While Wireless Sensor Networks Research Articles

Optimized Clustering Protocol for Balancing Energy in Wireless Sensor Networks

While wireless sensor networks (WSNs) are increasingly equipped to handle more complex functions and in-network processing may require these battery powered sensors to judiciously use their constrained energy to prolong the effective network lifetime. Cluster-based Hierarchical Routing Protocol using compressive sensing (CS) theory (CBHRP-CS) divides the network into several clusters, each managed by a set of CHs called a header. Each member of the header compresses the collected data using CS. This paper proposes an optimized clustering protocol using CS (OCP-CS) to improve the performance of WSNs by exploiting compressibility. In OCP-CS, each cluster is managed by a cluster head (CH). CHs are selected based on node concentration and sensor residual energy, and performs data aggregation using CS to reduce the energy consumed in the process of data sampling and transmission. Simulations show that our proposed protocol is effective in prolonging the network lifetime and supporting scalable data aggregation than existing protocols.

Python-Based TinyIPFIX in Wireless Sensor Networks

While wireless sensor networks (WSN) offer potential, their limited programmability and energy limitations determine operational challenges. Thus, a TinyIPFIX-based system was designed such that this application layer protocol is now used to exchange data in WSNs efficiently. The new prototype is based on the Espressif ESP32-WROOM-32D Internet-of-Things (IoT) platform, which is becoming famous, as it is inexpensive but powerful compared to older generations of IoT devices. The system implementation is provided in the programming language MicroPython, which provides a simple and efficient implementation, compared to a lower-level programming language. Therefore, this approach focuses on value creation rather than platform-specific implementation difficulties. The system is evaluated in smart home use cases and displays valuable overhead, reliability, and power efficiency. TinyIPFIX outperforms the data overhead of the type–length–value (TLV) paradigm by a factor of 7% when a TinyIPFIX data message carries only two records, and one TinyIPFIX template message is sent per three TinyIPFIX data messages. A further decrease in overhead is observed when the number of data records per message and the number of TinyIPFIX data messages sent per one TinyIPFIX template message increase to larger values. The message delivery between end devices and the application server resides at a very high level, close to 100%, when the transmission reliability is secured with acknowledgments and retransmissions. The energy efficiency resides at the limited level, as the experienced deep sleep power consumption of the ESP32 device resides at the milliwatt level.

Determination of Energy Consumption According to Wireless Network Topologies in Grid-Free Lighting Systems

While Wireless Sensor Networks (WSN) are used in various areas nowadays, they also come in front of us in the remote follow up and management of especially main street, road and city lighting systems and in autonomous applications relating with them. This study has been conducted with the aim to determine the energy consumed by Wireless Sensor Network (WSN) based monitoring and management systems as per topological sequence of lighting systems with renewable energy sources (RES) in a grid-free environment. In this way it was aimed to maximize the life time of WSN which are formed by minimum energy consumption of lighting elements that store energy with accumulator-battery in grid-free RES lighting systems and which use this energy later on. Physical installation of lighting systems having different topological distributions will show differences with respect to costs, labour force and time. Starting from here on, different topologies for grid-free lighting systems have been created in simulation environment and they have been analyzed and an optimal solution has been searched for. Energy consumptions of each lighting system having linear, random and tree lighting topology have been determined during data exchange. For each topology lighting systems with 25, 50, 100 and 200 armatures have been designed and their energy consumptions for data exchange have been found. It has been seen that data packages were influenced at first degree from node hopping numbers within topology and as being parallel to this, it has been seen that topology consuming most energy was linear lighting and that topology consuming minimum energy was tree lighting.

A multi-sensor data fusion technique using data correlations among multiple applications

While wireless sensor networks (WSNs) have been traditionally tasked with single applications, in recent years we have witnessed the emergence of WSNs that allow the sensing and communication infrastructure to be shared among multiple applications thus optimizing the use of resources. As the number of applications in a WSN increases, a growing amount of sensor-generated data will be produced, from which useful information can be extracted. A major requirement in these networks is to save energy in order to extend their operational lifetime. However, wireless sensors and actuators commonly rely on batteries as their energy sources, whose replacement is undesirable or unfeasible. Among the methods employed to extend network lifetime, Multisensor data fusion (MDF) is one of the most widely used. Traditional MDFs are not able to identify different contexts, since they are designed using an application-specific design for the network. As the number of applications increases, the application data ranges overlap and it becomes more complex to identify the origin of each data sample to deliver data to the correct application, with the consequence of reducing data accuracy. In order to overcome these limitations, we propose a MDF technique that divides the monitored interval into a set of intervals (non-overlapped intervals and overlapped intervals) and attributes each interval to an abstract sensor. Then we use MDFs to identify (hidden) correlations in abstract sensors and to exploit such knowledge to monitor the behavior of sensors during their working life. Our proposal is validated through simulations and tests on real nodes.

A Systematic Review of Shared Sensor Networks

While Wireless Sensor Networks (WSNs) have been traditionally tasked with single applications, in recent years we have witnessed the emergence of Shared Sensor Networks (SSNs) as integrated cyber-physical system infrastructures for a multitude of applications. Instead of assuming an application-specific network design, SSNs allow the underlying infrastructure to be shared among multiple applications that can potentially belong to different users. On one hand, a potential benefit of such a design approach is to increase the utilization of sensing and communication resources, whenever the underlying network infrastructure covers the same geographic area and the sensor nodes monitor the same physical variables of common interest for different applications. On the other hand, compared with the existing application-specific design, the SSNs approach poses several research challenges with regard to different aspects of WSNs. In this article, we present a systematic literature survey on SSNs. The main goal of the article is to provide the reader with the opportunity to understand what has been done and what remains as open issues in this field, as well as which are the pivotal factors of this evolutionary design and how this kind of design can be exploited by a wide range of WSN applications.

Power Efficient Scheduled-Based Medium Access Control Protocol over Wireless Sensor Networks

The flexible use of sensors has made them an attractive device to be deployed in almost every field of life such as health, military and home. Recent advancement in electronics and wireless communications has witnessed the development of low cost-sensor devices. While wireless sensor networks (WSNs) are flexible to use and less costly, they need to be more energy-efficient as they are operated by the battery. Mostly they are deployed in harsh environments where it is very difficult to change the batteries frequently. Several medium access control (MAC) algorithms have been developed for the energy-efficient acquisition of the wireless channel, however, none of them are satisfactory. In this paper, we proposed a medium access control algorithm called MAC-PE. MAC-PE is based on the concept of prioritized frames where prioritized frames are transmitted urgently. In addition, it uses scheduled-based MAC instead of accessing channel randomly. We found MAC-PE (Power-Efficient MAC) was efficient in terms of power consumption without sacrificing on the performance using NS-2.

Analysis of Power Characteristics for Sap Flow, Soil Moisture, and Soil Water Potential Sensors in Wireless Sensor Networking Systems

While wireless sensor networks (WSNs) become more popular as a tool for scientists and engineers in environmental monitoring, the energy efficiency of WSN's primary unit, the mote, is increasingly critical. Motes perform communication and processing functions and also take measurements using limited onboard battery power. For environmental monitoring deployment, sampling rates need to be assigned to motes such that useful information can be extracted over both spatial and temporal scales. The data sampling rate, which is intimately related to data transmission rate, plays an important role in the mote's battery life. Moreover, while it has been noted that mote operation continues under less than optimal power supply levels, data collected during this time undergoes attenuation from the desired measurement. That is, low battery conditions of motes could significantly affect the accuracy of sensed data. This paper investigates the above two issues to achieve extended battery life for individual wireless motes while maintaining sampling adequacy and reliability in transmitting accurate data. We first study how different sensor characteristics, such as different types of sap flow sensors, can affect motes' sampling and transmission rate. Then, we examine the effect of sensing attenuation due to low battery power on sap flow, soil moisture, and soil water potential measurements. A simple regression model was found to correct data for both the sap flow and soil water potential sensors sampled on under-powered motes. By operating under less than optimal power levels, this effectively increases motes' battery life for reliable data collection from wireless sensor networks.

Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity

While wireless sensor networks (WSN) are increasingly equipped to handle more complex functions, in-network processing still requires the battery-powered sensors to judiciously use their constrained energy so as to prolong the elective network life time. There are a few protocols using sensor clusters to coordinate the energy consumption in a WSN, but how to deal with energy heterogeneity remains a research question. The authors propose a modified clustering algorithm with a three-tier energy setting, where energy consumption among sensor nodes is adaptive to their energy levels. A theoretical analysis shows that the proposed modifications result in an extended network stability period. Simulation has been conducted to evaluate the new clustering algorithm against some existing algorithms under different energy heterogeneity settings, and favourable results are obtained especially when the energy levels are significantly imbalanced.

FieldMAP: A Spatiotemporal Field Monitoring Application Prototyping Framework

The fundamental aim of monitoring is to identify abnormalities in the observed phenomena and allow inference of the likely cause. Faced with the common problems of spatially irregular sensor distribution and intermittent sensor measurement availability, key to fulfilling the monitoring aim is filling in the spatiotemporal gaps in the data. While wireless sensor networks (WSNs) technology, combined with microelectromechanical systems availability potentially offer sensing solutions for a variety of application domains, in the context of monitoring applications a conceptual shift is needed from currently available, point-measurement-based ldquosense-and-sendrdquo systems toward the provision of phenomena field representations, in real time, enabling effective visualization of the spatiotemporal patterns. This paper argues the case for a generic, rapid prototyping framework for end-to-end sensing systems that support the approach of providing field representations for visualization. A formal approach to framework development was taken, ensuring that resulting instrumentation systems are well specified. Both the framework development and its evaluation are linked to the full cycle of requirements setting, design, and deployment of a prototype instrumentation system for aerospace applications-specifically, health monitoring of a gas turbine engine. The field monitoring application prototyping (FieldMAP) framework supports multimodal sensing, provides a number of opportunities for data processing and information extraction, caters for monitoring of the instrumentation health, offers a modular field-mapping design component and allows for real-time phenomena visualization, data and information logging, and postanalysis. Experience with the FieldMAP has shown that sophisticated and robust prototypes can be developed in a short period of time.