An Energy-Efficient MAC Protocol Using Dynamic Queue Management for Delay-Tolerant Mobile Sensor Networks

Li, Jie; Li, Qiyue; Yu-gui, QU; Zhao, Baohua

doi:10.3390/s110201847

Cited by 7 publications

(2 citation statements)

References 11 publications

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“…The probability of winning the contention is the probability that a node is scheduled in a slot, that is

, where

for each individual node in a cluster is a function of the number packets arrivals and the energy level in the sensor nodes. A node that spends the most time in the active state, transmits the most packets, and has the highest utilization factor

[ 26 , 27 ], hence the lowest remaining energy. Therefore the remaining energy level

is proportional to the time a node spends in the active state.…”

Section: Analytical Modelmentioning

confidence: 99%

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling

Sefuba

Walingo

Takawira

2015

Sensors

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This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.

show abstract

“…The probability of winning the contention is the probability that a node is scheduled in a slot, that is

, where

[ 26 , 27 ], hence the lowest remaining energy. Therefore the remaining energy level

is proportional to the time a node spends in the active state.…”

Section: Analytical Modelmentioning

confidence: 99%

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling

Sefuba

Walingo

Takawira

2015

Sensors

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show abstract

“…In [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ], wireless sensor networks are modeled applying queueing theory. In [ 24 ], the problem of congestion control and processing management is investigated using Markov chains.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Analysis of a Buffer Overflow Duration in Data Transmission in Wireless Sensor Networks

Kempa¹

2020

Sensors

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One of the most important problems of data transmission in packet networks, in particular in wireless sensor networks, are periodic overflows of buffers accumulating packets directed to a given node. In the case of a buffer overflow, all new incoming packets are lost until the overflow condition terminates. From the point of view of network optimization, it is very important to know the probabilistic nature of this phenomenon, including the probability distribution of the duration of the buffer overflow period. In this article, a mathematical model of the node of a wireless sensor network with discrete time parameter is proposed. The model is governed by a finite-buffer discrete-time queueing system with geometrically distributed interarrival times and general distribution of processing times. A system of equations for the tail cumulative distribution function of the first buffer overflow period duration conditioned by the initial state of the accumulating buffer is derived. The solution of the corresponding system written for probability generating functions is found using the analytical approach based on the idea of embedded Markov chain and linear algebra. Corresponding result for next buffer overflow periods is obtained as well. Numerical study illustrating theoretical results is attached.

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Confidence interval based model predictive control of transmit power with reliability constraint

Sun

Yang

et al. 2019

Wireless Netw

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An Energy-Efficient MAC Protocol Using Dynamic Queue Management for Delay-Tolerant Mobile Sensor Networks

Cited by 7 publications

References 11 publications

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling

Energy Efficient Medium Access Control Protocol for Clustered Wireless Sensor Networks with Adaptive Cross-Layer Scheduling

Probabilistic Analysis of a Buffer Overflow Duration in Data Transmission in Wireless Sensor Networks

Confidence interval based model predictive control of transmit power with reliability constraint

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