scholarly journals FROG: A Robust and Green Wireless Sensor Node for Fog Computing Platforms

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Manuel Castillo-Cara ◽  
Edgar Huaranga-Junco ◽  
Milner Quispe-Montesinos ◽  
Luis Orozco-Barbosa ◽  
Enrique Arias Antúnez

Over the past few years, we have witnessed the widespread deployment of wireless sensor networks and distributed data management facilities: two main building blocks of the Internet of things (IoT) technology. Due to the spectacular increase on the demand for novel information services, the IoT-based infrastructures are more and more characterized by their geographical sparsity and increasing demands giving rise to the need of moving from a cloud to a fog model: a novel deployment paradigm characterized by the provisioning of elastic resources geographically located as close as possible to the end user. Despite the large number of wireless sensor networks already available in the market, there are still many issues to be addressed on the design and deployment of robust network platforms capable of meeting the demand and quality of fog-based systems. In this paper, we undertake the design and development of a wireless sensor node for fog computing platforms addressing two of the main issues towards the development and deployment of robust communication services, namely, energy consumption and network resilience provisioning. Our design is guided by examining the relevant macroarchitecture features and operational constraints to be faced by the network platform. We based our solution on the integration of network hardware platforms already available on the market supplemented by smart power management and network resilience mechanisms.

Author(s):  
Mohammad Gholami ◽  
Robert W. Brennan

In this paper, we propose a multi-agent systems approach for wireless sensor node tracking in an industrial environment. The research builds on extant work on wireless sensor node clustering by reporting on the development of a set of simulation models to support our distributed management approach for tracking mobile nodes in a large-scale industrial wireless sensor network. Our simulation models build on models and concepts from the literature on wireless sensor networks and wireless communication, with adaptations to address the needs of an industrial environment. An example of mobile node tracking with our distributed management approach is presented, showing accurate tracking performance for both fixed and random mobile node paths.


2018 ◽  
Vol 210 ◽  
pp. 03011
Author(s):  
Masahiro Okuri ◽  
Hiroaki Higaki

In wireless sensor networks, data messages containing sensor data achieved by a sensor module in a wireless sensor node is transmitted to a stationary wireless sink node along a wireless multihop transmission route in which wireless sensor nodes themselves forward the data messages. Each intermediate wireless sensor node broadcast data messages in its wireless transmission range to forward them to its next-hop intermediate wireless sensor node. Hence, eavesdropper wireless nodes within the wireless transmission range easily overhear the data messages. In order to interfere with the eavesdropper wireless nodes illegally overhearing the data messages in transmission, wireless sensor nodes whose wireless transmission ranges overlap and their next-hop intermediate wireless sensor nodes are out of the wireless transmission ranges each other forward data messages in transmission concurrently and cause collisions between these two data messages at any possible eavesdropper wireless nodes intentionally. To enhance regions where concurrently forwarded data messages intentionally collide to prevent their overhearing and to realize concurrent forwarding of data messages, this paper designes an algorithm for TDMA transmission slot assignments for more opportunities to interfere the eavesdropper wireless nodes.


2021 ◽  
Vol 11 (4) ◽  
pp. 2836-2849
Author(s):  
K. Raghava Rao ◽  
D. Sateesh Kumar ◽  
Mohiddin Shaw ◽  
V. Sitamahalakshmi

Now a days IoT technologies are emerging technology with wide range of applications. Wireless sensor networks (WSNs) are plays vital role in IoT technologies. Construction of wireless sensor node with low-power radio link and high-speed processors is an interesting contribution for wireless sensor networks and IoT applications. Most of WSNs are furnished with battery source that has limited lifetime. The maximum operations of these networks require more power utility. Nevertheless, improving network efficiency and lifetime is a curtail issue in WSNs. Designing a low powered wireless sensor networks is a major challenges in recent years, it is essential to model its efficiency and power consumption for different applications. This paper describes power consumption model based on LoRa and Zigbee protocols, allows wireless sensor nodes to monitor and measure power consumption in a cyclic sleeping scenario. Experiential results reveals that the designed LoRa wireless sensor nodes have the potential for real-world IoT application with due consideration of communicating distance, data packets, transmitting speed, and consumes low power as compared with Zigbee sensor nodes. The measured sleep intervals achieved lower power consumption in LoRa as compared with Zigbee. The uniqueness of this research work lies in the review of wireless sensor node optimization and power consumption of these two wireless sensor networks for IoT applications.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Zhaozhuo Xu ◽  
Fangling Pu ◽  
Xin Fang ◽  
Jing Fu

Wireless sensor networks are proved to be effective in long-time localized torrential rain monitoring. However, the existing widely used architecture of wireless sensor networks for rain monitoring relies on network transportation and back-end calculation, which causes delay in response to heavy rain in localized areas. Our work improves the architecture by applying logistic regression and support vector machine classification to an intelligent wireless sensor node which is created by Raspberry Pi. The sensor nodes in front-end not only obtain data from sensors, but also can analyze the probabilities of upcoming heavy rain independently and give early warnings to local clients in time. When the sensor nodes send the probability to back-end server, the burdens of network transport are released. We demonstrate by simulation results that our sensor system architecture has potentiality to increase the local response to heavy rain. The monitoring capacity is also raised.


Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.


2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.


The fundamental capacity of a sensor system is to accumulate and forward data to the destination. It is crucial to consider the area of gathered data, which is utilized to sort information that can be procured using confinement strategy as a piece of Wireless Sensor Networks (WSNs).Localization is a champion among the most basic progressions since it agreed as an essential part in various applications, e.g., target tracking. If the client can't gain the definite area information, the related applications can't be skillful. The crucial idea in most localization procedures is that some deployed nodes with known positions (e.g., GPS-equipped nodes) transmit signals with their coordinates so as to support other nodes to localize themselves. This paper mainly focuses on the algorithm that has been proposed to securely and robustly decide thelocation of a sensor node. The algorithm works in two phases namely Secure localization phase and Robust Localization phase. By "secure", we imply that malicious nodes should not effectively affect the accuracy of the localized nodes. By “robust”, we indicate that the algorithm works in a 3D environment even in the presence of malicious beacon nodes. The existing methodologies were proposed based on 2D localization; however in this work in addition to security and robustness, exact localization can be determined for 3D areas by utilizing anefficient localization algorithm. Simulation results exhibit that when compared to other existing algorithms, our proposed work performs better in terms of localization error and accuracy.


2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime


Author(s):  
Anshu Kumar Dwivedi ◽  
Awadhesh Kumar Sharma ◽  
Pawan Singh Mehra

Now a day wireless sensor networks (WSNs) is an essential unit of the internet of things (IoT). IoT theater a vital role in real-time applications which is more useful in real life. Due to its small price and potential use, WSNs have shown importance in different applications over the past year. Health concerns, environmental observation, human protection, military operations, surveillance systems, etc. WSNs have a small device called a sensor node (SN) that has a limited battery. IoT based WSNs consume more energy in sensor node communication. Therefore a Novel energy-efficient sensor node deployment scheme for two-stage routing protocol (EE- DSTRP) has been proposed to reduce the energy consumption of sensor nodes and extend the lifetime of the network. Sensor node deployment is a novel approach based on the golden ratio. All traditional protocols divide network zones for communication. No existing protocols tell about the sensor node deployment ratio in each zone. The deployment method is an important factor in reducing the energy usage of a network. To validate its efficiency, in this article, simulation results prove that the proposed IoT based EE-DSTRP protocol is superior to other existing protocols.


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