GRATA: gradient‐based traffic‐aware routing for wireless sensor networks

Tan, Do Duy; Dinh, Nguyen Quoc; Kim, Dong-Seong

doi:10.1049/iet-wss.2012.0083

Cited by 28 publications

(7 citation statements)

References 20 publications

(23 reference statements)

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“…This method uses the normalized depth and traffic of network nodes to balance the flow between sensor nodes. Another part of the study proposes a model for improved control and allocation of weights to traffic-balancing routing cost and congestion window, ultimately enhancing the performance of this method compared to its counterparts such as the ESRT [38], CODA, GRAdient-based Traffic-Aware routing for wireless sensor networks (GRATA) [41], and Shortest Path First (SPF).…”

Section: ) Congestion Control Routing and Clustering Protocolsmentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms. INDEX TERMS Internet of Things, wireless sensor network, congestion control, fuzzy decision making, and back-pressure.

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Section: ) Congestion Control Routing and Clustering Protocolsmentioning

confidence: 99%

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

et al. 2020

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“…Faruque et al [1] indicate that the natural information potential field can be used to design efficient information-driven routing protocols in sensor networks. Tan et al [14] propose a distributed trafficaware routing scheme for WSNs with multiple sinks. In this scheme, an information gradient is built and gradient-based search is used for routing.…”

Section: Related Workmentioning

confidence: 99%

Lightweight construction of the information potential field in wireless sensor networks

Wang

et al. 2014

2014 23rd International Conference on Computer Communication and Networks (ICCCN)

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The information gradient-based routing protocols have been proved to be economical and effective by adopting the principle of achieving the global objective through local decision, but lightweight methods to construct the information gradient should be fully investigated, especially in a large-scale network with high information dynamics. In this paper, we focus on the construction of the information gradient by balancing convergence conditions and energy consumption. Therefore, two algorithms, Hierarchical Skeleton-based Construction Algorithm (HSCA) and Estimate value Substitution Algorithm (ESA) are proposed to achieve the goal of fastening the convergence in an energy efficient way. Both of the algorithms obey the typical assumptions on WSNs settings and the gossip-styled propagation principle. Comprehensive simulation results show that the proposed algorithms can reduce iteration times to reach a convergence status by 80% and conserve 30-50% energy consumption on average.

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“…To reduce packet delay, the algorithm allows moving from the super node to super node forwarding form to the sensor-to-sensor direct transmission form. In [20], a distributed routing algorithm is proposed for the multi-sink WSN. Using the gradient search method, the authors designed the gradient index based on both the distance-cost and the traffic delay for each node.…”

Section: Related Workmentioning

confidence: 99%

Delay constraint energy‐efficient routing based on Lagrange relaxation in wireless sensor networks

Huynh¹,

Tran²,

Tran³

et al. 2017

IET wirel. sens. syst.

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Most of researches on wireless sensor network (WSN) are focused on how to reduce energy consumption to increase the network lifetime. There are few researches solving the problem of energy optimization ensuring delay constraint. Whereas, the delay is important factor for applications that require delay-sensitive data. Several works have been published to balance the energy consumption and delay. They achieved many different results but each proposal has certain limitations. Some proposals have high computational and messaging complexity. Some others have not found the optimal solution. In this study, we investigate in finding solution to improve the energy efficiency of sensor nodes satisfying end-to-end delay to transmit data from sensor nodes to sink in multi-hop WSNs. Based on Lagrange relaxation method, we propose an aggregate cost function between energy consumption and delay as well as an efficient method to find the optimal multiplier for that objective function. We provide two algorithms to find paths with least energy consumption while maintaining end-to-end delay requirement from any sensor node to sink. Besides analyzing the complexity and convergence of the algorithm, the simulation results also show that the proposed algorithm achieved good balance between energy consumption and delay compared with the previous proposals.

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GRATA: gradient‐based traffic‐aware routing for wireless sensor networks

Cited by 28 publications

References 20 publications

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System

Lightweight construction of the information potential field in wireless sensor networks

Delay constraint energy‐efficient routing based on Lagrange relaxation in wireless sensor networks

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