Adaptive duty-cycle based congestion control for home automation networks

Lee, Dong‐Ho; Chung, Kwangsue

doi:10.1109/tce.2010.5439124

Cited by 45 publications

(22 citation statements)

References 10 publications

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“…Nonetheless, some of them change the duty cycle without analyzing the value of the parameters that define the duty cycle itself, as can be seen in [2]. On the other hand, there are a few works that adapt the duty cycle by changing only one of the MAC layer parameters, either BO or SO, [3] and [4].…”

Section: Related Workmentioning

confidence: 99%

“…Hence, in [2], the authors propose a congestion control mechanism that implements an adaptive duty cycle to do resource and traffic control. Although the congestion control is accomplished, as they do not consider the BO and SO values in their duty cycle adaptation and the active time is limited by thresholds, this solution may impose in certain cases delays in the packet delivery.…”

Section: Related Workmentioning

confidence: 99%

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A duty cycle self-adaptation algorithm for the 802.15.4 wireless sensor networks

Oliveira¹,

Ghamri‐Doudane²,

Lohier³

2013

Global Information Infrastructure Symposium - GIIS 2013

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The IEEE 802.15.4 protocol is widely adopted as the standard for the physical and MAC layers of wireless sensor networks. Among other mechanisms, it implements a mechanism called duty cycle that defines the node's active time during the network lifetime. This paper proposes a dynamic beacon interval and superframe adaptation algorithm (DBSAA) that adjusts the network duty cycle through two MAC layer parameters: the Beacon Order (BO) and the Superframe Order (SO). The parameters adaptation is triggered by the changes in the traffic load (i.e. increase or decrease due to modification in the environment). Using DBSAA, the network coordinator adjust the BO and SO parameters based on four parameter estimations: the superframe occupation ratio, the collision ratio, the number of packets received by the coordinator, and the number of source nodes. Performance evaluation results show that the duty cycle adaptation taking into account the BO and SO values meets the trade-off defined by the application requirements and energy consumption while compared to two other protocols: the standard 802.15.4 protocol, which does not perform duty cycle dynamic adaptation; and the DSAA (Dynamic Superframe Adjustment Algorithm), which adapts the duty cycle by adjusting only the SO parameter.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A duty cycle self-adaptation algorithm for the 802.15.4 wireless sensor networks

Oliveira¹,

Ghamri‐Doudane²,

Lohier³

2013

Global Information Infrastructure Symposium - GIIS 2013

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show abstract

“…This method is suitable only Science Publications JCS for homogeneous application because all source nodes in the network have same reporting rate. Lee and Chung (2010) investigate an Adaptive Duty Cycle based Congestion control (ADCC). It is a energy efficient and lightweight weight congestion control scheme, implemented over a duty cycle based MAC protocol for congestion avoidance in wireless sensor networks.…”

Section: Previous Researchmentioning

confidence: 99%

Priority Based Congestion Detection and Avoidance in Wireless Sensor Networks

Jayakumari¹,

Senthilkumar

2013

Journal of Computer Science

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The primary objective of event driven wireless sensor networks is to route the detected or monitored data at the earliest to the base station depending on their degree of priority since the data generated in a sensor network has different importance. In order to avoid indiscriminate dropping of data during congestion we propose a novel congestion protocol named priority based congestion detection and avoidance in wireless sensor networks. It aims to provide differentiated data delivery during congestion which comprises of packet priority assignment based on data value, dual queue scheduler for scheduling the next packet to forward based on priority and finally a dynamic dual path congestion aware routing protocol is developed.Our simulation results and analysis shows that this new protocol provides better performance than existing protocols in terms of throughput, packet delivery ratio and packet loss.

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“…In [1][2], congestion detection and congestion control are analyzed. In [3], the proposed scheme sufficiently exerts the idle or underloaded nodes to alleviate congestion and improve the overall throughput in WSNs. In [4][5], based on the introduced congestion degree and node priority index, priority-based congestion control protocol (PCCP) utilizes a cross-layer optimization and imposes a hop-by-hop approach to control congestion.…”

Section: Introductionmentioning

confidence: 99%

Cross-layer congestion control algorithm based on compressed sensing in wireless sensor networks

Wang

et al. 2014

Proceedings of the 33rd Chinese Control Conference

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This paper presents a cross-layer congestion control algorithm based on compressed sensing (CS) in wireless sensor networks (WSNs), in which node-congestion and link-congestion are occurred simultaneously. WSNs model is provided in the first group. The second group includes controller designing: sparse signal is projected compressively in bottleneck node, which reduces the data transmission; then the compressed signal is reconstructed with convex optimization method, whose target is reconstruct original signal. Via Lyapunov function the validity of the proposed algorithm is verified. NS2 and MATLAB simulation results show that there are improvements in the dropped packets and throughput as compared to the other congestion control protocols. The proposed scheme also perfects the quality of service for the whole network.

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Adaptive duty-cycle based congestion control for home automation networks

Cited by 45 publications

References 10 publications

A duty cycle self-adaptation algorithm for the 802.15.4 wireless sensor networks

A duty cycle self-adaptation algorithm for the 802.15.4 wireless sensor networks

Priority Based Congestion Detection and Avoidance in Wireless Sensor Networks

Cross-layer congestion control algorithm based on compressed sensing in wireless sensor networks

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