Adaptive Duty Cycle Control with Queue Management in Wireless Sensor Networks

Byun, Heejung; Yu, Ji‐Man

doi:10.1109/tmc.2012.102

Cited by 60 publications

(61 citation statements)

References 21 publications

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“…Conductivity, density and permittivity of water are different from and higher than those of air [17], [18]. Water differs from the air, as it has higher conductivity, higher density and higher permittivity.…”

Section: Underwater Electromagnetic Wave Propagationmentioning

confidence: 93%

“…Such parameters as end-to-end delay, average task waiting time, fairness, energy consumption and network lifetime have been evaluated as well. Byun et al [17] have proposed a control-based approach to duty cycle adaptation for WSNs. High performance has been achieved under variable traffic rates by using adaptive duty cycle control through queue management.…”

Section: Related Workmentioning

confidence: 99%

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The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks

Raina¹,

Jha²,

Bhattacharya³

2017

JTIT

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Abstract-Time synchronization between sensor nodes to reduce the end-to-end delay for critical and real time data monitoring can be achieved by cautiously monitoring the mobility of the mobile sink node in underwater wireless sensor networks. The Alive-in-Range Medium Access Control (AR-MAC) protocol monitors the delay of sensitive, critical and real-time data. The idea evolves as it involves reduction in duty cycle, precise time scheduling of active/sleep cycles of the sensors, monitoring the mobility of the sink node with the selection of appropriate queues and schedulers. The model for the path loss due to attenuation of electromagnetic wave propagation in the sea water is explained. The three-path reflection model evaluating reflection loss from the air-water and watersand interfaces as a function of distance between sensors and water depth is introduced. The algorithms for effective path determination and optimum throughput path determination are elaborated. The results verify that implementation of the Alive-in-Range MAC protocol has reduced the total number of packets dropped, the average queue length, the longest time in queue, the peak queue length and the average time in queue significantly, making it relevant for critical and real-time data monitoring.Keywords-Alive-in-Range MAC, effective path determination, mobile sink, optimum throughput path determination, underwater wireless sensor network.

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Section: Underwater Electromagnetic Wave Propagationmentioning

confidence: 93%

Section: Related Workmentioning

confidence: 99%

The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks

Raina¹,

Jha²,

Bhattacharya³

2017

JTIT

View full text Add to dashboard Cite

show abstract

“…To overcome this problem, several works [9,13,[15][16][17][18][19][20] allow dynamically changing sensor's polling interval. The role of these polling interval adaptation mechanism is to select the optimal polling interval according to traffic loads of sensor node.…”

Section: Related Workmentioning

confidence: 99%

Stochastic Polling Interval Adaptation in Duty-Cycled Wireless Sensor Networks

Lee

2015

International Journal of Distributed Sensor Networks

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In past decades, to achieve energy-efficient communication, many MAC protocols have been proposed for wireless sensor networks (WSNs). Particularly, asynchronous MAC protocol based on low power listening (LPL) scheme is very attractive in duty-cycled WSNs: it reduces the energy wasted by idle listening. In LPL scheme, a sensor node wakes up at every polling interval to sample the channel. If the channel is busy, the sensor node will stay in wake-up mode for receiving the data packet. Otherwise, it goes to sleep and saves power. However, wrong choice of polling interval in LPL scheme causes unexpected energy dissipation. This paper focuses on the polling interval adaptation strategy in LPL scheme with the aim of maximizing energy efficiency, defined as the number of packets delivered per energy unit. We propose a novel polling interval adaptation algorithm based on stochastic learning automata, where a sensor node dynamically adjusts its polling interval. Furthermore, our simulation results demonstrate that the polling interval asymptotically converges to the optimal value.

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“…Some works aim at improving energy efficiency for data collection with TDMA scheduling [7,[25][26][27][28][29]. Zhao and Tang [7] propose an energy-efficient TDMA schedule to accommodate periodic data collection with dynamic traffic patterns.…”

Section: Related Workmentioning

confidence: 99%

A Negotiation-Based TDMA Scheduling with Consecutive Slots Assignment for Wireless Sensor Networks

Zeng

Yang

Liu

2014

International Journal of Distributed Sensor Networks

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TDMA protocols are recognized to save energy consumption by avoiding unnecessary idle listening and communication collision. As sensor nodes are usually equipped with limited resource supply, they are thus desirable to improve network capacity and energy efficiency by adopting TDMA scheduling for wireless sensor networks (WSNs). This paper proposes a TDMA scheduling approach, which reuses time slots among sensor nodes, for WSNs. Specifically, with the idea of consecutive slots assignment, our approach can reduce both the time and energy cost of establishing nodes' schedule. Furthermore, the energy of node's switching is also reduced. To avoid the transmission of a node's result interference to all irrelevant receivers within its interference range, we develop a slot negotiation mechanism for slot assignment. We perform extensive simulations in NS-2 to evaluate our proposed approach. The results show that our approach outperforms existing TDMA scheduling in terms of time and energy overhead.

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Adaptive Duty Cycle Control with Queue Management in Wireless Sensor Networks

Cited by 60 publications

References 21 publications

The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks

The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks

Stochastic Polling Interval Adaptation in Duty-Cycled Wireless Sensor Networks

A Negotiation-Based TDMA Scheduling with Consecutive Slots Assignment for Wireless Sensor Networks

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