Review of Energy Conservation Using Duty Cycling Schemes for IEEE 802.15.4 Wireless Sensor Network (WSN)

Shabaneh, A. A.; Ali, Azizi Mohd; Ng, Chee Kyun; Noordin, Nor Kamariah; Sali, Aduwati; Yaacob, Mohd Hanif

doi:10.1007/s11277-013-1524-y

Cited by 18 publications

(8 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Duty cycling schemes aim to save energy by reducing the idle listening state and promoting the sleep mode. These schemes turn off the radio of a node most of the time and wake it up only if needed or at scheduled moments [ 115 , 116 ]. However, data latency issue occurs because the transmitter node needs to wait for the receiver node to be awake.…”

Section: Energy Saving On Network Levelmentioning

confidence: 99%

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Kanoun

Bradai

Khriji

et al. 2021

Sensors

View full text Add to dashboard Cite

Nowadays, wireless sensor networks are becoming increasingly important in several sectors including industry, transportation, environment and medicine. This trend is reinforced by the spread of Internet of Things (IoT) technologies in almost all sectors. Autonomous energy supply is thereby an essential aspect as it decides the flexible positioning and easy maintenance, which are decisive for the acceptance of this technology, its wide use and sustainability. Significant improvements made in the last years have shown interesting possibilities for realizing energy-aware wireless sensor nodes (WSNs) by designing manifold and highly efficient energy converters and reducing energy consumption of hardware, software and communication protocols. Using only a few of these techniques or focusing on only one aspect is not sufficient to realize practicable and market relevant solutions. This paper therefore provides a comprehensive review on system design for battery-free and energy-aware WSN, making use of ambient energy or wireless energy transmission. It addresses energy supply strategies and gives a deep insight in energy management methods as well as possibilities for energy saving on node and network level. The aim therefore is to provide deep insight into system design and increase awareness of suitable techniques for realizing battery-free and energy-aware wireless sensor nodes.

show abstract

Section: Energy Saving On Network Levelmentioning

confidence: 99%

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Kanoun

Bradai

Khriji

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Typically, however, we need to be slightly larger than this value because the sensor node is not guaranteed to find an available PU from which to harvest energy during all the ( − 1) time slots, which means, depending on the activity behavior of the PUs in the system, might need to be larger than that specified by (2) to ensure that the sensor nodes harvest Γ energy to be able to transmit one packet in that cycle.…”

Section: Journal Of Sensorsmentioning

confidence: 99%

“…Wireless Sensor Networks (WSNs) are made up of a big number of distributed sensor nodes, fitted with various sensors and typically spread over a wide geographical area [1]. Such WSNs have found a wide range of applications nowadays, including periodic monitoring, security, surveillance, and health monitoring and control [2]. Energy consumption is a major issue in the design of WSN protocols, since each WSN node is equipped with limited power supply, due to cost considerations.…”

Section: Introductionmentioning

confidence: 99%

A Self-Learning MAC Protocol for Energy Harvesting and Spectrum Access in Cognitive Radio Sensor Networks

et al. 2016

View full text Add to dashboard Cite

The fusion of Wireless Sensor Networks (WSNs) and Cognitive Radio Networks (CRNs) into Cognitive Radio Sensor Networks (CRSNs) is quite an attractive proposal, because it allows a distributed set of low-powered sensor nodes to opportunistically access spectrum bands that are underutilized by their licensed owners (called primary users (PUs)). In addition, when the PUs are actively transmitting in their own bands, sensor nodes can switch to energy harvesting mode to obtain their energy needs (for free), to achieve almost perpetual life. In this work, we present a novel and fully distributed MAC protocol, calledS-LEARN, that allows sensor nodes in a CRSN to entwine their RF energy harvesting and data transmission activities, while intelligently addressing the issue of disproportionate difference between the high power necessary for the node to transmit data packets and the small amount of power it can harvest wirelessly from the environment. The presented MAC protocol can improve both the network throughput and total harvested energy, while being robust to changes in the network configuration. Moreover, S-LEARN can keep the cost of the system low, and it avoids the pitfalls from which centralized systems suffer.

show abstract

“…Initialization: Set = 0 and randomly generate (0) , {p (0) −1 }, { (0) −1 }, and t (0) so that (20a), (20b), (20c), (20d), and (20e) is feasible. (1) repaet (2) Solve (20a), (20b), (20c), (20d), and (20e) to obtain the optimal solutions * , {p * −1 }, { * −1 } and t * . (…”

Section: Proposed Algorithm For Solving the Optimization Problemmentioning

confidence: 99%

“…Wireless sensor network (WSN) is basically made up of a large number of various sensor nodes that typically spread over a large geographical area. WSN is used to collect information on surrounding context and environment and employed over a wide range of applications, such as smart buildings, transportation and logistics, health cares, and smart grids [1, 2]. Recently, WSN is considered as one of the key enablers for the Internet of Things (IoT) [3].…”

Section: Introductionmentioning

confidence: 99%

Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks

Nguyen

Shin

2016

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

We consider an energy harvesting for cooperative wireless sensor networks with a nonlinear power consumption model. The information transmission from the source node to the destination node is assumed to occur via several clusters of decode-andforward relay nodes. We assume that all the source and relay nodes have the ability to harvest energy from the environment and use that harvested energy to transmit and forward the information to the next hop. Under such assumption, the objective of our design is to improve the total throughput of the end-to-end link over a number of transmission blocks subject to constraints on energy causality, battery overflow, and time duration for energy harvesting. The optimization problem is found to be a nonconvex maximin fractional program, which is difficult to solve in general. We present an efficient iterative algorithm to solve the optimization problem. Specifically, by introducing novel transformations, we apply an approximate convex technique to obtain a convex problem at each iteration. We then propose an iterative power allocation algorithm which converges to a locally optimal solution at a Karush-Kuhn-Tucker point. Numerical results are provided to evaluate the proposed scheme.

show abstract

Review of Energy Conservation Using Duty Cycling Schemes for IEEE 802.15.4 Wireless Sensor Network (WSN)

Cited by 18 publications

References 15 publications

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

A Self-Learning MAC Protocol for Energy Harvesting and Spectrum Access in Cognitive Radio Sensor Networks

Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks

Contact Info

Product

Resources

About