Wide Area Wireless Sensor Network Research Articles

Multiobjective 3-D UAV Movement Planning in Wireless Sensor Networks Using Bioinspired Swarm Intelligence

The use of unmanned aerial vehicles (UAVs) is a promising solution to efficiently acquire data in large-scale wireless sensor networks (WSNs). In a wide-area WSN environment, UAV path planning is one of the challenging issues in solving the optimization problem to achieve complex and multiple objectives under various constraints related to UAV operation. In this paper, we propose a novel asynchronous UAV path planning mechanism for multi-objective UAV operation. In a three-dimensional sensor field, a grid-based sensor field and information gathering model is introduced. We define a UAV coverage area where line-of-sight communication is possible between a UAV and the sensors and propose a method to quickly find the grid-cells within the coverage area. We define a multi-purpose fitness function that maximizes the value of the acquired sensing information and at the same time minimizes the time and energy required for UAV operation. The value of the sensing information reflects the sensor density for each sensor type within UAV coverage, as well as changes in the sensing information values over time. In the proposed method, time and energy objective functions are learned by considering location-dependent communication link quality, sensor density, and the next UAV locations. The optimum UAV position and the movement schedule of each UAV are asynchronously derived using the proposed particle swarm optimization (PSO) algorithm with several UAV operational constraints. The experiment results demonstrate that the proposed method can maximize the utility of the objective function and achieve fast convergence in finding the optimal solution compared with other methods.

Dimensioning of Wide-Area Alternate Wetting and Drying (AWD) System for IoT-Based Automation.

Water, one of the most valuable resources, is underutilized in irrigated rice production. The yield of rice, a staple food across the world, is highly dependent on having proper irrigation systems. Alternate wetting and drying (AWD) is an effective irrigation method mainly used for irrigated rice production. However, unattended, manual, small-scale, and discrete implementations cannot achieve the maximum benefit of AWD. Automation of large-scale (over 1000 acres) implementation of AWD can be carried out using wide-area wireless sensor network (WSN). An automated AWD system requires three different WSNs: one for water level and environmental monitoring, one for monitoring of the irrigation system, and another for controlling the irrigation system. Integration of these three different WSNs requires proper dimensioning of the AWD edge elements (sensor and actuator nodes) to reduce the deployment cost and make it scalable. Besides field-level monitoring, the integration of external control parameters, such as real-time weather forecasts, plant physiological data, and input from farmers, can further enhance the performance of the automated AWD system. Internet of Things (IoT) can be used to interface the WSNs with external data sources. This research focuses on the dimensioning of the AWD system for the multilayer WSN integration and the required algorithms for the closed loop control of the irrigation system using IoT. Implementation of the AWD for 25,000 acres is shown as a possible use case. Plastic pipes are proposed as the means to transport and control proper distribution of water in the field, which significantly helps to reduce conveyance loss. This system utilizes 250 pumps, grouped into 10 clusters, to ensure equal water distribution amongst the users (field owners) in the wide area. The proposed automation algorithm handles the complexity of maintaining proper water pressure throughout the pipe network, scheduling the pump, and controlling the water outlets. Mathematical models are presented for proper dimensioning of the AWD. A low-power and long-range sensor node is developed due to the lack of cellular data coverage in rural areas, and its functionality is tested using an IoT platform for small-scale field trials.

LDCA: Lightweight Dynamic Clustering Algorithm for IoT-Connected Wide-Area WSN and Mobile Data Sink Using LoRa

Wide-area monitoring applications of the Internet-of-Things (IoT) connected wireless sensor network (WSN) consists of sensor nodes (SNs) with limited hardware and energy sources. The distributed nature of such a network and the difficulty of remote access make it more demanding to design an energy-efficient WSN. Moreover, long-range and low-power wireless connectivity is a challenge in IoT-connected applications. Present WSN topologies deal mainly with fixed SNs, SN distribution, and fixed data sink (DS). The majority of the control layer is implemented in the lower hierarchical layer or in a virtual middle layer, which reduces the network lifetime due to excessive processing and data transmission activities. This article proposes a real-time lightweight dynamic clustering algorithm (LDCA) for a WSN that supports the following two scenarios with limited processing resources: 1) with mobile DSs and static SNs (such as DS and SNs mounted on unmanned aerial vehicles, autonomous vehicles) and 2) with mobile SNs and static DSs (such as livestock monitoring or autonomous robots in smart farming, and urban monitoring). The proposed algorithm is based on the received signal strength indicator and signal-to-noise ratio of a long-range (LoRa) interface and its residual energy. Mathematical models were derived for real-time clustering using LoRa. Memory requirement and clustering efficiency of the constrained SN and DS for various mobility scenario were evaluated. The proposed LDCA reduces the energy requirement to 33% compared to static clustering, by reducing the number of concurrent clusters and hops. In addition, a hardware-based approach was used to validate the LDCA algorithm, and evaluate its performance in terms of energy efficiency, packet delivery rate, and network lifetime.

IPv6 WSN Geolocation Using the MAC Address

Wide-area Wireless Sensor Network (WSN) deployments that consist of a large number of distributed nodes can benefit greatly from self-configuration and constant reporting of the location where data was sensed. Previous work has shown how a WSN node can calculate an initial estimate of its location and a finite set of alternate points that could be its actual location, using the coordinates and nominal transmission radius of its neighbours embedded in their IPv6 addresses. This paper extends that work, presenting a scheme for embedding the coordinates in the Ethernet MAC address to allow use of IPv6 header compression. To save energy, a practical and efficient method for exchanging neighbor address information and supporting dynamic address changes is also proposed to replace listening in promiscuous mode. Necessary modifications to the stack are identified, and a test program is outlined.

A reconfigurable hardware platform for low-power wide-area wireless sensor networks

Low power, large-area wireless sensor networks (WSNs) have been experiencing rapid growth in a wide range of applications, such as environmental monitoring applications and natural disaster early warning systems. The WSN consists of numerous nodes with sensing, computation, actuation, and radio communication capabilities. Dynamically reconfigurable hardware and context-aware operation to optimize performance and functionality and to prolong the lifetime of sensor nodes are critical goals in the design of distributed sensing systems, especially for battery-based systems being deployed in complex geographic areas where are hard to approach. In recent years, Programmable System-on-Chip (PSoC) technology is emerging as an efficient solution for achieving the dynamic hardware reconfiguration of a sensor node in a single chip. That aims at optimizing the use of resources, minimizing of energy waste, and system size according to the requirements of the applications. This paper presents the implementation of a configurable hardware platform for remote sensing systems based on PSoC and LoRa technology. The proposed hardware design stands out for high performance, ultralow-power, providing long-range communication as well as reconfigurable interfaces in communicating and manipulating with various types of sensors and actuators. The experiments to evaluate the functional requirements and energy consumption of the design were investigated with positive results.

A Review of Advanced Localization Techniques for Crowdsensing Wireless Sensor Networks.

The wide availability of sensing modules and computing capabilities in modern mobile devices (smartphones, smart watches, in-vehicle sensors, etc.) is driving the shift from mote-class wireless sensor networks (WSNs) to the new era of crowdsensing WSNs. In this emerging paradigm sensors are no longer static and homogeneous, but are rather worn/carried by people or cars. This results in a new type of wide-area WSN—crowd-based and overlaid on top of heterogeneous communication technologies—that paves the way for very innovative applications. To this aim, the positioning of mobile devices operating in the network becomes crucial. Indeed, the pervasive, almost ubiquitous availability of smart devices brings unprecedented opportunities but also poses new research challenges in their precise location under mobility and dense-multipath environments typical of urban and indoor scenarios. In this paper, we review recent advances in the field of wireless positioning with focus on cooperation, mobility, and advanced array processing, which are key enablers for the design of novel localization solutions for crowdsensing WSNs.

Practical Residual Interference After Cancellation for Constant Envelope Modulation With Data-Aided Synchronization

Interference cancellation (IC) is a well-known technique for improving bandwidth utilization in wireless networks. In this paper, we evaluate the practical residual interference of IC with constant envelope modulation in a flat fading environment for a low-power wide area wireless sensor network application, both analytically and experimentally. We propose a new model for the residual interference power, which is the power of the packet being canceled times a random variable. We derive the mean, variance, and distribution of the random variable considering the arbitrary overlapping scenario between two packets with one-time IC. Then, we show how the method can be applied recursively to model the residual interference power when multiple packets are canceled in ordered successive IC. In contrast to the conventional model, we find that this factor varies for different overlapping scenarios and is a function of the signal-to-interference-and-noise ratio of the preamble of the packet being canceled and of the overlapping degree. The theoretical statistics of the residual interference assume maximum likelihood estimation of synchronization offsets.

Improvement on LEACH protocol of a wide-area wireless sensor network

This paper proposes to increase the efficiency energy of nodes which rapidly drops during the transmission of the LEACH (Low Energy Adaptive Clustering Hierarchy), using the method of the dual-hop layered in the sensor field. By introducing dual-hop method in the data transmission, the proposed single-hop method for short-range transmission and multi-hop transmission method between the cluster heads for remote transmission was introduce. By introducing a partial multi-hop method in the data transmission, a single-hop method for short range transmission method between the cluster heads for remote transmission was introduces. In the proposed DL-LEACH, the energy consumption of cluster head for remote transmission reduces and increases the energy efficiency of sensor node by reducing the transmission distance and simplifying the transmission routine for short-range transmission. As compared the general LEACH, it was adapted to a wider sensor field.

A High-Resolution Sensor Network for Monitoring Glacier Dynamics

This paper provides an overview of a wide area wireless sensor network that was deployed on the calving front of the Helheim Glacier in Greenland during the summer of 2013. The purpose of the network was to measure the flow rate of the glacier using accurate satellite positioning data. The challenge in this extreme environment was to collect data in real time at the calving edge of the glacier. This was achieved using a solar powered 2.4-GHz Zigbee wireless sensor network operated in a novel hybrid cellular/mesh access architecture consisting of ice nodes communicating with base stations placed on the rock adjacent to the glacier. This highly challenging transmission environment created substantial signal outage conditions, which were successfully mitigated by a radio network diversity scheme. The network development and measurement campaign were highly successful yielding significant results on glacial dynamics associated with climate change.

Practical Remarks on Designing a Local Segment in a Wide-area Wireless Sensor Network for Measuring Factors Hazardous to the Environment

In order to construct an effective wide-area sensor network, an optimal solution consists in dividing it into a local and a core segment. On the local side, the ZigBee technology is commonly applied to transfer sensor data as it offers effective mechanisms of self-organization and automatic reorganization in case of failure. Since ZigBee is claimed to be natively suited to multi-hop transmission, its performance – in terms of throughput and delay – was quantitatively tested in a chain topology consisting of up to five hops. The achievable data rates were found to be exponentially decreasing with successive hops whereas the delay was growing linearly. A strong dependence was also confirmed between an antenna type used on ZigBee devices and the maximum achievable operating range.DOI: http://dx.doi.org/10.5755/j01.eee.18.9.2821