Adaptive energy saving algorithms for Internet of Things devices integrating end and edge strategies

Wang, Yang; Yang, Kun; Wan, Weixiang; Mei, Haibo

doi:10.1002/ett.4122

Cited by 3 publications

(5 citation statements)

References 35 publications

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“…This method leads to a reduced amount of sampled, processed, and transmitted data [19]. The primary motivation for introducing the adaptive sampling mechanisms is that in some sensor nodes, a significant percentage of energy is consumed by the sensing module, and it is necessary to reduce this energy consumption for the purposes of WSN lifetime extension [25,26]. The adaptive sampling approach was used in WSN for detection of water leaks from pipelines [25].…”

Section: Adaptive Samplingmentioning

confidence: 99%

Data Transmission Reduction in Wireless Sensor Network for Spatial Event Detection

Lewandowski

Płaczek

2021

Sensors

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Wireless sensor networks have found many applications in detecting events such as security threats, natural hazards, or technical malfunctions. An essential requirement for event detection systems is the long lifetime of battery-powered sensor nodes. This paper introduces a new method for prolonging the wireless sensor network’s lifetime by reducing data transmissions between neighboring sensor nodes that cooperate in event detection. The proposed method allows sensor nodes to decide whether they need to exchange sensor readings for correctly detecting events. The sensor node takes into account the detection algorithm and verifies whether its current sensor readings can impact the event detection performed by another node. The data are transmitted only when they are found to be necessary for event detection. The proposed method was implemented in a wireless sensor network to detect the instability of cargo boxes during transportation. Experimental evaluation confirmed that the proposed method significantly extends the network lifetime and ensures the accurate detection of events. It was also shown that the introduced method is more effective in reducing data transmissions than the state-of-the-art event-triggered transmission and dual prediction algorithms.

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Section: Adaptive Samplingmentioning

confidence: 99%

Data Transmission Reduction in Wireless Sensor Network for Spatial Event Detection

Lewandowski

Płaczek

2021

Sensors

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“…The new transmission frame was introduced to decrease the transmission collision, the frame having multiple slots, where each slot is cooperatively determined by parent–child pairs. Wang et al 30 proposes an integrated strategy for energy saving of internet of things (IoT) devices the strategy consists of two algorithms at the end and edge. an energy efficient automatic mode switching algorithm is designed at the end based on the changeable battery level and downlink communication traffic of the battery‐powered wireless nodes.…”

Section: Related Work On Duty Cycle Of Wmsnmentioning

confidence: 99%

“…The queueing delay is the most dynamic delay components and it is indicative of bandwidth utilization and congestion level. The limitations of previous literature studies 6‐36 are summarized in Table 1. The main advantage of the proposed dynamic duty cycle is the ability to maintain a balance between energy and latency where the packet service time (PST), traffic priority and per hop delay requirements are considered.…”

Section: Related Work On Duty Cycle Of Wmsnmentioning

confidence: 99%

Adaptive dynamic duty cycle mechanism for energy efficient medium access control in wireless multimedia sensor networks

Ahmed

Abazeed

2021

Trans Emerging Tel Tech

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Multimedia applications require significantly higher bandwidth than conventional textual applications. Furthermore, multimedia stream requires time sensitive and involves high-energy consumption, which become more challenging on resource constrained networks such as wireless multimedia sensor network (WMSN). As a result, developing an energy efficient algorithm to prolong the network lifetime is the main reoccurring issue in WMSN. Although the duty cycling mechanism has been proven to be an efficient solution for energy saving in various WSN applications, the tradeoff between energy efficiency and quality of service (QoS) on WMSN remains striking. In this article, an adaptive dynamic duty cycle mechanism for energy-efficient medium access control (ADE-MAC) is proposed for WMSNs. ADE-MAC uses a unique asynchronous duty cycle approach to schedule the sleep pattern of each sensor node which can be adapted according to the incoming traffic rate and queuing delay at each node. In the proposed system, the overhead of synchronization is avoided because every node has its own scheduling sleep, and the only sender node must wake up the receiver nodes by using preambles packets. The findings that result from comprehensive simulation show that ADE-MAC outperforms the baseline approaches in term of delivery ratio by 12%, less packet overhead by 28%, less end-to-end delay by 19%, and less power consumption by 41% compared to the baseline mechanisms.

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“…Whereas, more focus of scientists is to replace brown energy with green energy where ever possible. In every field of research, energy efficiency is the core issue 7‐11 …”

Section: Introductionmentioning

confidence: 99%

“…In every field of research, energy efficiency is the core issue. [7][8][9][10][11] Energy consumption of data centers is expected to double every 5 years. 12 Increasing energy consumption in data centers is not only becoming critical issue for service providers as it is an important factor in operational expenditures, it is also catching attention of environment watchdogs.…”

Section: Introductionmentioning

confidence: 99%

GreenCloudNet++: Simulation framework for energy efficient and secure, green job scheduling in geographically distributed data centers

Mahmood

Khan

Ahmed

et al. 2021

Trans Emerging Tel Tech

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Geographically distributed data centers are used as backbone infrastructure to meet rapidly increasing service demands of computations and data storage in cloud computing. This increase results in high energy consumption, increased operational expenditures, and high carbon footprint which are becoming points of great concern for service providers. In this research work, we present a simulation framework named GreenCloudNet++ for simulation and evaluation of energy‐efficient, green‐aware, and secure job scheduling mechanisms for geographically distributed data centers. GreenCloudNet++ has been developed as an extension to CloudNetSim++, which is designed to simulate distributed data center architectures connected with high speed networks. The functionality of CloudNetSim++ is extended by adding hierarchical job scheduling mechanism, hierarchical statistics collection mechanism and integration mechanism for green energy. Proposed model considers availability of green energy at each data center and maximizes its utilization. It considers the amount of underutilized computational resources at individual data centers while assigning jobs to the data centers, which helps to achieve better server consolidation resulting in better energy efficiency. Proposed model also relies on network load inside each data center which helps avoiding hotspots.

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Adaptive energy saving algorithms for Internet of Things devices integrating end and edge strategies

Cited by 3 publications

References 35 publications

Data Transmission Reduction in Wireless Sensor Network for Spatial Event Detection

Data Transmission Reduction in Wireless Sensor Network for Spatial Event Detection

Adaptive dynamic duty cycle mechanism for energy efficient medium access control in wireless multimedia sensor networks

GreenCloudNet++: Simulation framework for energy efficient and secure, green job scheduling in geographically distributed data centers

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