scholarly journals CU-MAC: A Duty-Cycle MAC Protocol for Internet of Things in Wireless Sensor Networks

2018 ◽  
Vol 16 (2) ◽  
pp. 30-43
Author(s):  
Tanapoom Danmanee ◽  
Kulit Na Nakorn ◽  
Kultida Rojviboonchai
Keyword(s):  
Internet Of Things ◽  
Duty Cycle ◽  
Data Transfer ◽  
Mac Protocol ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Local Network ◽  
The Internet ◽  
Delivery Ratio ◽  
Hidden Terminal

Nowadays “Internet of Things” or IoT becomes the most popular technology in the Internet system. Types of devices and sensors have been connected as a network of devices and sensors. While a wireless sensor network is a traditional network of sensors that can be considered as a beginning point of IoT systems. Currently, these sensor data are not only exchanged within a local network but also are delivered to other devices in the Internet. Consequently, well-known organizations such as IEEE, IETF, ITU-T and ISO/IET are trying to set standards for wireless sensor devices in IoT systems. The recommended standard utilizes many of internet stack standards such as CoAP, UDP and IP. However, the traditional design of WSNs is to avoid using internet protocol in the system to reduce transmission overhead and power consumption due to resource limitation. Fortunately, the current technology in both hardware and software allow the internet standard to sufficiently operate in a small sensor.  In this paper, we propose a MAC protocol named CU-MAC to efficiently support IoT standard that need request-respond communication or bi-direction communication. CU-MAC uses multi-channel communication to perform continuous and bi-directional data transfer at low duty-cycle. It also has a mechanism to overcome the hidden terminal problem. We evaluated the performance of CU-MAC on both simulation and real testbed based on Contiki OS. The result shows that CU-MAC outperforms other existing MAC protocols in term of packet delivery ratio at 98.7% and requires lower duty-cycle than others to operate in the high traffic environment.

A Semantic Sensor Web Architecture in the Internet of Things

2019 ◽  
pp. 75-97
Author(s):  
Eliot Bytyçi ◽  
Besmir Sejdiu ◽  
Arten Avdiu ◽  
Lule Ahmedi
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Web Architecture ◽  
Hidden Knowledge ◽  
Semantic Sensor Web ◽  
The Internet Of Things ◽  
The Web

The Internet of Things (IoT) vision is connecting uniquely identifiable devices to the internet, best described through ontologies. Furthermore, new emerging technologies such as wireless sensor networks (WSN) are recognized as essential enabling component of the IoT today. Hence, the interest is to provide linked sensor data through the web either following the semantic web enablement (SWE) standard or the linked data approach. Likewise, a need exists to explore those data for potential hidden knowledge through data mining techniques utilized by a domain ontology. Following that rationale, a new lightweight IoT architecture has been developed. It supports linking sensors, other devices and people via a single web by mean of a device-person-activity (DPA) ontology. The architecture is validated by mean of three rich-in-semantic services: contextual data mining over WSN, semantic WSN web enablement, and linked WSN data. The architecture could be easily extensible to capture semantics of input sensor data from other domains as well.

scholarly journals Optimization of Water Microbial Concentration Monitoring System Based on Internet of Things

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Miaomiao Zheng ◽  
Shanshan Zhang ◽  
Yidan Zhang ◽  
Baozhong Hu
Keyword(s):  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Environmental Monitoring ◽  
Data Acquisition ◽  
Development Trend ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Microbial Sensor ◽  
The Internet Of Things

The Internet of Things is an emerging information industry. Applying the information collection, transmission, and processing technologies in the Internet of Things technology to environmental monitoring, environmental emergency, and other environmental protection supervision fields will greatly improve the speed and accuracy of environmental supervision and facilitate the scientific development of environmental protection. Through the Internet of Things, people can obtain a large amount of reliable real-time information, and it is not easy to be affected by time, place, and environment, while the wireless sensor network has the advantages of easy installation and low cost, so environmental monitoring through the Internet of Things is the future development trend. In this paper, in view of the current situation of water scarcity and serious water pollution in China, combined with the development trend and advantages of the Internet of Things (IoT), and based on the inadequacy of the existing microbial sensor data collection equipment, we propose a design scheme of microbial concentration monitoring system for waters based on IoT. The system is based on Zig Bee wireless sensor network to build a common data acquisition platform and design special hardware to carry out high-precision microbial sensor data acquisition in water and through the PC to complete the real-time measurement data storage, waveform display, and data processing. In this paper, the schematic diagram and PCB board design of the system hardware module NUC120 main control board, CC2530 RF board, Wi-Fi wireless communication module, and high-precision ADC acquisition module are completed and fabricated. Then, the four modules are combined to realize the development of the data aggregation node and data acquisition node of the dedicated Zig Bee wireless network hardware device.

Implementation of Smart Home with Multi-Channel Technology

2015 ◽  
Vol 764-765 ◽  
pp. 579-583
Author(s):  
Chia Hsin Cheng ◽  
Chung Ching Ho ◽  
Yeh Wei Lin
Keyword(s):  
Smart Home ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Automation System ◽  
Delivery Ratio ◽  
Monitor System ◽  
Packet Delivery ◽  
Embedded Platform ◽  
Hidden Terminal ◽  
Access Control System

In this paper, we propose a Smart-Home system with ZigBee Wireless Sensor Networks (WSNs) technology. The system provides automation system in the House. The monitor system uses Andriod NDK and SDK to write application interface for an Android embedded platform. In this system, we provide access control system to obtain sensor data and inquiry into node status. We use multi-channel architecture to reduce a hidden terminal problem and upgrade packet delivery ratio.

SEMDPA

2020 ◽  
pp. 977-998
Author(s):  
Eliot Bytyçi ◽  
Besmir Sejdiu ◽  
Arten Avdiu ◽  
Lule Ahmedi
Keyword(s):  
Data Mining ◽  
Wireless Sensor Networks ◽  
Internet Of Things ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Contextual Data ◽  
Hidden Knowledge ◽  
The Internet Of Things ◽  
The Web

The Internet of Things (IoT) vision is to connect uniquely identifiable devices that surround us to the Internet, which is best described through ontologies. Thereby, new emerging technologies such as wireless sensor networks (WSN) are recognized as an essential enabling component of the IoT today. Hence, given the increasing interest to provide linked sensor data through the Web either following the Semantic Web Enablement (SWE) standard or the Linked Data approach, there is a need to also explore those data for potential hidden knowledge through data mining techniques utilized by a domain ontology. Following that rationale, a new lightweight IoT architecture SEMDPA has been developed. It supports linking sensors and other devices, as well as people via a single web by mean of a device-person-activity (DPA) crossroad ontology. The architecture is validated by mean of three rich-in-semantic services: contextual data mining over WSN, semantic WSN web enablement, and Linked WSN data. SEMDPA could be easily extensible to capture semantics of input sensor data from other domains as well.

scholarly journals Duty Cycle Control Method Considering Buffer Occupancy for IEEE 802.15.4-Compliant Heterogeneous Wireless Sensor Network

2021 ◽  
Vol 11 (4) ◽  
pp. 1362
Author(s):  
Kohei Tomita ◽  
Nobuyoshi Komuro
Keyword(s):  
Duty Cycle ◽  
Ieee 802.15.4 ◽  
Control Method ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Buffer Occupancy ◽  
Heterogeneous Wireless Sensor Networks ◽  
Heterogeneous Wireless Sensor Network ◽  
Analytical Expressions

This paper proposes a Duty-Cycle (DC) control method in order to improve the Packet Delivery Ratio (PDR) for IEEE 802.15.4-compliant heterogeneous Wireless Sensor Networks (WSNs). The proposed method controls the DC so that the buffer occupancy of sensor nodes is less than 1 and assigns DC to each sub-network (sub-network means a network consisting of a router node and its subordinate nodes). In order to use the appropriate DC of each sub-network to obtain the high PDR, this paper gives analytical expressions of the buffer occupancy. The simulation results show that the proposed method achieves a reasonable delay and energy consumption while maintaining high PDR.

scholarly journals Problems of Powering End Devices in Wireless Networks of the Internet of Things

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2417
Author(s):  
Andrzej Michalski ◽  
Zbigniew Watral
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Wireless Sensor ◽  
Alternative Possibilities ◽  
The Internet ◽  
Power Sources ◽  
Wide Range ◽  
The Internet Of Things

This article presents the problems of powering wireless sensor networks operating in the structures of the Internet of Things (IoT). This issue was discussed on the example of a universal end node in IoT technology containing RFID (Radio Frequency Identification) tags. The basic methods of signal transmission in these types of networks are discussed and their impact on the basic requirements such as range, transmission speed, low energy consumption, and the maximum number of devices that can simultaneously operate in the network. The issue of low power consumption of devices used in IoT solutions is one of the main research objects. The analysis of possible communication protocols has shown that there is a possibility of effective optimization in this area. The wide range of power sources available on the market, used in nodes of wireless sensor networks, was compared. The alternative possibilities of powering the network nodes from Energy Harvesting (EH) generators are presented.

scholarly journals A Novel Bioinspired Multiobjective Optimization Algorithm for Designing Wireless Sensor Networks in the Internet of Things

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Jun Huang ◽  
Liqian Xu ◽  
Cong-cong Xing ◽  
Qiang Duan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Multiobjective Optimization ◽  
Optimization Algorithm ◽  
Chaotic Behavior ◽  
Ant Colony ◽  
Wireless Sensor ◽  
The Internet ◽  
The Internet Of Things

The design of wireless sensor networks (WSNs) in the Internet of Things (IoT) faces many new challenges that must be addressed through an optimization of multiple design objectives. Therefore, multiobjective optimization is an important research topic in this field. In this paper, we develop a new efficient multiobjective optimization algorithm based on the chaotic ant swarm (CAS). Unlike the ant colony optimization (ACO) algorithm, CAS takes advantage of both the chaotic behavior of a single ant and the self-organization behavior of the ant colony. We first describe the CAS and its nonlinear dynamic model and then extend it to a multiobjective optimizer. Specifically, we first adopt the concepts of “nondominated sorting” and “crowding distance” to allow the algorithm to obtain the true or near optimum. Next, we redefine the rule of “neighbor” selection for each individual (ant) to enable the algorithm to converge and to distribute the solutions evenly. Also, we collect the current best individuals within each generation and employ the “archive-based” approach to expedite the convergence of the algorithm. The numerical experiments show that the proposed algorithm outperforms two leading algorithms on most well-known test instances in terms of Generational Distance, Error Ratio, and Spacing.

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