in WSNs. The proposed least-square linear array (LSLA) manages to select nodes to perform as a linear antenna array (LAA), which is similar to and as outstanding as the conventional uniform linear array (ULA). The LSLA technique is also able to solve positioning error problems that exist in the random nodes deployment. The beampattern fluctuations have been analyzed due to the random positions of sensor nodes. Performances in terms of normalized power gains are given. It is demonstrated by a simulation that the proposed technique gives similar performances to the conventional ULA and at the same time exhibits lower complexity.     

DR-NAP: Data reduction strategy using neural adaptation phenomenon in wireless sensor networks

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.     

Fish bone structure based data aggregation and routing in wireless sensor network: multi-agent based approach

Wireless sensor networks (WSNs) are constrained by limited node (device) energy, low network bandwidth, high communication overhead and latency. Data aggregation alleviates the constraints of WSN. In this paper, we propose a multi-agent based homogeneous temporal data aggregation and routing scheme based on fish bone structure of WSN nodes by employing a set of static and mobile agents. The primary components of fishbone structure are backbone and ribs connected to both sides of a backbone. A backbone connects a sink node and one of the sensor nodes on the boundary of WSN through intermediate sensor nodes. Our aggregation scheme operates in the following steps. (1) Backbone creation and identifying master centers (or nodes) on it by using a mobile agent based on parameters such as Euclidean distance, residual energy, backbone angle and connectivity. (2) Selection of local centers (or nodes) along the rib of a backbone connecting a master center by using a mobile agent. (3) Local aggregation process at local centers by considering nodes along and besides the rib, and delivering to a connected master center. (4) Master aggregation process along the backbone from boundary sensor node to the sink node by using a mobile agent generated by a boundary sensor node. The mobile agent aggregates data at visited master centers and delivers to the sink node. (5) Maintenance of fish bone structure of WSN nodes. The performance of the scheme is simulated in various WSN scenarios to evaluate the effectiveness of the approach by analyzing the performance parameters such as master center selection time, local center selection time, aggregation time, aggregation ratio, number of local and master centers involved in the aggregation process, number of isolated nodes, network lifetime and aggregation energy. We observed that our scheme outperforms zonal based aggregation scheme.     

Energy-efficient optical acquisition schemes in wireless sensor networks

Energy-efficiency is an essential feature of wireless sensor networks (WSNs) where the longevity of autonomous sensor nodes is limited by their battery life and/or energy-harvesting capability. Base-station-initiated optical wireless communication with nodes equipped with a passive optical transmitter in the form of a corner cube retroreflector (CCR) provides sensor acquisition with no energy expenditure on the part of the sensor node itself and is therefore an attractive option for WSN. However, the return signal from an illuminated sensor node is a stochastic variable dependant on fabrication parameters, ambient conditions and receiver noise so that the sensor acquisition process is inherently error-prone. In this paper we propose an energy-aware, base station-initiated interrogation scheme based on exponentially increasing beam scan areas, that takes into consideration the error-prone trait of CCR-outfitted sensor nodes. We analyse the scheme performance subject to different values of signal variance and various cost functions. We extend the analysis to address the circumstance of a spatially-limited sensor-failure event, such as may be caused by deliberate tampering or by environmental factors. We show that agile beam-steering on the basis of accrued knowledge of contaminated sensor distributions promotes energy-conserving acquisition. The validity of a Poisson spatial distribution model for the sensor dispersion is discussed and the impact of this initial assumption on acquisition error is demonstrated.     

An efficient UE cluster head selection algorithm in wireless sensor networks and cellular networks

Wireless Sensor Networks (WSNs) have been applied in many different areas. Energy efficient algorithms and protocols have become one of the most challenging issues for WSN. Many researchers focused on developing energy efficient clustering algorithms for WSN, but less research has been concerned in the mobile User Equipment (UE) acting as a Cluster Head (CH) for data transmission between cellular networks and WSNs. In this paper, we propose a cellular-assisted UE CH selection algorithm for the WSN, which considers several parameters to choose the optimal UE gateway CH. We analyze the energy cost of data transmission from a sensor node to the next node or gateway and calculate the whole system energy cost for a WSN. Simulation results show that better system performance, in terms of system energy cost and WSNs life time, can be achieved by using interactive optimization with cellular networks.     

分布式无线Ad Hoc传感器网络中的合成式波束形成

分布式无线Ad Hoc传感器网络中的合作式波束形成的性能分析是建立在随机阵理论和移动通信波束形成的基础上的。在分布式Ad Hoc传感器网络中,每个传感器节点有一个全向天线,且在簇中的节点传输同一信号,使信号在远区场的目标方向上叠加。波束的方向的随机性是由无线Ad Hoc网络结构决定的。介绍了随机阵理论和移动通信波束形成,接着介绍了系统模型,分析了波束的方向特性,着重讨论了平均方向性增益,推导出平均方向性增益的近似公式。     

卫星物联网场景下基于节点选择的协作波束成形技术研究

针对卫星物联网(IoT)场景下信号长距离传输衰减大以及单个终端节点传输性能受限的问题，该文提出一种基于节点选择的协作波束成形算法，增强终端节点的传输能力。在实际终端位置信息存在误差的条件下，推导出了协作波束成形平均方向图函数，分析了不同系统参数对于协作波束成形平均方向图和瞬时方向图差异的影响。在此基础上，根据卫星物联网链路传输性能需求，提出一种区域分组优化的协作节点选择算法。仿真结果表明，相比于传统的分布式协作波束成形节点选择算法，该文提出的算法在实际的误差模型中旁瓣抑制和零陷生成方面具有更好的性能。     

MUQAMI+: a scalable and locally distributed key management scheme for clustered sensor networks

Wireless sensor networks (WSN) are susceptible to node capture and many network levels attacks. In order to provide protection against such threats, WSNs require lightweight and scalable key management schemes because the nodes are resource-constrained and high in number. Also, the effect of node compromise should be minimized and node capture should not hamper the normal working of a network. In this paper, we present an exclusion basis system-based key management scheme called MUQAMI+ for large-scale clustered sensor networks. We have distributed the responsibility of key management to multiple nodes within clusters, avoiding single points of failure and getting rid of costly inter-cluster communication. Our scheme is scalable and highly efficient in terms of re-keying and compromised node revocation.     

Practical and secure localization and key distribution for wireless sensor networks

In many applications of wireless sensor networks, sensor nodes are manually deployed in hostile environments where an attacker can disrupt the localization service and tamper with legitimate in-network communication. In this article, we introduce Secure Walking GPS, a practical and cost effective secure localization and key distribution solution for real, manual deployments of WSNs. Using the location information provided by the GPS and inertial guidance modules on a special master node, Secure Walking GPS achieves accurate node localization and location-based key distribution at the same time. We evaluate our localization solution in real deployments of MicaZ. Our experiments show that 100% of the deployed nodes localize (i.e., have a location position) and that the average localization errors are within 1–2 m, due mainly to the limitations of the existing commercial GPS devices. Our further analysis and simulation results indicate that the Secure Walking GPS scheme makes a deployed WSN resistant to the Dolev-Yao, the wormhole, and the GPS-denial attacks, the scheme is practical for large-scale deployments with resource-constrained sensor nodes and has good localization and key distribution performance.     

QoS evaluation of energy-efficient ML-MAC protocol for wireless sensor networks

Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. If the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit.     

Tree‐based channel assignment schemes for multi‐channel wireless sensor networks

Many sensor node platforms used for establishing wireless sensor networks (WSNs) can support multiple radio channels for wireless communication. Therefore, rather than using a single radio channel for whole network, multiple channels can be utilized in a sensor network simultaneously to decrease overall network interference, which may help increase the aggregate network throughput and decrease packet collisions and delays. This method, however, requires appropriate schemes to be used for assigning channels to nodes for multi‐channel communication in the network. Because data generated by sensor nodes are usually delivered to the sink node using routing trees, a tree‐based channel assignment scheme is a natural approach for assigning channels in a WSN. We present two fast tree‐based channel assignment schemes (called bottom up channel assignment and neighbor count‐based channel assignment) for multi‐channel WSNs. We also propose a new interference metric that is used by our algorithms in making decisions. We validated and evaluated our proposed schemes via extensive simulation experiments. Our simulation results show that our algorithms can decrease interference in a network, thereby increasing performance, and that our algorithms are good alternatives for static channel assignment in WSNs. Copyright © 2015 John Wiley & Sons, Ltd.     

Fair data collection in wireless sensor networks: analysis and protocol

In general, wireless sensor networks (WSNs) consist of many sensors which transmit data to a central node, called the sink, possibly over multiple hops. This many-to-one data routing paradigm leads to nonuniform traffic distribution for the different sensors (e.g., nodes closer to the sink transfer more traffic than those farther away). In this paper, we perform an analysis of the fairness issue by presenting a tree-based WSN and derive the throughput, delay, and energy distribution for each sensor under the fairness constraint. Based on the analysis, we design our fair data collection protocol in which each node decides its media access and packet forwarding strategies in a distributed manner. Finally, we demonstrate the effectiveness of our solution through simulations. The results for the proposed protocol show the accuracy of the analysis and show that the protocol ensures the fair delivery of packets and reduces end-to-end delay. Based on the analysis, we also quantitatively determine the energy required for each of the nodes and show that a nonuniform energy distribution can maximize the network lifetime for the WSN scenario under study.     

A new range-free localisation in wireless sensor networks using support vector machine

Location information of sensor nodes is of vital importance for most applications in wireless sensor networks (WSNs). This paper proposes a new range-free localisation algorithm using support vector machine (SVM) and polar coordinate system (PCS), LSVM-PCS. In LSVM-PCS, two sets of classes are first constructed based on sensor nodes’ polar coordinates. Using the boundaries of the defined classes, the operation region of WSN field is partitioned into a finite number of polar grids. Each sensor node can be localised into one of the polar grids by executing two localisation algorithms that are developed on the basis of SVM classification. The centre of the resident polar grid is then estimated as the location of the sensor node. In addition, a two-hop mass-spring optimisation (THMSO) is also proposed to further improve the localisation accuracy of LSVM-PCS. In THMSO, both neighbourhood information and non-neighbourhood information are used to refine the sensor node location. The results obtained verify that the proposed algorithm provides a significant improvement over existing localisation methods.     

Simple,secure, and lightweight mechanism for mutual authentication of nodes in tiny wireless sensor networks

Wireless sensor networks (WSNs) are widely used in large areas of applications; due to advancements in technology, very tiny sensors are readily available, and their usage reduces the cost. The mechanisms designed for wireless networks cannot be implied on networks with tiny nodes due to battery and computational constraints. Understanding the significance of security in WSNs and resource constraintness of tiny WSNs, we propose a node authentication mechanism for nodes in wireless sensor networks to avoid security attacks and establish secure communication between them. In the proposed mechanism, a base station (BS) generates a secret value and random value for each sensor node and stores at the node. The sensor node authenticates using secret value and random number. Random nonce ensures freshness, efficiency, and robustness. The proposed mechanism is lightweight cryptographic, hence requires very less computational, communication, and storage resources. Security analysis of the proposed mechanism could not detect any security attack on it, and the mechanism was found to incur less storage, communication, and computation overheads. Hence, the proposed mechanism is best suitable for wireless sensor networks with tiny nodes.     

Lifetime enhancement of wireless sensor networks by avoiding energy-holes with Gaussian distribution

Wireless sensor networks (WSNs) are receiving significant attention due to their potential applications in environmental monitoring and surveillance domains. In WSNs, preserving energy requires utmost attention, as they are highly resource constrained. One fundamental way of conserving energy is judicious deployment of nodes within the network for balancing energy flow throughout the network. Node deployment using Gaussian distribution is a standard practice and is widely acceptable when random deployment is used. Initially, an analysis is done to establish that Gaussian distribution based node deployment is not energy balanced. Standard deviation of Gaussian distribution is identified as the parameter responsible for energy balancing. A deployment strategy is proposed for energy balancing using customized Gaussian distribution by discretizing the standard deviation. Performance of the scheme is evaluated in terms of energy balance and network lifetime. Exhaustive simulation is performed to measure the extent of achieving our design goal of enhancing network lifetime while attaining energy balancing. The simulation results show that our scheme also provides satisfactory network performance in terms of end-to-end delay and throughput. Finally, all the results are compared with three competing schemes and the results confirm our scheme’s supremacy in terms of both design performance metrics as well as network performance metrics.     

Topology control of tactical wireless sensor networks using energy efficient zone routing

The US Department of Defense (DoD) routinely uses wireless sensor networks (WSNs) for military tactical communications. Sensor node die-out has a significant impact on the topology of a tactical WSN. This is problematic for military applications where situational data is critical to tactical decision making. To increase the amount of time all sensor nodes remain active within the network and to control the network topology tactically, energy efficient routing mechanisms must be employed. In this paper, we aim to provide realistic insights on the practical advantages and disadvantages of using established routing techniques for tactical WSNs. We investigate the following established routing algorithms: direct routing, minimum transmission energy (MTE), Low Energy Adaptive Cluster Head routing (LEACH), and zone clustering. Based on the node die out statistics observed with these algorithms and the topological impact the node die outs have on the network, we develop a novel, energy efficient zone clustering algorithm called EZone. Via extensive simulations using MATLAB, we analyze the effectiveness of these algorithms on network performance for single and multiple gateway scenarios and show that the EZone algorithm tactically controls the topology of the network, thereby maintaining significant service area coverage when compared to the other routing algorithms.     

Energy awareness workflow model for wireless sensor nodes

Before the development of a large‐scale wireless sensor network (WSN) infrastructure, it is necessary to create a model to evaluate the lifespan of the infrastructure, the system performance and the cost so that the best design solution can be obtained. Energy consumption is an important factor that influences the lifespan of WSNs. One of the ways to extend the lifespan of WSNs is to design wireless sensor nodes with low power consumption. This involves component selection and the optimisation of hardware architecture, monitoring software system and protocols to satisfy the requirements of the particular applications. This paper proposes a comprehensive model to describe the workflow of a wireless sensor node. Parameter setup and energy consumption calculation are demonstrated through the model simulation. It provides a mathematical approach to dynamically evaluate the energy consumption of a sensor node. This will benefit the development of wireless sensor nodes based on microprocessors with limited computational capability. Therefore, the model can be applied in dynamic power management systems for wireless sensor nodes or in wireless communication protocols with energy awareness, in particular, for WSNs with self‐organisation. More importantly, the generalisation of the model may be employed as a standard paradigm for the development of wireless sensor node with energy awareness. Copyright © 2012 John Wiley & Sons, Ltd.