Energy-Aware Real-Time Routing for Large-Scale Industrial Internet of Things

Nguyen, Bach Long; Tran-Dang, Hoa; Kim, Dong-Seong

doi:10.1109/jiot.2018.2827050

Cited by 80 publications

(33 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…IIoT / ICPS [372], [386], [392], [393], [366], [367], [375], [394], [395], [398] WSAN [369]- [371], [377], [396], [373], [374], [376], [378], [379], [381] NCS -Industrial Robots [384] Assembly Line [62], [364], [365], [383], [385], [387], [6], [388]- [391], [399] M2M Communication [368], [397] whole toward minimizing energy consumption is proposed in [384]. Dynamic low-power reconfiguration [364] and machine energy consumption minimization [365] are key objectives of novel assembly lines.…”

Section: Data Enabling Technology Articles On Energy Managementmentioning

confidence: 99%

Data Management in Industry 4.0: State of the Art and Open Challenges

2019

View full text Add to dashboard Cite

Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This article surveys the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future. As a first step, we extract important data properties (volume, variety, traffic, criticality) and identify the corresponding data enabling technologies of diverse fundamental industrial use cases, based on practical applications. Secondly, we provide a detailed outline of recent industrial architectural designs with respect to their data management philosophy (data presence, data coordination, data computation) and the extent of their distributiveness. Then, we conduct a holistic survey of the recent literature from which we derive a taxonomy of the latest advances on industrial data enabling technologies and data centric services, spanning all the way from the field level deep in the physical deployments, up to the cloud and applications level. Finally, motivated by the rich conclusions of this critical analysis, we identify interesting open challenges for future research. The concepts presented in this article thematically cover the largest part of the industrial automation pyramid layers. Our approach is multidisciplinary, as the selected publications were drawn from two fields; the communications, networking and computation field as well as the industrial, manufacturing and automation field. The article can help the readers to deeply understand how data management is currently applied in networked industrial environments, and select interesting open research opportunities to pursue.

show abstract

Section: Data Enabling Technology Articles On Energy Managementmentioning

confidence: 99%

Data Management in Industry 4.0: State of the Art and Open Challenges

2019

View full text Add to dashboard Cite

show abstract

“…Existing literature has also claimed beneficial usage of machine learning approach for enhancing the consumption of energy in IoT as seen in work of Javed et al [28]. Long et al [29] have presented an energy-aware routing scheme for massive scale of deployment of IoT nodes. Discussion of fog-based energy management scheme was carried out by Moghaddam et al [30] emphasizing over delay and bandwidth.…”

Section: A the Backgroundmentioning

confidence: 99%

Robust Modelling to Jointly Address Security Threats, Bandwidth Utilization, and Energy issues in IoT

Ambore*,

2019

IJITEE

View full text Add to dashboard Cite

The advent of Internet-of-Things (IoT) revolutionizes the mechanism of connectivity of massive chains of machine offering better improvement in data communication and analytical services. Review of existing approaches towards IoT performance improvement shows that there are still larger scope of enhancing the present solution. The proposed system introduces a mechanism where 3 different problems has been jointly addressed viz. security issues, channel capacity issues, energy depletion issues. The proposed model uses analytical research methodology where energy problem is offered common focus and linked with other two problem using stochastic method, probability logic, decision-making approach, packet scheduling, etc. The simulation outcome of the study shows that proposed system offers better energy efficiency, better resistivity against threats, and effective optimization of the bandwidth in contrast to existing related mechanism towards IoT ecosystem.

show abstract

“…WSN applications have varying characteristics and network requirements. Generally, each sensor in a WSN collects and processes data, routing it to a sink node or base station via other sensors [1].…”

Section: Introductionmentioning

confidence: 99%

Hybrid MAC Protocol for UAV-Assisted Wireless Sensor Networks

Ramli¹,

D²,

Lee³

2018

Preprint

Self Cite

View full text Add to dashboard Cite

This paper proposes a hybrid medium access control (MAC) protocol for wireless sensor network (WSN) data gathering, employing unmanned aerial vehicles (UAV). The UAV sends a beacon frame periodically to inform sensor nodes regarding its presence. Afterward, each sensor node which receives beacon frame contends to send registration frame to the UAV. The UAV will transmit the second beacon frame to the registered nodes to notify their transmission schedule. The time-slot scheme is used for the transmission schedule. The transmission schedule of each sensor is determined based on their priority. Specifically, the priority of each sensor is determined during the registration process. Furthermore, the architecture of UAV-WSN data gathering system is introduced in this paper. Simulations are performed, showing that the proposed MAC protocol achieves fairness while enhancing network performance.

show abstract

Energy-Aware Real-Time Routing for Large-Scale Industrial Internet of Things

Cited by 80 publications

References 42 publications

Data Management in Industry 4.0: State of the Art and Open Challenges

Data Management in Industry 4.0: State of the Art and Open Challenges

Robust Modelling to Jointly Address Security Threats, Bandwidth Utilization, and Energy issues in IoT

Hybrid MAC Protocol for UAV-Assisted Wireless Sensor Networks

Contact Info

Product

Resources

About